Advances in Agronomy, Vol. 86

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT IN COMPLEX ENVIRONMENTAL SETTINGS S. Mahimairaja,1,* N. S. Bolan,1 D. C. Adriano2 and B. Robinson3 1

Institute of Natural Resources, Massey University, Palmerston North, New Zealand 2 Savannah River Ecology Laboratory, The University of Georgia, Aiken, South Carolina 29802 3 HortResearch, Palmerston North, New Zealand

I. Introduction II. Origin and Sources of Arsenic Contamination A. Geogenic B . Anthropogenic C . Biogenic Redistribution III. Distribution and Speciation of Arsenic in the Environment A. Distribution in Soil B . Distribution in the Aquatic Environment C . Chemical Form and Speciation IV. Biogeochemistry of Arsenic in the Environment A. Biogeochemistry of Arsenic in the Soil B . Biogeochemistry of Arsenic in Aquatic Environments V. Bioavailability and Toxicity of Arsenic to Biota A. Toxicity to Plants and Microorganisms B . Risk to Animals and Humans VI. Risk Management of Arsenic in Contaminated Environments A. Remediation of Arsenic-Contaminated Soil B . Removal of Arsenic from Aquatic Environments C . Multiscalar-Integrated Risk Management VII. Summary and Future Research Needs Acknowledgments References

Contamination of terrestrial and aquatic ecosystems by arsenic (As) is a very sensitive environmental issue due to its adverse impact on human health. Although not anthropogenic in origin, the problem of As contamination in

*Current address: Department of Environmental Sciences, Tamil Nadu Agricultural University, Coimbatore 641003, India. 1 Advances in Agronomy, Volume 86 Copyright 2005, Elsevier Inc. All rights reserved. 0065-2113/05 $35.00

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S. MAHIMAIRAJA ET AL. groundwaters of West Bengal (India) and Bangladesh has been considered of calamitous proportion because significant segment of the population is at high risk, with untold numbers already suffering from irreversible effects of As poisoning. Elsewhere, indiscriminate disposal of industrial and mining wastes has led to extensive contamination of lands, thereby exacerbating the potential for food chain contamination. With greater public awareness of As poisoning in animal and human nutrition, there has been a growing interest in developing regulatory guidelines and remediation technologies for mitigating As-contaminated ecosystems. Although the immediate needs revolve around the stripping of As from domestic water supplies as exemplified by the affected areas in Bangladesh and West Bengal, a remediation scheme should also be explored to be able to cope with pivotal needs to abate the contamination of soils, sediments, and water and the potential to compromise the quality of the food chain. A range of technologies, including bioremediation, has been applied with varying levels of success either to remove As from the contaminated medium or to reduce its biotoxicity. This review provides general overview of the various biogeochemical processes that regulate As bioavailability to organisms, including microbes, plants, animals and humans. In turn, the role of the source term, chemical form, and chemical species of As are discussed as an overture to As bioavailability. Having laid the fundamental mechanisms and factors regulating As bioavailability, we then assembled the various physical, chemical, and biological mitigative methods that have been demonstrated, some being practical, highlighting their special strengths and potential for more effective and economical widespread applications. Because of the complexity involved in dealing with contaminated sites, exacerbated by site characteristics, nature of hydrogeology, source term, chemical form, land use, and so on, no one remedial technology might suffice. Therefore, we have attempted to offer an “integrated” approach of employing a combination of technologies at multiscalar levels, depending on extenuating circumstance, with the aim of securing viable methods, economically and technologically. Future research needs, especially in the area of As bioavailability and remediation strategies, are identified. ß 2005, Elsevier Inc.

Arsenic is a unique carcinogen. It is the only known human carcinogen for which there is adequate evidence of carcinogenic risk by both inhalation and ingestion. While arsenic is released to the environment from natural sources such as wind-blown dirt and volcanoes, releases from anthropogenic sources far exceed those from natural sources. Oral exposure of arsenic to human beings however, is usually not the result of anthropogenic activity as it is with many carcinogens, but the result of natural contamination of well-water supplies by arsenic-rich geologic strata. Centeno et al. (2002)

I. INTRODUCTION Arsenic (As) is a toxic metalloid found in rocks, soil, water, sediments, and air. It enters into the terrestrial and aquatic ecosystems through a

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

3

combination of natural processes such as weathering reactions, biological activity, and volcanic emissions, as well as a result of anthropogenic activities. Excessive use of As-based pesticides and indiscriminate disposal of domestic (sewage) and industrial (timber, tannery, paints, electroplating, etc.) wastes, as well as mining activities, have resulted in widespread As contamination of soils and waterways. Arsenic in terrestrial and aquatic ecosystems attracts worldwide attention primarily because of its adverse impact on human health. The general population may be exposed to As from air, food, and water (Adriano, 2001; Sparks, 1995). Of the various sources of As in the environment, drinking water probably poses the greatest threat to human health (Smedley and Kinniburgh, 2002). People drinking As-contaminated water over prolonged periods often show typical arsenical lesions, which are a late manifestation of As toxicity. Arsenic has been unequivocally demonstrated to be both toxic and carcinogenic to humans and animals. Although trace levels of As have been shown to be beneficial in plant and animal nutrition (Leonard, 1991; Smith et al., 1998; USEPA, 1993), no comparable data are available for humans (Adriano, 2001), and elevated concentrations of As in the biosphere pose a significant threat to mankind. Arsenic contamination of surface and groundwaters occurs worldwide and has become a sociopolitical issue in several parts of the globe. For example, several million people are at risk from drinking As-contaminated water in West Bengal (India) (Chakraborti et al., 2002; Chatterjee et al., 1995) and Bangladesh (Smith et al., 2000). Scores of people from China (Wang, 1984), Vietnam (Berg et al., 2001), Taiwan (Lu, 1990), Chile (Smith et al., 1998), Argentina (Hopenhayn-Rich et al., 1998), and Mexico (Del Razo et al., 1990) are likely at risk as well. The problem of As contamination in groundwaters of West Bengal and Bangladesh has been considered of calamitous proportion because a significant segment of the population is at high risk, with untold number already suffering from irreversible effects of As poisoning (Chatterjee et al., 1995). “For many people in Bangladesh it can sometimes literally be a choice between death by arsenic poisoning and death by diarrhea,” says Timothy Claydon, country representative of Water Aid (http://Phys4. Harvard.Edu/
Wilson/Arsenic). Elsewhere, indiscriminate disposal of industrial and mining wastes has led to extensive contamination of lands. Consequently, thousands of As-contaminated sites have been reported around the world (Eisler, 2004; ETCS, 1998; Smith et al., 1998; USEPA, 1997). The economic consequences of As contamination include loss of productivity, healthcare costs, and, most importantly, imposition of As contamination as a nontariff trade barrier, preventing export sales to some countries. With greater public awareness of As poisoning in animal and human nutrition, there has been growing interest in developing guidelines and remediation technologies for mitigating As-contaminated ecosystems. A

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range of technologies, including chemical immobilization and bioremediation, has been applied with varying levels of success either to completely remove As from the system or to reduce its biotoxicity. Phytoremediation, an emerging form of bioremediation technology that uses plants to remove or stabilize contaminants, may offer a low-cost and ecologically viable means for the mitigation of As toxicity in the environment. There have been a number of reviews on As in soil (Matschullat, 2000; Smith et al., 1998) and aquatic (Korte and Fernando, 1991; Smedley and Kinniburgh, 2002) environments. However, there has been no comprehensive review on the biogeochemistry and transformation of As in relation to its remediation. The present review, therefore, aims to integrate fundamental aspects of As transformation and recent developments on As speciation in relation to remediation strategies for the risk management of As-contaminated terrestrial and aquatic ecosystems. The review first discusses the various sources and distribution of As in soil, sediments, and water. The transformation of As in these systems is examined in relation to As speciation and bioavailability. The detrimental effects of As on plant growth, microbial functions, and animal and human health are discussed with relevant examples. Various physical, chemical, and biological techniques available for remediation of As-contaminated sites are synthesized with an aim to develop integrated practical strategies at multiscalar levels to manage As-contaminated sites. Future research needs, especially in the area of As bioavailability and long-term remediation strategies, are identified. The review encourages greater interaction among soil scientists, agronomists, aquatic biogeochemists, and environmental and resource engineers in devising risk management strategies to resolve one of the worst environmental calamities of the 21st century.

II.

ORIGIN AND SOURCES OF ARSENIC CONTAMINATION

A range of As compounds, both organic and inorganic, are introduced into the environment through geological (geogenic) and anthropogenic (human activities) sources (Fig. 1). Small amounts of As also enter the soil and water through various biological sources (biogenic) that are rich in As (Table I). Although the anthropogenic source of As contamination is increasingly becoming important, it should be pointed out that the recent episode of extensive As contamination of groundwaters in Bangladesh and West Bengal is of geological origin, transported by rivers from sedimentary rocks in the Himalayas over tens of thousands of years, rather than anthropogenic.

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

Figure 1

5

Major sources and routes of arsenic in soil and aquatic ecosystems.

A. GEOGENIC Arsenic is widely distributed in all geological materials at varying concentrations. An average concentration of 1.5 to 2.0 mg As kg1 is expected in the continental crust of the earth. The mean concentrations of As in igneous rocks range from 1.5 to 3.0 mg kg1, whereas in sedimentary rocks range from 1.7 to 400 mg kg1 (Smith et al., 1998). Arsenic ranks 52nd in crustal abundance and it is a major constituent in more than 245 minerals (O’Neill, 1995). These are mostly sulfide-containing ores of copper (Cu), nickel (Ni), lead (Pb), cobalt (Co), zinc (Zn), gold (Au), or other base metals. The most important ores of As include pyrites, realgar, and orpiment. Arsenic is introduced into soil and water during the weathering of rocks and minerals followed by subsequent leaching and runoff. Therefore, the primary source of As in soil is the parent (or rock) materials from which it is derived (Yan-Chu, 1994). Geogenic contamination of As in soils (Table II)

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S. MAHIMAIRAJA ET AL. Table I Selected References on Sources of Arsenic in Soil and Aquatic Environments

Source Broiler litter Cattle manure (composted) Coal Cow manure Dikes and ores Earthworms Fly ash FYM from cattle Lake weeds Metallurgical ore waste Mine spoils Mine tailing Mushroom (edible) from contaminated soil Poultry manure Rice straw Sewage sludge

Concentration (mg kg1)

Reference

34.6 3.0–5.2

Jackson and Miller (2000) Raven and Loeppert (1997)

2–825 15,005 6–8.5 1242–30,800 1358 2–6300 0.8–2.6 83–1262 52,700–63,000 >20,000 62,350 7000 1420

Adriano et al. (1980) Bencko and Symon (1977) Raven and Loeppert (1997) Ongley et al. (2003) Langdon et al. (2002) Page et al. (1979) Nicholson et al. (1999) Aggett and Aspell (1980) Magalhaes et al. (2001) Porter and Peterson (1975) Kim et al. (2002) Roussel et al. (2000) Larsen et al. (1998)

50 16.8 91.8 11.9–21.0

Arai et al. (2003) Jackson and Bertsch (2001) Abedin et al. (2002) Department of Health (NZ) (1992); Ross et al. (1991) Caper et al. (1978); Raven and Loeppert (1997)

8.1–14.3

and water (Table III) has been reported in many parts of the world. One typical example is the extensive As contamination of groundwaters in Bangladesh and West Bengal in India. Based on As geochemistry, three probable mechanisms have been offered for As mobility in groundwaters of West Bengal and Bangladesh (Bose and Sharma, 2002): i. Mobilization of As due to the oxidation of As-bearing pyrite minerals. Insoluble As-bearing minerals such as arsenopyrite (FeAsS) are rapidly oxidized [Eq. (1)] when exposed to atmosphere, releasing soluble arsenite [As(III)], sulfate (SO2 4 ), and ferrous iron [Fe(II)] (Mandal et al., 1996). The dissolution of these As-containing minerals is highly dependent on the availability of oxygen and the rate of oxidation of sulfide (Loeppert, 1997). The released As(III) is partially oxidized to arsenate [As(V)] by microbially mediated reactions (Wilkie and Hering, 1998).

Table II Selected References on Arsenic Concentration in Contaminated Soils Reference

Australia Australia Australia (NSW) Australia (NSW) Austria Bangladesh Belgium Belgium Brazil China England England (southwest) Germany Ghana Ghana India (West Bengal India (West Bengal) Japan Mexico Mexico New Zealand

Tannery wastes Arsenical pesticides Mining and processing of arsenopyrite ore Cattle dip Ore vein Geological Metal alloy and metallurgical industries Arsenic factory Metallurgical plant wastes Wastewater Tin, copper, and arsenic mining Geological Storage of organoarsenic-based chemical warfare agents Mining Mining Geological (through irrigation water) Disposal from arsenical pesticides manufacturing Arsenic mine and smelter Mining activities Runoff from mining waste Timber treatment with CCA

Slovakia Thailand (southern) USA USA (Colorado) USA (Florida) USA (Louisiana) USA (southern California)

Coal-burning power station Geologcal Mine tailing Pesticide spray Industrial activities Arsenic dipping vat Crude oil storage facility

<1–435 9.8–124 9300 37–3542 700–4000 1.7–56.7 36,000 25,000 –35,000 636–748 40–120 120–52,600 110 Up to 250,000 (mean 923) 2.1–48.9 189–1025 11.5–28.0 20,100–35,500 391–459 14,700 >2.0 6100 161–790 376–10,440 80–5475 8.8–139 Up to 5000 48–3421 >1000 0.2–660 555 30–2300

Sadler et al. (1994) Bishop and Chisholm (1961) Ashley and Lottermoser (1999) McLaren et al. (1998) Geiszinger et al. (2002) Alam and Sattar (2000) Cappuyns et al. (2002) Dutre et al. (1998) Magalhaes et al. (2001) Jiang and Ho (1983) Kavanagh et al. (1997) Mitchell and Barr (1995) Pitten et al. (1999) AmonooNeizer et al. (1996) Bowell et al. (1994) Amit et al. (1999); Chatterjee and Mukherjee (1999) Roychowdhury et al. (2002) Hiroki (1993) Ongley et al. (2003) Naranjo-Pulido et al. (2002) CMPS & F (1995) Yeates et al. (1994) Armishaw et al.(1994) McLaren (1992) Keegan et al. (2002) Williams et al. (1996) Jones et al. (1997) Folkes et al. (2001) Chirenje et al. (2003) Masscheleyn et al. (1991) Wellman et al. (1999)

7

As content (mg kg1)

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

Source of contamination

Country

8

Table III Selected References on Arsenic Concentration in Contaminated Aquatic Media

Argentina Australia Australia (NSW)

Bangladesh Bangladesh Bangladesh Bangladesh Bangladesh Brazil Chile Chile Chile (north) China (inner Mongolia) England (SW) Germany (northern Bavaria) India (West Bengal)

Water source

Source of contamination

As content (
g liter1)

Reference

Groundwater River sediments Water sample from a mine shaft and waste dump seepage Tube wells Tube wells Groundwater Tube wells Tube well water River sediments Natural water Drinking water Drinking water Groundwater

Geological Mining Geological

3000 32.8–42.7 13,900

Sbarato and Sanchez (2001) Taylor (1996) Ashley and Lottermoser (1999)

Geological Geological Geological Geological Geological Metallurigical plant Geological Geological Geological Geological

260–830 >50 0.7–640 1–535 0.01–0.071 347 mg kg1 950–13,080 750–800 600 1088–1354

Ali and Tarafdar (2003) Yokota et al. (2002) Frisbie et al. (2002) Watanabe et al. (2001) Alam and Sattar (2000) Magalhaes et al. (2001) Munoz et al. (2000) Smith et al. (2000) Hopenhayn-Rich et al. (1996) Guo et al. (2001)

River Deep water wells

Tin mine drainage Geological

Dissolved As(III) 240 10–150

Hunt and Howard (1994) Heinrichs and Udluft (1999)

Groundwater

Geological

0.5–135.9

Nag et al. (1996)

S. MAHIMAIRAJA ET AL.

Country

Tube well water Drinking water Tube well water Tube well water Tube well water Groundwater Groundwater Well water Tube wells Tube wells River, Waikato Lake Ohakuri Sediments from Waikato river Deep well water Well water Geothermal water Lake Groundwater from a confined sandstone aquifer Groundwater

Geological Geological Geological Geological Geological Geological Geological Geological Geological Geological Geothermal release Geothermal release Geothermal Geological Geological Geological Geological Geological

22–2000 212 82–170 85 2.7–170 200–3700 293 267–1070 >10 >50 3–121 37–60 8700–156,100 >10 671 1135 200
mol liter1 12,000

Mazumder et al. (1988) Mahata et al. (2003) Roychoudhury et al. (2002a) Roychoudhury et al. (2002b) Tokunaga et al. (2002) Mandal et al. (1996) Kondo et al. (1999) Gomez-Arroyo et al. (1997) Neku and Tandukar (2003) Shrestha et al. (2003) Robinson et al. (1995) Aggett and Aspell (1980) Robinson et al. (1995) Wai et al. (2003) Chen et al. (1995) Buyuktuncel et al. (1997) Oremland et al. (2000) Schreiber et al. (2000)

16–176

Nimick (1998)

Groundwater

Natural hydrological and geochemical Geological

USA (New England) USA (New Hampshire) Vietnam

>10

Ayotte et al. (2003)

Well water

Geological

0.003–180

Peters et al. (1999)

Tube well water

Geological

1–3050

Berg et al. (2001)

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

India (West Bengal) India (West Bengal) India (West Bengal) India (West Bengal) India (West Bengal) India (West Bengal) Japan Mexico Nepal Nepal New Zealand New Zealand New Zealand Taiwan Taiwan Turkey USA (California) USA (eastern Wisconsin) USA (Madison)

9

10

S. MAHIMAIRAJA ET AL. þ FeAsS þ 13Fe3þ þ 8H2 O ! 14Fe2þ þ SO2 4 þ 13H þ H3 AsO4 ðaqÞ

ð1Þ

ii. Dissolution of As-rich iron oxyhydroxides (FeOOH) due to onset of reducing conditions in the subsurface. Under oxidizing conditions, and in the presence of Fe, inorganic species of As are predominantly retained in the solid phase through interaction with FeOOH coatings on soil particles. The onset of reducing conditions in such environments can lead to the dissolution of FeOOH coatings. Fermentation of peat in the subsurface releases organic molecules (e.g., acetate) to drive reductive dissolution of FeOOH, resulting in the release of Fe(II), As(III), and As (V) present on such coatings [Eq. (2)] (McArthur et al., 2000; Nickson et al., 2000). 8FeOOH  AsðsÞ þ CH3 COOH þ 14H2 CO3 ! 8Fe2þ þ AsðdÞ þ 16HCO 3 þ 12H2 O

ð2Þ

where As(s) is sorbed As and As(d) is dissolved As. iii. Release of As sorbed to aquifer minerals by competitive exchange with phosphate (H2 PO 4 ) ions that migrate into aquifers from the application of fertilizers to surface soil (Acharya et al., 1999). However, the second mechanism involving dissolution of FeOOH under reducing conditions is considered to be the most probable reason for excessive As accumulation in groundwater (Harvey et al., 2002; Smedley and Kinniburgh, 2002). Relatively high concentrations of naturally occurring As can appear in some areas as a result of inputs from geothermal sources or As-rich groundwaters (Smedley and Kinniburgh, 2002). For example, Robinson et al. (1995) found high As concentrations (3800
g liter1) in waste geothermal brine from the main drain at Wairakei geothermal field in New Zealand. River and lake waters receiving inputs of geothermal waters were found to contain up to 121
g As liter1. Arsenic concentration is usually higher in soil and shales than in earth crust because of its continuous accumulation during weathering and translocation in colloidal fractions. Arsenic may also be coprecipitated with Fe hydroxides and sulfides in sedimentary rocks. Therefore, Fe deposits and sedimentary Fe ores are rich in As, and the soils derived from such sedimentary rocks may contain as high as 20 to 30 mg As kg1 (Zou, 1986). Arsenic in the natural environment occurs in soil at an average concentration of about 5 to 6 mg kg1 (i.e., background level), but this varies among geological regions (Peterson et al., 1981). Volcanoes are also considered as a geogenic source of As to the environment with the total atmospheric annual

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11

emissions from volcanoes being estimated at 31,000 mg (Smith et al., 1998; Walsh et al., 1979).

B. ANTHROPOGENIC Arsenic is also being introduced into the environment through various anthropogenic activities. These sources release As compounds that differ greatly in chemical nature (speciation) and bioavailability. Major sources of As discharged onto land originate from commercial wastes (
40%), coal ash (
22%), mining industry (
16%), and the atmospheric fallout from the steel industry (
13%) (Eisler, 2004; Nriagu and Pacyna, 1988). Arsenic trioxide (As2O3) is used extensively in the manufacturing of ceramic and glass, electronics, pigments and antifouling agents, cosmetics, fireworks, and Cubased alloys (Leonard, 1991). Arsenic is also used for wood preservation in conjunction with Cu and chromium (Cr), i.e., copper–chromium–arsenate (CCA). Some important physicochemical properties of As compounds are presented in Table IV. Industries that manufacture As-containing pesticides and herbicides release As-laden liquid and solid wastes that, upon disposal, are likely to contaminate soil and water bodies. For example, indiscriminate discharge of industrial effluents from the manufacturing of Paris Green (copper acetoarsenite, an arsenical pesticide) resulted in the contamination of soil and

Table IV Physicochemical Properties of Arsenic Compoundsa

Compounds Arsenic–As (element) Arsenic trioxide or arsenous oxide–As2O3 Arsenic oxide or arsenic pentoxide–As2O5 Arsenic sulfide or arsenic trisulfide–As2S3 Dimethylarsinic acid or cacodylic acid (CH3)2AsO(OH) Arsenate or salts of arsenic acid–HAsO4 a

Density (g cm3)

Water solubility (g liter1)

Melting point (  C)

Boiling point (  C)

5.727 3.738

Insoluble 37 at 20  C

613 312.3

– 465

4.32

1500 at 16  C

–

3.43

5104 at 18  C

315 (decomposes) 300

–

829 at 22  C

200

–

5.79

Very slightly

720 (decomposes)

–

From Lide (1992) and IARC (1980).

707

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S. MAHIMAIRAJA ET AL.

groundwater in residential area of Calcutta, India (Chatterjee et al., 1999). Similarly, in New Zealand, timber treatment effluent is considered to be the major source of As contamination in aquatic and terrestrial environments (Bolan and Thiyagarajan, 2001). Because As is widely distributed in the sulfide ores of Pb, Zn, Au, and Cu, it is released during their mining and smelting processes. The flue gases and particulate from smelters can contaminate nearby ecosystems downwind from the operation with a range of toxic metal(loid)s, including As (Adriano, 2001). Coal combustion not only releases gaseous As into the atmosphere, but also generates fly and bottom ash containing varied amounts of As. Disposal of these materials often leads to As contamination of soil and water (Beretka and Nelson, 1994). Arsenic is present in many pesticides, herbicides, and fertilizers. The use of horticultural pesticides, lead arsenate (PbAsO4), calcium arsenate (CaAsO4), magnesium arsenate (MgAsO4), zinc arsenate (ZnAsO4), zinc arsenite [Zn(AsO2)2], and Paris Green [Cu(CH3COO)2.3Cu(AsO2)2] in orchards has contributed to soil As contamination in many parts of the world (Merry et al., 1983; Peryea and Creger, 1994). Soil contamination due to the use of organoarsenical herbicides such as monosodium methanearsonate (MSMA) and disodium methanearsonate (DSMA) was also reported (Gilmore and Wells, 1980; Smith et al., 1998). The use of sodium arsenite (NaAsO2) to control aquatic weeds has contaminated small fish ponds and lakes in several parts of United States with As (Adriano, 2001). Arsenic contamination in soil was also reported due to the arsenical pesticides used in sheep and cattle dips to control ticks, fleas, and lice (McBride et al., 1998; McLaren et al., 1998). A study of 11 dip sites in New South Wales indicated considerable surface soil (0 –10 cm) contamination with As (37–3542 mg kg1) and significant movement of As (57–2282 mg kg1) down the soil profile at 20–40 cm depth (McLaren et al., 1998). Continuous application of fertilizers that contain trace levels of As also results in As contamination of soil, thereby reaching the food chain through plant uptake (McLaughlin et al., 1996).

C. BIOGENIC REDISTRIBUTION Biological sources contribute only small amounts of As into soil and water ecosystems. However, plants and micro- and macroorganisms affect the redistribution of As through their bioaccumulation (e.g., biosorption), biotransformation (e.g., biomethylation), and transfer (e.g., volatilization). Arsenic accumulates readily in living tissues because of its strong affinity for proteins, lipids, and other cellular components (Ferguson and Gavis, 1972). Aquatic organisms are particularly known to accumulate As, resulting in considerably higher concentrations than in the water in which they live (i.e.,

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biomagnification). Upon disposal or consumption they subsequently become a source of environmental contamination. Arsenic could be transferred from soil to plants and then to animals and humans, involving terrestrial and aquatic food chains. For example, poultry manure addition is considered to be one of the major sources of As input to soils. In the Delaware–Maryland– Virginia peninsula along the eastern shore of the United States, 20–50 mg of As is introduced annually to the environment through the use of As compounds (e.g., Roxarsone, ROX) in poultry feed (Christen, 2001). However, in many situations the soil–plant transfer of As is low (Smith et al., 1998) and it is important to recognize that metal(loid)s loading through manure application may overestimate their actual net accumulation in soil, as a substantial portion of the metal(loid)s in manure originate in crop uptake and are therefore being recycled within a production system (Bolan et al., 2004).

III. DISTRIBUTION AND SPECIATION OF ARSENIC IN THE ENVIRONMENT A. DISTRIBUTION IN SOIL Generally, As concentrations in uncontaminated soils seldom exceed 10 mg kg1. However, anthropogenic sources of As have elevated the background concentration of As in soils (Adriano, 2001). For example, in areas near As mineral deposits, As levels in soils may reach up to 9300 mg kg1 (Ashley and Lottermoser, 1999). The distribution of As in contaminated soils around the world is presented in Table II. Depending on the nature of the geogenic and anthropogenic sources, As concentration in soils can range from <1 to 250,000 mg kg1. However, there is a large fluctuation among countries due to variation in soil parent material, for example, calcareous soils can be expected to have higher levels of As than noncalcareous soils (Aichberger and Hofer, 1989). As discussed in Section II,B, although the dominant source of As in soils is geological, additional inputs may also be derived locally from industrial sources, such as smelting and fossilfuel combustion products and agricultural sources, namely pesticides and phosphatic fertilizers. In soils, As forms a variety of inorganic and organic compounds (Vaughan, 1993). Arsenic forms solid precipitates with Fe, aluminium (Al), calcium (Ca), magnesium (Mg), and Ni. A number of studies involving solidphase speciation have shown that As is prevalent mostly in the oxalate fractions associated with amorphous and crystalline Fe and Al oxides, indicating the strong affinity of As for these soil components (Wenzel et al., 2001). The soluble As concentration in soil is largely determined by

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S. MAHIMAIRAJA ET AL.

redox conditions, pH, biological activity, and adsorption reactions. The adsorption and mobility of As in soil are affected more strongly by the presence of H2PO 2 ion than any other anions. Arsenic is subject to both chemical and biological transformations in soils, resulting in the formation of various species.

B. DISTRIBUTION

IN THE

AQUATIC ENVIRONMENT

Arsenic in an aquatic environment is distributed in both the aqueous solution and sediments. Elevated concentrations of As in natural waters are usually associated with As-rich sedimentary rocks of marine origin, weathered volcanic rocks, fossil fuels, geothermal areas, mineral deposits, mining wastes, agricultural use, and irrigation practices (Korte and Fernando, 1991). Uncontaminated waters usually contain less than 0.001
g As liter1. In contaminated areas, however, high levels of As have been reported in water bodies (Table III). It should be noted that considerable variation in As concentration exists within the same geological area as reported by different researchers. The World Health Organization (WHO, 1981) recommends that the As concentration in drinking water not exceed 10
g liter1. However, the limit in many countries, including Bangladesh and the United States, is still 50
g As liter1. The widespread occurrence of high concentrations of As in water in many parts of the world caused the U.S. President George W. Bush to state “Arsenic is a natural substance that sometimes causes problems,” and to reverse the previous government’s decision to accept a five times lower WHO standard (i.e., 10
g liter1) (Kaiser, 2001). As discussed earlier, one of the principal causes of high As concentrations in subsurface waters is the reductive dissolution of hydrous Fe oxides and/or the release of adsorbed As (Smedley and Kinniburgh, 2002). Deuel and Swoboda (1972) proposed that the release was primarily due to reduction (and dissolution) of “ferric arsenates” instead of changes in the As speciation. The high As in groundwater can be associated with reducing conditions, resulting from the presence of dissolved organic carbon, particularly in alluvial and delta environments. The groundwater of the Bengal basin is the most notable example. While the exact mechanisms responsible for this remain uncertain, it is possible that both reductive dissolution and desorption of As from oxides and clay play an important role in elevating As concentration (Smedley and Kinniburgh, 2002). A significant proportion of As in aquatic environment is derived from the sediments, and the relative distribution of As in water and sediments depends mainly on the nature and amounts of sediments (Table III). Arsenic in river sediments is highly variable, ranging from 32.8–42.7 mg kg1 (Australia) (Taylor, 1996) to 8700–156100 mg kg1 (New Zealand)

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15

(Robinson et al., 1995). The As-rich sediments act as a buffer in maintaining the As concentration in water bodies, thereby controlling the dynamics and bioavailability of As in the aquatic environment.

C. CHEMICAL FORM AND SPECIATION Speciation of metal(loid)s can be achieved by both analytical processes and on the basis of theoretical consideration. The analytical processes involved in the speciation of metal(loid)s in soils can be grouped into solidphase speciation and solution-phase speciation. In view of the limitations of many of the analytical procedures used in speciation, often species distribution is predicted using a number of speciation models (e.g., GEOCHEM by Mattigod and Sposito, 1979; MINTEQ2 by Allison et al., 1991) that are based on theoretical chemical (thermodynamic) concepts. Although the fundamental thermodynamic principles that drive these models are based on scientific facts, problems arise when these principles are applied to complex natural matrixes. A large number of sequential extraction schemes have been used for soils, generally attempting to identify metal(loid)s held in any of the following fractions: soluble, exchangeable, sulfide/carbonate bound, organically bound, oxides bound, and residual or lattice mineral bound. The bioavailability of metal(loid)s in soils has been examined using the physiologically based in vitro chemical fractionation schemes that include the physiologically based extraction test (PBET), potentially bioavailable sequential extraction (PBASE), and gastrointestinal (GI) test. These innovative tests predict the bioavailability of metal(loid)s in soil/sediments when ingested by animals and humans. A vast number of analytical techniques are available for solution-phase characterization and quantification of metal(loid)s. These include electroanalytical techniques, cation/anion-exchange resins and chemical adsorbents to fractionate ionic and nonionic forms, ultrafiltration, dialysis, and gel permeation techniques for molecular size fractionation, spectroscopic techniques measuring the oxidation state of elements, X-ray techniques to measure trace element distribution, and chromatographic techniques to measure the phase distribution of metal(loid)s. Arsenic speciation is determined by both biotic and abiotic variables. Arsenic speciation is important not only for understanding the biogeochemical cycling of As in different ecosystems and mechanisms of As accumulation and detoxification, but also for designing safe disposal options of As-rich biomass (Tu et al., 2003; Watt and Le, 2003). In soil, As occurs both as inorganic [As(III) and As(V)] and as organic forms. Trivalent As can exist as arsenous oxide (As2O3), arsenious acid

16

S. MAHIMAIRAJA ET AL.

2 3 (HAsO2), arsenite (H2AsO 3 , HAsO3 , AsO3 ) ions, arsenic trichloride (AsCl3), arsenic sulfide (AsS3), and arsine (AsH3). Pentavalent As commonly occurs as arsenic pentoxide (As2O5), orthoarsenic acid (H3AsO4), metaarse2 3 nic acid (HAsO3), and arsenate (H2AsO 4 , HAsO4 , AsO4 ) ions. The presence of different forms of organic As, such as monomethylarsonic acid [MMA, CH3AsO(OH)2], dimethylarsenic acid [DMA, (CH3)2AsO(OH)], trimethylarsine oxide [(CH3)3AsO], methylarsine (CH3AsH2), dimethylarsine [(CH3)2AsH] and trimethylarsine [TMA, (CH3)3As], has also been observed in contaminated soil and water (Gao and Burau, 1997). The most common forms of As in the environment are the inorganic oxyions of As(III) and As(V). Arsenite [As(III)] is more toxic and relatively mobile in contaminated soils, whereas arsenate [As(V)] is relatively less toxic. Both As(III) and As(V) compounds are highly soluble in water and may change valency states depending on the pH and redox conditions. Results of a literature search on the speciation of As in environmental and biological samples are presented in Table V. In contaminated soils, generally As(V) predominates over As(III), whereas in waters, the relative proportion of these two species varies depending on a number of factors, including As sources, redox potential, pH, and microbial activity. Masscheleyn et al. (1991) studied the influence of redox potential and pH on As speciation and solubility in a contaminated soil. They observed that alterations in the oxidation state of As, as influenced by redox potential and pH, greatly affected its solubility in soil. At oxic redox levels (500–200 mV), As solubility was low and the major part (65–98%) of the As in soil solution was present as As(V). At alkaline pH, the reduction of As(V) to As(III) released substantial proportions of As into solution. Under moderately reducing conditions (0–100 mV), As solubility was controlled by the dissolution of Fe oxyhydroxides. At an anoxic redox level of 200 mV, soluble As increased 13-fold as compared to an oxic redox level of 500 mV. The apparent slow kinetics of the As(V) to As(III) transformation and the high concentrations of manganese (Mn) present indicate that, under reducing conditions, As solubility could be controlled by the Mn3(AsO4)2 phase. In a study conducted in New Zealand, Aggett and Aspell (1976) showed that with the occasional exception of a few summer months, over 90% of the As in water of the Waikato River and dams was present as As(V). Freeman (1985) detected As(III) in the Waikato River only when cyanobacteria (Anabaena oscillaroides) reduced As(V) to As(III). While reviewing the As cycle in natural waters, Ferguson and Gavis (1972) suggested that As(III) is stable and mobile only in a narrow range of Eh and pH conditions. Conditions must be reducing enough to produce dissolved As(III) but not so reducing as to produce sulfide, which could precipitate As(III). Under conditions where sulfide is formed, realgar (AsS) and orpiment (As2S3) occur as stable solids. At low pH, HAsS2(aq) is the

Table V Selected References on Chemical Speciation of Arsenic in Various Media Speciation techniquea

Acid mine drainage

LC-ICP-MS

Coal fly ash Drinking water (Natural water)

IC-ICP-MS –

Geothermal waters Groundwater

HPLC/GFAS and HPLC/HGAAS LC-ICP-MS

Groundwater

FI-HG-AAS

Groundwater

FI-HGAAS

Groundwater close to cattle tick dip sites Human urine (Bangladesh) Mine tailings

ICP-AES

Mine tailings Mung bean seedlings

XANES and EXAFS LC-ICP-MS

Mushroom (edible)

HPLC-ICP-MS

Plant—Chinese brake (Pteris vittata L.)

HPLC - AFS

IC-FI-HG-AAS AAS

Fraction/concentration As(III) ¼ 13,000
g liter1 As(V) ¼ 3700
g liter1 As(V) >> As(III) Particulate and soluble As contributed 11.4 and 88.6% of the total As, respectively. In the case of soluble As, As(III) and As(V) were 47.3 and 52.7%, respectively Na2HAsO4 was predominant 1

As(III) ¼ 720
g liter As(V) ¼ 1080
g liter1 As(III) and As(V) were present in 1:1 ratio As(III) was present at about 50% of the total As As(V) was dominant

Bednar et al. (2002) Jackson and Miller (1998) Thirunavukkarasu et al. (2001)

Buyuktuncel et al. (1997) Bednar et al. (2002) Samanta et al. (1999) Chatterjee et al. (1995) Kimber et al. (2002) Alauddin et al. (2003) Kim et al. (2002) Foster et al. (1997) Van den Broeck et al. (1998) Larsen et al. (1998)

Tu et al. (2003)

17

As (III) was the major species Total As ¼ 62350 mg kg1 63–99% as As(V) As(V) was dominant Roots: As(III) > As(V) Leaves: As(V) >> As(III) DMA 68–74% Methylarsonic acid 0.3–2.9% Trimethylarsine oxide 0.6–2.0% Arsenic acid 0.1–6.1% 94% of As in fronds was primarily as As(III)

Reference

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

Environment

(continued )

18

Table V (continued) Environment

Speciation techniquea

IC-ICP-MS

Poultry wastes

IC-ICP-MS

Rice grain

IC-ICP-MS

Rice straw River waters

Sewage sludge

HPLC-ICP-MS HGAAS using Na-tetrahydro borate(III) reductant HG-CT-AAS

Soil (contaminated)

HPLC-ICP-MS

Soil (contaminated)

Soil (contaminated) Well waters

Extraction with 1 M phosphoric acid plus 0.1 M ascorbic acid and measurement in LC-UV-HG-ICP/MS XAFS AAS

Wetlands

XANES

Dissolved As mostly as As(V) 130
g liter1 Organoarsenic compounds (Roxarsone) was dominant with trace levels of DMA and As(V) Total As 0.11–0.34 mg kg1 Inorganic As 11–91% remaining DMA As(V) > As(III) As(V) was the principal species

Reference

Gault et al. (2003) Jackson and Bertsch (2001)

Heitkemper et al. (2001) Abedin et al. (2002) Quinaia and Rollember (2001)

At pH 5.0 inorganic-As > organic-As At pH 6.5 organic-As > inorganic-As Total As ¼ 10000 mg kg1 As(V) ¼ >90% As(V) was the major species

Carbonell-Barrachina et al. (2000)

Mg3(AsO4)2 8H2O 670
g liter1 total dissolved arsenic; As(III) was dominant: As(III)/As(V) ratio ¼ 2.6 As(III) > As(V)

Foster et al. (1997) Chen et al. (1994)

Matera et al. (2003) Garcia-Manyes et al. (2002)

La Force et al. (2000)

a HPLC, high-performance liquid chromatography; ICP, inductively coupled plasmanalysis; MS, mass spectroscopy; LC, liquid chromatography; HG, hydride generation; XAFS, X-ray absorption fine structure spectroscopy; FI, flow injection; AAS, atomic absorption spectrometry; GFAAS, graphite furnace atomic absorption spectrometry; XANES, X-ray absorption near edge structure (XANES) spectroscopy; EXAFS, extended X-ray absorption fine-structure spectroscopy; AFS, atomic florescence spectrometry; CT, cold trapping.

S. MAHIMAIRAJA ET AL.

Polluted urban watercourse

Fraction concentration

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

19

predominant species if sulfide is present, whereas AsS 2 species predominate at pH greater than 3.7. Studying a stratified lake, Seyler and Martin (1989) showed that Mn, which has a higher redox potential than Fe and As, was reduced before the complete depletion of dissolved oxygen, and any dissolved As was present predominantly in the form of As(V). As conditions became more reducing, there was a rapid and concomitant increase of Fe and As and a reversal of As speciation such that as As(III) became more dominant, As2S3 and As concentrations correspondingly decreased. In groundwater, As is predominantly present as As(III) and As(V). The major As species in freshwater are As(III) and As(V), and small amounts of MMA, DMA, and methylated As(III) have also been detected. In seawater, As speciation differs in the surface and deep zones, with As(V) and As(III) species dominating the respective zone. In addition to the aforementioned species, Watt and Le (2003) noticed that an array of uncharacterized As species also appeared to constitute a significant portion of the total As present in water. The identification of these compounds is necessary to fully understand the As biogeochemistry in water.

IV. BIOGEOCHEMISTRY OF ARSENIC IN THE ENVIRONMENT The biogeochemistry and dynamics of As and other metal(loid)s vary between soil and aquatic environments. In the case of soil environment, a substantial proportion of the metal(loid)s is associated with the solid phase and their fate is strongly influenced by physicochemical interactions (e.g., adsorption–desorption) with the solid phase. Whereas in the case of aquatic environment, depending on the sediment content, a substantial proportion of metal(loid)s remains in solution and their fate is controlled largely by biological transformation.

A. BIOGEOCHEMISTRY OF ARSENIC IN THE SOIL Smith et al. (1998) presented a comprehensive review on the biogeochemistry of As in the soil environment. Here we include a brief discussion on various biogeochemical reactions of As in soil, which is helpful in understanding its behavior and in developing remediation strategies. As already discussed, As can exist in soil in different oxidation states but mostly as inorganic species, As(V) or As(III) (Adriano, 2001; Masscheleyn et al., 1991). In addition to inorganic species, microbial methylation of As in soil results in the release of organic methylarsenic compounds, such as MMA and

20

S. MAHIMAIRAJA ET AL.

Figure 2 Arsenic dynamics in contaminated soil and aquatic ecosystems.

DMA, and ultimately arsine gas (Smith et al., 1998; Vaughan, 1993). Both inorganic and organic species of As undergo various biological and chemical transformations in soils, including adsorption, desorption, precipitation, complexation, volatilization, and methylation (Fig. 2). Some important biogeochemical reactions of As and their significance in soil and aquatic environments are given in Table VI. The most thermodynamically stable 2 species of As(III) (i.e., H3AsO3 and H2 AsO 4 ) and As(V) (i.e., HAsO4 ) occur over the normal soil pH range of 4 to 8.

1. Adsorption and Surface Complexation The adsorption and retention of As by soils determine its persistence, reactions, movement, transformation, and ecological effects (toxicity). As in the case of most other metal(loid)s and nonmetals, one of the most

Table VI Some Important Biochemical Reactions of Arsenic and their Environmental Significance Process

Oxidation

Eq. No.

2 þ AsO3 4 þ H ¼ HAsO4 ðlog Ka ¼ 11:60Þ  þ AsO3 4 þ 2H ¼ H2 AsO4 ðlog Ka ¼ 18:35Þ þ AsO3 4 þ 3H ¼ H3 AsO4 ðlog Ka¼ 20:60Þ 2 þ AsO3 3 þ H ¼ HAsO3 ðlog Ka ¼ 13:41Þ  þ AsO3 þ 2H ¼ H AsO 2 3 3 ðlog Ka ¼ 25:52Þ  þ AsO3 3 þ 3H ¼ H3 AsO3 ðlog Ka ¼ 34:74Þ Chemical 2 2HFeðVIÞO 4 þ 3H3 AsðIIIÞO3 ! 2FeðIIIÞ þ 3HAsðVÞO4 2þ þ þ HAsO þ 2H O ! 2Fe þ H AsO þ 2H 2Feþ 2 2 3 4 3  þ H3 AsOo3 þ OH þ O2 ðgÞ ! H2 AsO 4 þ O2 þ 2H 3 þ MnO2 þ 2H þ AsO3 ! Mn2þ þ AsO3 þ H2 O 4 MnO2 þ HAsO2 þ 2Hþ ! Mn2þ þ H3 AsO4

Microbial 2þ Fe2 O3 þ 4Hþ þ AsO3 þ AsO3 þ 2H2 O 3 ! 2Fe 4

ðCH3 Þ2 AsH ! ðCH3 Þ2 AsOðOHÞ ðCH3 Þ3 As ! ðCH3 Þ2 AsOðOHÞ Reduction

Significance

Reference

3 4 5 6 7 8

As(V), a less toxic As species, can exist in solution as H3AsO4, 3 3 H2AsO As(III), 4 , HAsO4 , and AsO4 a highly toxic As species, exists at natural pH values as H3AsO3, and H2AsO 3

Wilkie and Hering (1996)

9 10 11 12 13

As(III) is more toxic and mobile and hence it is desirable to oxidize to As(V), which is less toxic and relatively immobile. Chemical oxidation of As(III) may occur via Fe, or H2O2, or MnO2(VI) and Fe(VI) and is found very effective in the removal of As from water

Kocar and Inskeep (2003); Lee et al. (2003); Oscarson et al. (1981)

14

Competition of Fe(III) as a terminal electron acceptor in microbial respiration results in the oxidation of As(III) Arsine (di- and trimethyl) compounds can be oxidized by bacteria and fungi in the methylation process In waters reduction of As(V) to As(III) is possible at low pH and pE Reduction of As(V) to As(III) is possible in the presence of Fe even at a pE value of 0.5 at pH 7, while at pH 8 such reduction is not possible unless pE is <1.5 The formation of sulfides in reducing environment facilitates the reduction of As(V) to As(III) with the latter species dominating in the porewater

Masscheleyn et al. (1991)

15 16 17

2þ þ 5H2 O ! H3 AsO3 þ 2FeðOHÞ3 ðs Þ þ 3Hþ H2 AsO 4 þ 2Fe 2þ HAsO2 þ 5H2 O ! H3 AsO3 þ 2FeðOHÞ3 ðs Þ þ 2Hþ 4 þ 2Fe

18 19

þ  H2 AsO 4 þ 3H þ 2e ! H3 AsO3 þ H2 O 2H3 AsO3 þ 6Hþ þ 3S 2 ! As2 S3 þ 6H2 O 2As2 S3 þ 4e ! 4AsS þ 2S2

20 21 22

Bose and Sharma (2002) Bose and Sharma (2002)

Moore et al. (1988)

21

3 þ  AsO3 4 þ 2H þ 2e ! AsO3 þ H2 OðlogK ¼ 5:293Þ

O’Neill (1995)

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

Acid–base reactions

Reactions

(continued )

22

Table VI (continued ) Process

Methylation

Reactions

Significance

ðCH3 Þ2 AsOðOHÞ ! ðCH3 Þ2 AsH

23

H3 AsO4 ! H3 AsO3 ! ðCH3 ÞAsOðOHÞ ! ðCH3 Þ AsOðOHÞ 2 2 ðCH3 Þ2 AsOðOHÞ ! ðCH3 Þ AsH 2 ðCH3 Þ2 AsOðOHÞ ! ðCH3 Þ As

24 25 26

þ FeOHþ AsO3 4 þ 3H ! FeH2 AsO4 þ H2 O  þ FeOHþ AsO3 4 þ 2H ! FeHAsO4 þ H2 O 3 FeOHþ AsO3 4 ! FeOHAsO4 þ FeOHþ AsO3 3 þ 3H ! FeH2 AsO3 þ H2 O

27 28 29 30

3 AlOHþ AsO3 4 ! AlOHAsO4 2 þ þ H ! AlAsO AlOHþ AsO3 4 4 þ H2 O  þ AlOHþ AsO3 4 þ 2H ! AlHAsO4 þ H2 O

31 32 33

Dimethylarsinic acid can be reduced by bacteria to dimethyl arsine Biochemical transformations are mediated by microorganisms in terrestrial and aquatic environments. Biomethylation of inorganic and organic As is considered a major detoxification process Arsenic removal from water and wastewater is governed by sorption processes. Hydrous ferric oxide (FeOH) is an important sorbent in natural and engineered aquatic systems. Adsorption of As(III) increases with decreasing As/Fe ratios. As(V) adsorption is higher at high pH Natural Boehmite (monohydrates of trivalent aluminium oxide) is found to adsorb large amounts of As(V) and thus is suitable for As removal from water and wastewaters A molar ratios (FeAs) of 4, and an optimum pH of 5 at 33  C achieved less residual As in solution Liming results in the precipitation of As as calcium arsenate, which is unstable in aqueous environment and becomes insoluble As(V) can be immobilized through coprecipitation with hydrous Fe oxide or hydrous Mn oxide

3

Adsorption

Precipitation Fe2 ðSO4 Þ3 þ 2H3 AsO4 ! 2FeAsO4 þ 3H2 SO4

34

H3 AsO4 þ CaðOHÞ2 ! CaHAsO4 :2H2 O

35

FeðOHÞ3 þ H3 AsO4 ! FeAsO4 :2H2 Oþ H2 O  þ 3MnOOHþ 2HAsO2 4 þ 7H þ 3e ! Mn3 ðAsO4 Þ2 þ 6H2 O

36 37

Reference O’Neill (1995) O’Neill (1995)

Wilkie and Hering (1996)

Dousova et al. (2003)

Papassiopi et al. (1996)

Stefanakis and Kontopoulos (1988) Masscheleyn et al. (1991)

S. MAHIMAIRAJA ET AL.

Eq. No.

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

23

commonly reported, and perhaps the first reaction to occur in soils, is As adsorption onto soil particles. Numerous studies have dealt with As sorption on to specific minerals and uncontaminated soils. Ferrous oxides/ hydroxides are involved most commonly in the adsorption of As in both acidic and alkaline soils. Carbonate minerals adsorb As in calcareous soils. In acidic soils, Mn oxides and biogenic particles play a dominant role in the adsorption of As (Arai et al., 2003; Oscarson et al., 1981). Arsenic is known to have high affinity for oxide surfaces, and several biogeochemical factors are found to play a major role in adsorption. Soil particle size, organic matter, type and nature of constituent minerals, pH, redox potential, and competing ions have all been shown to influence As adsorption (Chiu and Hering, 2000; Jones et al., 2000; Smith et al., 1998). In general, adsorption of As(V) decreases with increasing pH. In contrast, adsorption of As(III) increases with increasing pH. The effect of pH on As adsorption varies considerably among soils and is dependent on the nature of mineral surface. In soils containing low oxidic minerals, increasing the pH has little effect on the amount of As(V) adsorbed, whereas in highly oxidic soils, adsorption of As(V) decreases with increasing pH (Smith et al., 1998). This decrease is attributed to two interacting factors: (i) the increasing negative surface potential on the plane of adsorption and (ii) the increasing concentration of negatively charged As(V) species present in the soil solution. Brookins (1988) observed that amorphous Al and Fe hydroxides adsorbed more As(V) than As(III). The surface charge properties of variable charge soil components are strongly influenced by pH. At acid pH these soil components contain large amounts of positive charges, and adsorption of As (V) may become important. Arsenate ions are attracted to positively charged colloidal surfaces either at broken clay lattice edges where charged Al3þ groups are exposed or on surfaces of Fe and Al oxides and hydroxide films. Many researchers have investigated As(III) and As(V) adsorption reactions and surface speciation on major soil minerals (i.e., metal oxyhydroxides and phyllosilicate minerals) using various macroscopic and spectroscopic techniques. Arsenate is strongly adsorbed at acidic pH values on amorphous Al (OH)3, a-Al2O3, ferrihydrite, and hematite (Arai et al., 2001; Raven et al., 1998; Xu et al., 1988). Several spectroscopic [e.g., extended X-ray adsorption fine structure spectroscopy (EXAFS)], macroscopic [e.g., electrophoretic mobility (EM)], and thermodynamic modeling (e.g., surface complexation model) have revealed innersphere bidentate binuclear and/or monodentate As(V) complexes on ferrihydrite, goethite, amorphous Fe and Al oxides, and the bayerite polymorph (Arai et al., 2001; Fendorf et al., 1997) and on both inner sphere and outer sphere As(III) complexes on Al oxides (Arai et al., 2001; Goldberg and Johnston, 2001). In general, As(V) sorption on amorphous Al and Fe oxides is characterized by an apparent sorption maximum

24

S. MAHIMAIRAJA ET AL.

at pH 4, whereas As(III) sorption maximum occurs in the pH range of 7 to 8.5. The type and quantity of silicate clay minerals present in soil also influence the retention of As. Soils having higher clay content retain more As than sandy soils with low clay content. The degree of As sorption onto silicate clay minerals decreases in the order of kaolinite > vermiculite > montmorillonite (Goldberg and Glaubig, 1988; Manning and Goldberg, 1997). The silicate clay minerals also generally adsorb more As(V) than As (III), and adsorption by clay minerals is affected by pH (Lin and Puls, 2000). Arsenic and P belong to the same chemical group and both have comparable dissociation constants for their acids and solubility products for  their salts. Therefore, H2AsO 4 and H2PO4 ions compete for the same sorption sites in soils, although some sites are preferentially available for  the sorption of either H2PO 4 or H2AsO4 ions. A number of studies have shown that among the competing anions, the H2PO 4 suppresses As(V) sorption by soil more significantly than chloride (Cl), nitrate (NO 3 ), and sulfate (SO2 ) (Matera and LeHecho, 2001; Manful et al., 1989; O’Neill, 4 1995; Thanabalasingam and Pickering, 1986). Soil organic matter content also affects the adsorption of As and thus its bioavailability as organic molecules compete with As for sorption to surface sites. Thanabalasingam and Pickering (1986) showed that the maximum adsorption of As(V) on humic acids occurred around pH 5.5, whereas adsorption of As(III) increased up to pH 8. At high pH, the solubilization of humic substances reduces As retention. While there is very little information available on the effects of organic matter on As adsorption, Grafe et al. (2001) have shown that humic acid reduces both As(V) and As(III) adsorption on geothite between pH 3 and 9. Several functional groups present on these complex organic polymers may be responsible for binding As. Further, dissolved organic carbon substances are capable of increasing the mobility and bioavailability of As in soil and water ecosystems through redox reactions and soluble complex formation. Depending on various factors affecting the adsorption of As, part of the As adsorbed onto soil constituents is desorbed and released into the soil solution. Soil pH and phosphate addition are the most important factors that control the desorption of As. For example, Woolson et al. (1973) observed that phosphate addition to an As-contaminated soil displaced about 77% of the total As in the soil. Although phosphate addition increases As solubility, Peryea (1991) reported that desorption of As was dependent on the soil type, as no increase in As concentration in soil solution from a volcanic soil (with high anion-fixing and pH-buffering capacity) was observed. This suggests that only large additions of P (>400 mg kg1) would affect the As solubility in these soils (Chen et al., 2002; Smith et al., 1998). In long-term poultry litter-amended agricultural soils, Arai et al. (2003)

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

25

observed that the extent of As desorption from the litter increased with increasing pH from 4.5 to 7, but only 15% of the total As was released at pH 7, indicating the presence of insoluble phases and/or strongly retained soluble compounds. Elkhatib et al. (1984) suggested that the sorption of As (III) is not reversible in soil. One of the important factors affecting the adsorption/desorption characteristics of As is the contact time (residence time) in soils and sediments. For example, Arai and Sparks (2002) reported that the longer the residence time (1 year), the greater the decrease in As(V) desorption at pH 4.5 and 7.8, suggesting nonsingular reactions. The surface transformation processes, such as rearrangement of surface complexes and conversion of surface complexes into aluminum arsenate-like precipitates, might be responsible for the decrease in As(V) reversibility with aging. Thus, the fate and transport of the contaminants must be predicted/modeled not only on short-term adsorption and desorption studies, but also on long-term reactions. Although the desorption process is important in relation to the bioavailability and mobility of As, only a few studies have focused on desorption of As from soil constituents. Further studies on desorption are needed to fully understand the chemistry of As in soils, which might help in developing appropriate remediation technologies.

2.

Redox Reactions

In soil and aquatic environments, redox reactions not only determine the nature of chemical species, but also the solubility and mobility of As and thus its environmental significance. Arsenic in soils is subject to both abiotic and biotic redox reactions [Eqs. (9–23) in Table VI]. The Fe(III) oxides, Mn (III) oxides, and organic compounds in soils play a major role in catalyzing the abiotic oxidation of As(III) through an electron transfer mechanism (Adriano, 2001; Oscarson et al., 1981). Similarly, abiotic redox reactions are also responsible for the release of As from arsenopyrite through oxidation by Fe(III), considered to be a predominating process inducing the release of As into the groundwater in areas where well waters are highly contaminated with As [Eq. (1)]. Under moderately reducing conditions, As(III) is often found to be the predominant species in soil solution (Marin et al., 1993; Masscheleyn et al., 1991; Onken and Hossner, 1995). Studies by Deuel and Swoboda (1972) showed that there was an increase of As(III) in soil solution over time under flooded conditions. This was attributed to the release of As(V) during reductive dissolution of Fe oxyhydroxide minerals that have a strong affinity for As(V) and the subsequent reduction of As(V) to As(III).

26

S. MAHIMAIRAJA ET AL.

Biotransformation of As, involving the oxidation of As(III) to As(V) and the reduction of As(V) to As(III) by a variety of microorganisms, may occur in contaminated soil. For example, Alcaligenes faecalis was found to oxidize As(III) to As(V) (Osborne and Ehrlich, 1976; Phillips and Taylor, 1976). Bacteria, fungi, and algae are also able to reduce As(V) to As(III) and subsequently to arsine (Frankenberger and Losi, 1995). However, the effect of microbial activity on the transformation and movement of As in soil is difficult to quantify (Smith et al., 1998).

3.

Biomethylation

Arsenic in soil is also subject to biological transformation resulting in the formation of organo-arsenicals and other compounds [Eqs. (24 –26) in Table VI]. Inorganic As can undergo microbially mediated biochemical transformation, i.e., the hydroxyl group of arsenic acid [AsO(OH)3] is replaced by the CH3 group to form MMA, DMA, and TMA (Maeda, 1994). The pathway of As(V) methylation initially involves the reduction of As(V) to As(III), with the subsequent methylation of As(III) to dimethylarsine by coenzyme S-adenosylmethionine (Frankenberger and Losi, 1995). Methylation is often enhanced by sulfate-reducing bacteria. In addition to bacteria, several fungal species also have shown their ability to reduce As. Inorganic As is incorporated by autotrophic organisms such as algae and is then transported through the food chain. Arsenic becomes progressively methylated during this transfer. Therefore, methylation of As is considered a major detoxifying processes for these microorganisms (Adriano, 2001). The methylated As species is also subject to volatilization and photochemical reactions that may eliminate As from soil. Demethylation of methylarsenicals can occur under both aerobic and anaerobic conditions. Anaerobic demethylation reactions may result in the formation of toxic and reactive AsH3 from less toxic DMA, whereas aerobic demethylation of DMA is likely to yield As(V), thereby retaining As in the system. Although AsH3 undergoes rapid chemical oxidation under oxic conditions, it can exist for long periods in an aerobic environment. Because the demethylation process often produces CO2 in addition to CH4, it is preceded by oxidative assimilatory pathways used in substrate metabolism rather than by dissimilatory lyses. Methylation, demethylation, and reduction reactions are also important in controlling the mobilization and subsequent distribution of arsenicals in soils. These transformations are promoted by microbes; however, it is still not clear if in situ biomethylation is a common phenomenon. Although the presence of organic forms of As in soil can be associated with the application of anthropogenic compounds, such as fertilizers and pesticides (O’Neill,

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

27

1995), their presence is often linked to biomethylation. However, biomethylation reactions occur readily in aquatic environment and these reactions are discussed in Section IV.B.

4.

Leaching

Due to its strong adsorption onto organic and clay colloids, As(V) is likely to persist in soils for a long time, especially in fine-textured soils with high Fe contents (Woolson, 1983). In these soils, leaching of As(V) is low and therefore As contamination of groundwater is considered unlikely (Woolson, 1983). However, under certain environmental conditions (i.e., low pH and low Eh), As would leach in the soil profile, thereby contaminating the surface and groundwaters (Hingston et al., 2001; Ruokolainen et al., 2000). Considerable amounts of solubilized As could move downward in the soil profile with leaching water, especially in coarse-textured soils. It is for this reason that abandoned wood preservative (CCA) sites may threaten groundwater quality. For example, in examining the leaching of Cu, Cr, and As from CCA solution through free-draining, coarse-textured surface and subsurface soils using undisturbed soil lysimeters, McLaren et al. (1994) observed that the cumulative amounts of As leached ranged from 4 to 30% of the total As applied. Arsenic is present as a simple salt (soluble Na2HAsO4) in CCA, which is liable for leaching losses, especially in coarse-textured soils. Whereas when As is present as an organically complexed form (e.g., in sewage sludge), it is not readily leached in soils (McLaren et al., 1994). Again the role of H2PO 4 ions in enhancing the mobility of As, especially AsO2 ions, should be noted. For example, Qafoku et al. (1999) noticed 4 that the leaching of As in a column containing mineral soil incorporated with As-rich poultry manure increased with the addition of a phosphate compound. The arsenic concentration in the leachate was approximately 10 times higher when Ca(H2PO4)2 was used to leach the soil column as compared to the CaSO4 solution. In the presence of the Ca(H2PO4)2 solution, a maximum As concentration of 800
g liter1 was found in the leachate, much higher than the WHO maximum permissible limit of 10
g liter1 for drinking water.

B. BIOGEOCHEMISTRY OF ARSENIC IN AQUATIC ENVIRONMENTS As in the case of soil systems, the environmental and ecological significance of As dynamics in aquatic ecosystem is largely determined by its biogeochemical reactions, which are discussed in this section.

28

S. MAHIMAIRAJA ET AL.

1.

Adsorption and Desorption

Arsenic is stable in four oxidation states (+5, +3, 0, 3) under the Eh conditions that occur in aquatic systems. At high Eh values (mostly exist in 2 oxygenated waters), arsenic acid species (i.e., H3AsO4, H2AsO 4 , HAsO4 , 3 and AsO4 ) are stable. At mildly reducing conditions, arsenious acid species 2 (i.e., H3AsO3, H2AsO 3 , and HAsO3 ) become stable (Korte and Fernando, 1991; Penrose, 1974; Smith, 1986). The speciation of As in aquatic environment is critical in controlling the adsorption/desorption reactions with sediments. Adsorption to sediment particles may remove As(V) from contaminated water, as well as inhibiting the precipitation of As minerals such as scorodite (FeAsO4 2H2O) that control the equilibrium aqueous concentration (Foster et al., 1997). Under the aerobic and acidic to near-neutral conditions (typical of many aquatic environments), As(V) is adsorbed very strongly by oxide minerals in sediments. The highly nonlinear nature of the adsorption isotherm for As(V) in oxide minerals ensures that the amount of As adsorbed is relatively large, even when dissolved aqueous concentrations of As are low. Such adsorption occurring in natural environments protects water bodies from widespread As toxicity problems. Adsorption of As species by sediments are as follows: As(V) > As(III) > As (II) > DMA (Smedley and Kinniburgh, 2002). In As-contaminated sediments, Clement and Faust (1981) found that a significant portion of the As was bound in organo-complex forms and indicated that adsorption–desorption equilibrium must be considered as well as the redox effects in examining the dynamics of As in aquatic environment. As pH increases, especially above pH 8.5, As desorbs from the oxide surfaces, thereby increasing the concentration of As in solution. Desorption of As from As-contaminated sediments at high pH is the most likely mechanism for the development of groundwater As problems under the oxidizing conditions (Robertson, 1989; Smedley et al., 2002). These adsorption and desorption reactions of As in the aquatic environment have not been studied in detail under varied ecological conditions and therefore require greater attention.

2. Biotransformation Arsenic undergoes a series of biological transformations in the aquatic environment, yielding a large number of compounds, especially organoarsenicals. Certain reactions, such as oxidation of As(III) to As(V), may occur both in the presence and in the absence of microorganisms, whereas other reactions, such as methylation, are not thermodynamically favorable in water and can occur only in the presence of organisms. In neutral

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

29

oxygenated waters, As(V) is the thermodynamically favored form, whereas As(III) is stable under reducing conditions (Ferguson and Gavis, 1972). Some bacteria and marine phytoplankton are capable of reducing As(V) to As(III) or oxidizing As(III) to As(V) (Andreae, 1977). Biological reduction of As(V) to As(III) reportedly occurs most easily at a pH between 6 and 6.7 (Korte and Fernando, 1991). For example, Aggett and Aspell (1980) noticed that As was usually found as As(V) in the Waikato River of New Zealand, but during the spring and summer months, As(III) was often found to predominate. The reduction of As(V) to As(III) has been attributed to biological components of the river ecosystem. This biotransformation has been reported to occur in various aquatic systems, mediated by bacteria (Johnson, 1972; Myers et al., 1973) and algae (Andreae and Klumpp, 1979; Sanders 1983; Sanders and Windom, 1980). A cyanobacteria (Anabaena oscillaroides)–bacteria assemblage was also found to reduce As(V) to As (III) (Freeman, 1985). Benthic microbes are capable of methylating As under both aerobic and anaerobic conditions to produce methylarsines and methyl-arsenic compounds with a generic formula (CH3)nAs(O)(OH)3n where n may be 1, 2, or 3. MMA and DMA are the common organoarsenicals in river water. Methylated As species could result from direct excretion by algae or microbes or from degradation of the excreted arsenicals or more complex cellular organoarsenicals. Methylation may play a significant role in the mobilization of As by releasing it from the sediments to aqueous environment. The presence of organoarsenicals in river sediments is evidence that methylation occurs in the sediments (Anderson and Bruland, 1991). The rate of methylation/demethylation reactions and the consequent mobilization of arsenicals are affected by adsorption by sediments and soils. Primary producers such as algae take up As(V) from solution and reduce this to As(III) prior to methylation of the latter to produce MMA and DMA; the methylated derivatives are then excreted. This may be considered to represent a detoxification process in respect to the organism involved. Arsenic is taken up by algae due to its chemical similarity to phosphate. Although the detoxification of As by microorganism can be achieved through methylation, the element may be of significant toxicity to phytoplankton and periphyton communities in marine environments. Both macro- and microorganisms accumulate As in their tissues. Concentrations in organisms may be considerably higher than in the water in which they live, but unlike mercury (Hg), there is little, if any, concentration upward through the food chain (i.e., bioaugmentation). The toxicity of As to aquatic organisms is similar to its effects on terrestrial life, i.e., As(V) is much less toxic than As(III) (Ferguson and Gavis, 1972). Arsenate can replace H2PO 4 uptake in phosphate-deficient waters and can then be accumulated by algae. In a study of As accumulation in the food

30

S. MAHIMAIRAJA ET AL.

chain, it has been reported that most of the As accumulated by algae was in a nonmethylated form, which was bound strongly to protein or polysaccharides in the algal cell (Maeda et al., 1990). Such transformation can be stimulated by adding nutrients. Microbial formation of volatile arsine or other volatile-reduced compounds may play a role in the discharge of As to the atmosphere. Arsenite can be reduced and methylated to DMA, which can be further methylated or reduced and may eventually volatilize (Korte and Fernando, 1991).

V.

BIOAVAILABILITY AND TOXICITY OF ARSENIC TO BIOTA

Arsenic is used as an additive in various metal alloys and in wood preservation. Its toxic properties are exploited in the formulation of arsenical herbicides and insecticides. To date, however, geogenic As is largely responsible for most human poisoning (Smith et al., 2000). Due to its environmental and human health impact, As toxicity has been researched and documented more extensively than any other metal(loid)s.

A. TOXICITY

TO

PLANTS

AND

MICROORGANISMS

Arsenic contamination of soil and water poses a serious threat to plants and animals. Plants and microorganisms are known to accumulate As in their tissues and exhibit a certain degree of tolerance. However, at high concentrations, As is toxic to nearly all forms of life. Some selected references on toxicity (risks) of As in microorganisms, higher plants, and animals are presented in Table VII. Biotoxicity is mostly determined by the nature and bioavailability of As species present in the contaminated habitat. An average toxicity threshold of 40 mg kg1 has been established for crop plants (Sheppard, 1992). At high concentrations, As in plants inhibits plant metabolic processes, such as photosynthesis through interference of the pentose–phosphate pathway, thereby inhibiting growth and often leading to death (Marques and Anderson, 1986; Tu and Ma, 2002). Arsenite penetrates the plant cuticle to a greater degree than As(V) and generally results in the loss of turgor (Adriano, 2001). Biomass production and yields of a variety of crops have been shown to reduce significantly at high concentrations of As in soils (CarbonellBarrachina et al., 1997). For example, significant yield reductions of barley (Hordeum vulgare L.) and ryegrass (Lolium perenne L.) have been reported

Table VII Potential Risks of Arsenic to Terrestrial Biota

Soil

360 50–100 70–100

Soil

Soil

0, 15, 20, 30, 50, and 100 as power station fly ash or disodium hydrogen arsenate 100

Seedling beds

1000 and 2000

Soil

0–280 kg As ha1 (fine sandy loam soil) 0–560 kg As ha1 (clay soil). NaAsO2 applied at rates up to 720 kg As ha1 0.01, 0.1, or 1.0 mM PbCl2 or Na2HAsO4 in 1% agar þ modified Arnon and Hoagland solution. 1.0–5.5 1.0–5.0

Soil Water & nutrient solutions Soilless culture Soilless culture

Effect Yield reduction in barley; plants showed symptoms of As toxicity and P deficiency Reduction in growth of vegetative and root system in tomatoes As contents in rice cultivars exceeded the WHO standard 50% yield reduction in wheat, barley, and oats. Sensitivity to As was in the order: oats > wheat > barley Decreased the height of the apple tree: 100% growth inhibition at above 100 mg kg1 Substantial growth reduction in white spruce seedlings Significant growth reduction in cotton and soyabean As toxicity persisted for four growing seasons in potatoes and peas Growth inhibition of pea seedlings at all concentrations. As resulted in more growth inhibition than Pb No phytotoxic effect on radish Organic arsenicals (MAA > DMA) more phytotoxic than inorganic As to turnip, accumulating above the threshold for As in food crops (1.0 mg kg1)

Reference Lambkin and Alloway (2003) Miteva (2002) Xie and Huang (1998) Toth and Hruskovicova (1977)

Benson (1976) Rosehart and Lee (1973) Deuel and Swoboda (1972)

Steevens et al. (1972) Paivoke (1979)

Carbonell-Barrachina et al. (1999a) Carbonell-Barrachina et al. (1999b)

31

(continued )

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

Concentrationa

Medium

32

Table VII Concentrationa

Medium 0–10

Water culture

0, 0.04, 0.4, 4.0, and 20

Green algae in culture medium

78.7
g liter1 As(III) 159.3
g liter1 As(V) 12.4 (MMA) 35.7 (DMA) >400 Up to 8000

Earthworms

0.5–50
M As

PDA (phenyldichloroarsine), As(III) and As(V) at varied concentrations mg kg1 or mg liter1 unless specified.

a

Effect

Reference

Significant yield reduction in tomato (no tissue chlorosis or necrosis was observed) Growth inhibition of mung bean above 2.2
g g1 of As in the dry mass Increasing As decreased plant dry weight in cabbage. Most As remained in the roots with only 10–25% transported to the tops,
2% entered the inner leaves Raising phosphate concentration in the medium increased As(V) toxicity to freshwater green alga Scenedesmus obliguus

Carbonell-Barrachina et al. (1997)

Caused total fatality to earthworms Tolerated by Lumbricus rubellus and Dendrodrilus rubidus tolerated Toxicity follows: PDA > As(III) > As(V) and 24 h LD50 values 189.5, 191.0, and 519.4
mol kg1, respectively

Van den Broeck et al. (1997) Hara et al. (1977)

Chen et al. (1994)

Yeates et al. (1994) Langdon et al. (1999) Li et al. (1994)

S. MAHIMAIRAJA ET AL.

Nutrient solution Growth medium

(continued )

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

33

with the application of only 50 mg As kg1 soil (Jiang and Singh, 1994). Plant uptake of As is greatly influenced by its species in soil. As has already been discussed, different species have different solubility and mobility, thereby differing in their bioavailability to plants. Marin et al. (1992) reported that the order of As availability to rice (Oryza sativa L.) is as follows: As(III) > MMA > As(V) > DMA. They observed that upon absorption, DMA is readily translocated to the plant shoot, whereas As (III), As(V), and MMA accumulate primarily in the roots. While the application of As(V) and DMA did not affect rice growth, both As(III) and MMA were found to be phytotoxic to rice. Burlo et al. (1999) noted that both MMA and DMA in tomato plants (Lycopersicon esculentum Mill.) had a greater upward translocation than As(III) and As(V). In general, the accumulation of As in the edible parts of most plants is low (O’Neill, 1995), which is attributed to a number of reasons, including (Wang et al., 2002) (i) low bioavailability of As in soil; (ii) restricted uptake by plant roots; (iii) limited translocation of As from roots to shoots; and (iv) phytotoxicity and subsequent premature plant death at relatively low As concentrations in plant tissues. Apart from chemical forms, it has been shown that the phytotoxicity of As varies with the soil conditions. For example, Reed and Sturgis (1963) reported that As inhibits rice plant growth more strongly under submerged soil conditions than under upland soil conditions, because As(V) is reduced to As(III), which is more soluble and more toxic to plants in submerged soil. Arsenic phytotoxicity is expected to be greater in sandy soils than in other soil types, as the former soils generally contain low amounts of Fe and Al oxides and silicate clays, which have been implicated in the adsorption of As from soil solution (Sheppard, 1992; Smith et al., 1998). The antagonistic and synergistic effects of various nutrient anions also determine the phytotoxicity of As to some extent. For example, Davenport and Peryea (1991) reported a reduction of As uptake by plants with the application of phosphate, which was attributed to H2PO 4 ion-induced inhibition of As(V) uptake by plant roots. In contrast, Woolson (1973) observed that a phosphate application increased As availability and As uptake by plants, which was attributed to the H2PO 4 ion-induced release of As(V) to the soil solution. Most plants do not accumulate enough As to be toxic to animals and humans. Growth reductions and crop failure are the main consequences of soil As contamination (Walsh and Keeney, 1975). Thus the major hazard for animal and human systems is derived from direct ingestion of As-contaminated soil or water (Smith et al., 1998). Arsenic contamination of soil and water has a direct impact on microbial community and structure. At high concentrations, a reduction in the soil microbial population has been reported by a number of researchers (Bisessar, 1982; Van Zwieten et al., 2003). In general, as in the case of higher plants, As(III) is more toxic to microorganisms than As(V) (Maliszewska

34

S. MAHIMAIRAJA ET AL.

et al., 1985). Hiroki (1993) has shown that As(III) is more toxic to bacteria and actinomycetes than As(V) and that fungi not only display a higher tolerance to As(III) than bacteria and actinomycetes, but also show the same tolerance to both As(V) and As(III). Arsenite also inhibits enzyme activities in soil (Tabatabai, 1977). However, many bacterial communities are found to adapt to As-contaminated environments by developing resistance and tolerance mechanisms (Smith et al., 1998). Earthworms usually have a high capacity for accumulating toxic elements; however, the extent of accumulation is dependent on the type of element and on soil properties (Ma, 1982). Earthworms are known to inhabit As-rich metalliferous soils (Langdon et al., 1999). They are likely to accumulate As present in soils through ingestion of solid-phase As and dermal contact with pore water As. Yeates et al. (1994) observed a complete elimination of earthworms in soils contaminated by As derived from timber preservatives at concentrations of 400 and 800 mg As kg1, but few earthworms at 100 mg As kg1. In contrast, Langdon et al. (1999) found populations of Lumbricus rubellus and Dendrodrilus rubidus resistant to As(V) and Cu present in mine spoil containing up to 8000 mg As kg1 and 750 mg Cu kg1. The difference in the threshold levels of As for earthworms between these two experiments may be attributed to the difference in the bioavailability of As, which is a function of speciation and substrate matrix. Earthworms generally show resistance to As toxicity; however, the mechanisms of such resistance are not fully understood (Langdon et al., 2003).

B. RISK

TO

ANIMALS

AND

HUMANS

Drinking water is the most important source of dietary intake of As by animals and humans (Fitz and Wenzel, 2002). However, food also forms a source of As exposure (Adriano, 2001). The occurrence of inorganic As in drinking water has been identified as a source of risk for human health even at relatively low concentrations. As a consequence, more stringent safer limits for As in drinking water have been proposed (Wenzel et al., 2001). Soluble As compounds are rapidly absorbed from the gastrointestinal tract (Hindmarsh and McCurdy, 1986). Several studies in humans indicate that both As(III) and As(V) are well absorbed across the gastrointestinal tract (USDHHS, 2000). Studies involving the measurement of As in fecal excretion in humans indicated that almost 95% of oral intake of As(III) is absorbed (Bettley and O’Shea, 1975). This was supported by studies in which urinary excretion in humans was found to account for 55–80% of daily intakes of As(III) or As(V) (Buchet et al., 1981; Crecelius, 1977; Mappes, 1977). It has also been reported that both MMA and DMA are also well absorbed (75–85%) across the gastrointestinal tract (Buchet et al., 1981).

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

35

Once absorbed, simultaneous partial oxidation of As(III) to As(V) and partial reduction of As(V) to As(III) occur, yielding a mixture of As(III) and As(V) in the blood. The As(III) may undergo enzymatic methylation primarily in the liver to form MMA and DMA, but the rate and relative proportion of methylation production vary among animal species. Most As is promptly excreted in the urine as a mixture of As(III), As(V), MMA, and DMA, and relatively smaller amounts are excreted in the feces. Some As may remain bound to tissues, depending on the rate and extent of methylation. Monomethylarsonic acid may be methylated to DMA, but neither MMA nor DMA is demethylated to yield As(III) or As(V). Arsenic may accumulate in skin, bone, and muscle and its half-life in humans is between 2 and 40 days (USDHHS, 2000). Teratogenic effects of As in chicks, golden hamsters, and mice have been reported. Arsenic does not appear to be mutagenic in bacterial and mammalian assays, although it can induce chromosomal breakage, chromosomal aberration, and chromatid exchange. Studies have shown that As may be an essential element at trace concentrations for several animals such as goats, rats, and poultry, but there is no evidence that it is essential for humans (USEPA, 1988). The acute toxicity of As compounds in humans is a function of their rate of removal from the body. Arsine is considered to be the most toxic form, followed by As(III), As(V) and organic As compounds (MMA and DMA). Lethal doses in humans range from 1.5 mg kg1 (diarsenic trioxide) to 500 mg kg1 of body weight (DMA). Acute As intoxication associated with the ingestion of contaminated well water has been reported in many countries (Table VIII). The single most characteristic effect of long-term exposure to As is a pattern of skin changes, including hyperkeratosis (a darkening of the skin and appearance of small “corns” or “warts” on the palms, soles, and torso; Fig. 3). A small number of the “corns” may ultimately develop into skin cancer (USDHHS, 2000). Early symptoms of As poisoning in humans include abdominal pain, vomiting, diarrhea, muscular pain, and weakness, with flushing of the skin (Armstrong et al., 1984; Cullen et al., 1995; Moore et al., 1994). These symptoms are often followed by numbness and tingling of the extremities, muscular cramping, and the appearance of an erythematous rash. Further symptoms may appear within a month, including burning paraesthesias of the extremities, hyper/hypopigmentation (mottled or multicolor skin), Mee’s lines on fingernails, and progressive deterioration in motor and sensory responses (Fennell and Stacy, 1981; Murphy et al., 1981). Acute oral As poisoning at doses of 8 mg As kg1 and above have been reported to affect the respiratory system (Civantos et al., 1995). A number of studies in humans have shown that As ingestion may lead to serious effects on the cardiovascular system (Cullen et al., 1995). Anemia and leukopenia

36

S. MAHIMAIRAJA ET AL. Table VIII Selected References on Effect of Arsenic on Human Health

Effect and/or symptoms Neoplasia and induce DNA damage and inhibit DNA hypermethylation Malanosis, melanokeratosis (malignancy) in adults Hyper pigmentation, keratosis, weakness, anemia, burning sensation of eyes, solid swelling of legs, liver fibrosis, chronic lung disease, gangrene of toes, neuropathy Chromosomal aberrations and chromatid exchanges Skin cancer

Bladder cancer Lung cancer Peripheral vascular, cardiovascular, cerebrovascular diseases Diabetes Adverse reproductive outcome Neuropathy

Countries

Reference

France USA

Burnichon et al. (2003) Goering et al. (1999)

Bangladesh and India

Saha (2003)

Bangladesh Bangladesh Bangladesh and India Bangladesh Bangladesh

Karim (2000) Mazumder (2003) Rahman et al. (2001) Kadono et al. (2002) Karim (2000)

India

Mahata et al. (2003)

Bangladesh India USA USA USA Bangladesh India USA USA USA USA

Mazumder (2003) Mukherjee et al. (2003) Brown and Ross (2002) Hamadeh et al. (2002) Hall (2002) Kadono et al. (2002) Das et al. (1996) Brown and Ross (2002) Brown and Ross (2002) Hall (2002) Brown and Ross (2002)

USA USA Bangladesh and India India India

Brown and Ross (2002) Brown and Ross (2002) Mazumder (2003) Mukherjee et al. (2003) Mukherjee et al. (2003)

India India

Mukherjee et al. (2003) Chattopadhyay et al. (2002) Yih et al. (2002) Hughes (2002) Hughes (2002)

Paresthesias and pains in the distal parts of extremities Dysfunction of sensory nerve Apoptosis and necrosis in developing brain cells Inducement of oxidative stress, activating stress gene expression Altered DNA methylation and cell proliferation Bone marrow depression Hypertension Gastrointestinal disturbances

USA India USA

Hepatocellular carcinoma

China

Taiwan USA USA

Hall (2002) Rahman et al. (1999) Cullen et al. (1995); Hall (2002) Liu et al. (2001) (continued )

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

37

Table VIII (continued ) Effect and/or symptoms Hepatic fibrosis Blackfoot disease

Acute intake results: vomiting, diarrhea, low blood pressure, and high heart beat Teratogenesis in unborn children

Countries

Reference

India Taiwan Bangladesh, China, India, Taiwan, and USA USA

Santra et al. (2000) Wang et al. (1997) Wai et al. (2003)

Bangladesh

Karim (2000)

Cullen et al. (1995)

Figure 3 Skin lesions (hyperkeratosis) at various stages due to arsenic poisoning.

were also found to be the common effects of As poisoning in humans resulting from prolonged oral exposure at doses of 0.05 mg As kg1 day1 or more (Armstrong et al., 1984; Mazumder et al., 1988; Saha et al., 2003).

38

S. MAHIMAIRAJA ET AL.

Studies have also revealed hepatic effects of As poisoning (USDHHS, 2000), as indicated by swollen and tender liver with elevated levels of hepatic enzymes in blood (Armstrong et al., 1984).

VI. RISK MANAGEMENT OF ARSENIC IN CONTAMINATED ENVIRONMENTS Risk management of contaminated sites includes source reduction, site remediation, and environmental protection. Selection of optimal risk management strategies requires consideration of core objectives such as technical practicability, feasibility, and cost effectiveness of the strategy and wider environmental, social, and economic impacts. Arriving at an optimal risk management solution for a specific contaminated site involves three main phases of the decision-making process. These include problem identification, development of problem solving alternatives (i.e., remediation technologies), and management of the site. The next section discusses the various remediation technologies considered suitable for managing As-contaminated soil and aquatic environments.

A. REMEDIATION

OF

ARSENIC-CONTAMINATED SOIL

Remediation of As-contaminated soil involves physical, chemical, and biological approaches that may achieve either the partial/complete removal of As from soil or the reduction of its bioavailability in order to minimize toxicity (Fig. 4). A large variety of methods have been developed to remediate metal(loid)s-contaminated sites. These methods can also be applicable for the remediation of As-contaminated soils. The selection and adoption of these technologies depend on the extent and nature of As contamination, type of soil, characteristics of the contaminated site, cost of operation, availability of materials, and relevant regulations.

1.

Physical Remediation

Major physical in situ treatment technologies to remediate metal(loid)contaminated sites include capping, soil mixing, soil washing, and solidification. The simplest technique for reducing the toxic concentration of As in soils is mixing the contaminated soil with uncontaminated soil. This results in the dilution of As to acceptable levels. This can be achieved by importing clean soil and mixing it with As-contaminated soil or redistributing clean

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

39

Figure 4 Viable remediation technologies for arsenic-contaminated soil/sediment and aquatic ecosystems.

materials already available in the contaminated site. Another dilution technique, especially in cultivated soils, relies on deep ploughing, during which the vertical mixing of the contaminated surface soil with less contaminated subsoil reduces the surface contamination, thereby minimizing the potential for As uptake by plants and ingestion of As by grazing animals. However, in this method the total concentration of As in soil will remain the same. Soil washing or extraction has also been used widely for the remediation of metal(loid)-contaminated soils in Europe (Tuin and Tels, 1991) and this method may be applicable for As-contaminated soils to some extent. Tokunaga and Hakuta (2002) evaluated an acid-washing process to extract the bulk of As(V) from a highly contaminated (2830 mg As kg1 soil) Kuroboku soil (Andosol) so as to minimize the risk of As to human health and the environment. The contaminated soil was washed with different concentrations of hydrogen fluoride, phosphoric acid, sulfuric acid, hydrogen chloride, nitric acid, perchloric acid, hydrogen bromide, acetic acid,

40

S. MAHIMAIRAJA ET AL.

hydrogen peroxide, 3:1 hydrogen chloride–nitric acid, or 2:1 nitric acid– perchloric acid. Phosphoric acid proved to be most promising as an extractant, attaining 99.9% As extraction at 9.4% acid concentration. Sulfuric acid also attained a high percentage extraction. The acid-washed soil was further stabilized by the addition of lanthanum (La), cerium (Ce), and Fe(III) salts or their oxides/hydroxides, which form an insoluble complex with dissolved As. Both salts and oxides of La and Ce were effective in immobilizing As in the soil attaining less than 0.01 mg liter1 As in the leachate. The success of soil washing largely depends on speciation of As present in the contaminated soils, as it is based on the desorption or dissolution of As from the soil inorganic and organic matrix during washing with acids and chelating agents. Although soil washing is suitable for off-site treatment of soil, it can also be used for on-site remediation using mobile equipment. However, the high cost of chelating agents and choice of extractant may restrict their usage to only small-scale operations. Arsenic-contaminated soil may be bound into a solid mass by using materials such as cement, gypsum, or asphalt. However, there are issues associated with the long-term stability of the solidified material. Capping the contaminated sites with clean soil is used to isolate contaminated sites as it is less expensive than other remedial options (Kookana and Naidu, 2000). Such covers should obviously prevent upward migration of contaminants through the capillary movement of soil water. The depth of such cover or “cap” required for contaminated sites should be assessed carefully. Using a simulated experiment, Kookana and Naidu (2000) demonstrated that when the water table is deeper than 2 m from the surface of cap, the upward migration of As through the cap is likely to be less than 0.5 m in 5 years. Where the water table is shallow enough to supply water to the surface (i.e., 1.5 to 2 m in most soils), dissolved As could take <10 years to reach the surface. They have also indicated that when the cap is of a different soil type than the underlying contaminated soil, a coarse-textured cap is very effective in reducing the capillary rise and therefore the cap should always be designed to include a coarser layer to break the capillary continuity.

2.

Chemical Remediation

Remediation, based on chemical reactions, is becoming increasingly popular largely because of a high rate of success. A number of methods have been developed mainly involving adsorption, immobilization, precipitation, and complexation reactions [Eqs. (27–37) in Table VI]. However, such methods are often expensive for the remediation of large areas. Two approaches are often used in the chemical remediation of metal(loid)contaminated soils: (i) immobilization of metal(loid)s using inorganic and

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

41

organic soil amendments in order to reduce their bioavailability and (ii) mobilization of metal(loid)s and their subsequent removal through plant uptake (phytoremediation) or soil washing. This section discusses the immobilization techniques used for the remediation of As-contaminated soil. The second approach is discussed in Section VI.A.3. Chemical immobilization is achieved mainly through adsorption/precipitation of As in contaminated sites through the addition of soil amendments. The mobilization of metal(loid)s in soils for plant uptake and leaching to groundwater can be minimized by reducing their bioavailability through chemical and biological immobilization (Bolan et al., 2004). There has been interest in the immobilization of metal(loid)s using a range of inorganic compounds such as lime, P fertilizers (e.g., phosphate rocks) and alkaline waste materials, and organic compounds such as biosolids (Basta et al., 2001; Knox et al., 2000). Depending on the source, the application of P compounds can cause direct adsorption of As onto these materials, promote As complex formation, or induce desorption of As through competition. This method is considered more economical and less disruptive than the conventional remediation option of soil removal (Bolan et al., 2003). Immobilization of As may be achieved by (i) changing the physical properties of the soil so that As is more tightly bound and therefore becomes less bioavailable; (ii) chemically immobilizing As either by sorption onto a mineral surface or by precipitation as a discrete insoluble compound; and/ or (iii) mixing the contaminated soil with uncontaminated soil, thereby increasing the number of As-binding sites (Naidu et al., 2003). A number of organic and inorganic amendments are known to immobilize a range of metal(loid)s including As by chemical adsorption. These include ion-exchange resin, ferrous sulfate, silica gel, gypsum, clay minerals such as bentonite, kaolin, and zeolite, green sand, and liming materials. These materials are naturally occurring and nontoxic with a large specific surface area and a significant amount of surface charge. The use of naturally occurring clay minerals such as zeolite as adsorbents is a novel method for the remediation of metal(loid)-contaminated soils (Minato et al., 2000). The advantages of zeolite application are its high efficiency for retention of metal(loid)s in soils, low cost, and easy application. Naidu et al. (2000) examined the potential for using strongly weathered oxidic soils as reactive barriers and found a strong affinity for As as it retains almost 5000 mg As kg1. Boisson et al. (1999) assessed the effectiveness of soil additives in reducing contaminant mobility. Their results indicated that the lowest amount of As was extracted when the soil was amended with beringite, steel shots, and their combination. Although the addition of hydroxyapatite decreased the mobility of metals such as Cd and Pb, it increased the mobility of As mainly due to H2PO4–AsO4 competition for the sorption sites. Therefore, the use

42

S. MAHIMAIRAJA ET AL.

of hydroxyapatite at multimetal(loid)-contaminated sites requires careful attention. Liming is increasingly being used as an important soil management practice in reducing the toxicity of certain metal(loid)s in soils. In addition to the traditional agricultural lime, a large number of studies have examined the potential value of other liming materials as immobilizing agents in reducing the bioavailability of a range of metal(loid)s in soils (Bolan et al., 2003). However, the effect of liming soils on As mobility has been rather inconsistent. Lime addition to As-contaminated soil induces the formation of CaH(AsO4)2 [Eq. (35) in Table VI], thereby reducing the soluble As in the soil solution for plant uptake and leaching. However, the solubility product of this compound is greater than that for Fe and Al arsenates, which are readily formed in most soils. For this reason, liming is not practiced widely to overcome As toxicity in soils (Jones et al., 1997), although liming has been reported to increase the immobilization of As (Bothe and Brown, 1999) and to decrease the plant uptake of As (Jiang and Singh, 1994; Tyler and Olsson, 2001). Naidu et al. (2003) evaluated the potential value of the chemical immobilization technique in the remediation of an As-contaminated site under field conditions in Australia. The site was a former railway depot that had previously been shown to be extensively contaminated with As. The As levels in the soil exceeded both ecological (20 mg kg1) and health investigation levels (100 mg kg1) and was appreciably water soluble, indicating that large amounts of As were potentially mobile at this site. The historical source of the contamination appears to be the ubiquitous use of As-based herbicides. Exposure pathway analyses showed that the highly mobile As posed a risk to both the groundwater and the residents living in the area. The contaminated site was identified for industrial development with Australian industrial guidelines for As set at 500 mg kg1 soil. Options for managing contaminated soil included in situ cleanup, excavation, and transport to landfill sites or application of risk-based land management strategy. Both in situ cleanup and excavation and transport to landfill were found to be prohibitively expensive and ranged from
$500,000 to $1,000,000. A risk reduction strategy was adopted with the aim to reduce the mobility of As through chemical immobilization. Ferrous salt was used to generate in situ mineral phases to immobilize As [Eq. (38)]. This reaction requires oxygen to be available to the soil and also generates considerable amounts of acid, which may be counterproductive to As immobilization in poorly buffered soils. The increased acidity could be neutralized by the amendment with lime [Eq. (39)]. The redox conditions of the soil also influence the speciation of As, and an example of two possible redox couples is given later [Eqs. (40) and (41)]. Following initial detailed laboratory studies, a mixture of Fe/Mn/gypsum was used as the stabilizing chemical. As shown in

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

43

Fig. 5, application of the mixed chemical led to a significant decline in mobile As. Subsequent studies involving aging of the treated soil showed complete elimination of risk posed by As. The total cost using this strategy was < $100,000, thus providing significant savings to the client. þ 4FeSO4 þ O2ðgÞ þ 6H2 O ! 4FeOOHðsÞ þ 4SO2 4 þ 8H

1 2FeSO4 þ O2ðgÞ þ 2CaCO3 þ 5H2 O ! 2

ð38Þ

2FeOOHðsÞ þ2CaSO4 2H2 O þ 2CO2ðgÞ ð39Þ

þ

AsO3 3

! 2Fe2þ þ AsO3 4 þ 2H2 O

þ

AsO3 3

! Mn2þ þ AsO3 4 þ H2 O Eo ¼ 0:67 V

Fe2 O3ðsÞ þ 4H þ MnO2ðsÞ þ 2H þ

Eo ¼ 0:21 V

ð40Þ ð41Þ

Results of a field experiment conducted by Xie and Huang (1998) on an As-polluted soil (Typentiaqualf ) in China have shown that the application of Fe (as FeCl3 at 25 mg Fe kg1 soil) or Mn (as MnO2 at 25 mg Mn kg1 soil) markedly lowered the total water- soluble As [As(III) þ As(V)] (24–26%) and As(III) (17–82%) in the soil and made the rice plants grow better than the control treatment, resulting in a higher rice grain yield and lesser As content in rice husk. This was attributed to the oxidation of As(III) to As(V) by MnO2 and the subsequent strong adsorption of As(V) by Fe and Mn oxides.

Figure 5 Variation of water-extractable As (1:5) for a subsurface-contaminated soil with soil treatment and incubation temperature. Treatments were (0) control soil; (A) Fe; (B) Fe þ lime; (C) Fe þ Mn; and (D) Fe þ Mn þ Al (Naidu et al., 2003).

44

S. MAHIMAIRAJA ET AL.

3.

Biological Remediation

a. Bioremediation. Bioremediation of soils contaminated with organic compounds such as pesticides and hydrocarbons is widely accepted in which native or introduced microorganisms and/or biological materials, such as compost, animal manures, and plant residues, are used to detoxify or transform contaminants. There has been increasing interest in the application of this technology for the remediation of metal(loid)-contaminated soils, especially for those metal(loid)s that undergo biological transformation. Although it has several limitations, this technology holds continuing interest because of its cost effectiveness. The unique aspect in bioremediation is that it relies mainly on natural processes and does not necessarily require the addition of chemical amendments other than microbial cultures and biological wastes. Because As undergoes biological transformation in soil, appropriate microorganisms may be used for the remediation of Ascontaminated soils. Existing and developing in situ bioremediation technologies may be grouped into the following two broad categories (NRC, 1997). i. Intrinsic bioremediation is where the essential materials required to sustain microbial activity exist in sufficient concentrations that naturally occurring microbial communities are able to degrade the target contaminants without the need for human intervention. This technique is better suited for remediation of soils with low levels of As over an extensive area. ii. Engineered bioremediation relies on various approaches to accelerate in situ microbial degradation rates. This is accomplished by optimizing the environmental conditions by adding nutrients and/or an electron donor/acceptor, thus promoting the proliferation and activity of existing microbial consortia. It is favored for highly contaminated localized sites. Three approaches could be used in the bioremediation of As-contaminated soils: (i) As could be immobilized into microbial cells through biosorption (bioaccumulation), (ii) toxic As(III) could be oxidized to less toxic As(V), and (iii) As compounds could be removed from the soil by volatilization. i. Bioaccumulation: Microorganisms exhibit a strong ability to accumulate (bioaccumulation) As from a substrate containing very low concentrations of this element. Bioaccumulation is activated by two processes, namely biosorption of As by microbial biomass and its byproducts and physiological uptake of As by microorganisms through metabolically active and passive processes. Factors such as soil pH, moisture and aeration, temperature, concentration and speciation of As, soil amendments, and rhizosphere are known to influence the process of bioaccumulation of As in microbial cells. While a number of bacterial and

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

45

fungal species have been known to bioaccumulate As, some algal species (Fucus gardneri and Chlorella vulgaris) are also known to accumulate As (Granchinho et al., 2001; Maeda et al., 1985). This technique has often been used successfully to remove metal(loid) ions from the aquatic environment and is therefore discussed further in Section VI.B.2. ii. Microbial redox reactions: Heterotrophic bacteria have been found to oxidize toxic As(III) in soils and sediments to less toxic As(V) and thus could play an important role in the remediation of contaminated environment (Wakao et al., 1988). Because As(V) is strongly adsorbed onto inorganic soil components, microbial oxidation could result in the immobilization of As. Strains of Bacillus and Pseudomonas spp. (Frankenberger and Losi, 1995) and Alcaligenes faecalis (Phillips and Taylor, 1976) and Alcaligenes spp. (Osborne and Ehrlich, 1976) were found capable of oxidizing As(III) to As(V). A dissimilatory metal(loid) reduction has the potential to be a helpful mechanism for both intrinsic and engineered bioremediation of contaminated environments. Arsenic can be reduced to Aso, which is subsequently precipitated as a result of microbial sulfate reduction. Desulfototomaculum auripigmentum, which reduces both As(V) to As(III) and SO2 4 to H2S leads to As2S3 precipitation (Newman et al., 1997). Because arsenite is more soluble than As(V), the latter can be reduced to As(III) using bacteria in soil and subsequently leached. iii. Methylation of As: A variety of microbes could transform inorganic As into its metallic hydride or methylated forms. Due to their low boiling point and/or high vapor pressure, these compounds are susceptible for volatilization and could easily be lost to the atmosphere (Braman and Foreback, 1973). Methylation is considered a major biological transformation through which As is volatilized and lost. As discussed earlier, biomethylation of As in soils and aquatic systems is well documented, as it is important in controlling the mobilization and subsequent distribution of arsenicals in the environment (Frankenberger and Losi, 1995; Gao and Burae, 1997; McBride and Wolfe, 1971; Tamaki and Frankenberger, 1992). Methanogenic bacteria, commonly present in sewage sludge, freshwater sediments, and composts, are capable of methylating inorganic As to volatile DMA. Arsenate, As(III), and MAA can serve as substrates in DMA formation. Inorganic As methylation is coupled to the CH4 biosynthetic pathway and may be a widely occurring mechanism for As removal and detoxification (Frankenberger and Losi, 1995). In addition to bacteria, certain soil fungi also are able to volatilize As as methylarsine compounds, which are derived from inorganic and organic As species.

46

S. MAHIMAIRAJA ET AL.

Woolson (1977) demonstrated the release of alkylarsines in a number of soils. Dimethylarsine and trimethylarsine are produced when soils were amended with inorganic and methylated arsenic herbicides. The organisms responsible for volatilization of As originate from diverse environments, suggesting that a number of species have the capacity to produce alkylarsines (Frankenberger and Losi, 1995; Woolson, 1977). Some examples of the organisms involved in the biomethylation of As are given in Table IX. In most cases, these organisms were tested in laboratory conditions; however, their performance should be assessed under field conditions in contaminated sites. b. Phytoremediation. Phytoremediation is considered a subset of bioremediation that employs plants and their associated root-bound microbial community to remove, contain, degrade, or render environmental contaminants harmless (Raskin et al., 1997; Robinson et al., 2003b). This terminology applies to all plant-influenced biological, chemical, and physical processes that aid in the remediation of contaminated medium (Cunningham and Lee, 1995). It involves soil–plant systems in which metal(loid)s-accumulating plants are grown in contaminated sites. It is considered an economically feasible and environmentally viable technology for remediating metal(loid)-contaminated systems. The effectiveness of this technology is, however, variable and highly site dependent. In phytoremediation, plants are exploited as a biopump that use the energy of the sun to remove water and contaminants from the soil to the aboveground portion and return some of the products of photosynthesis back into the root zone in the form of root exudates involved in the (im) mobilization of contaminants. Transpiration is the driving force for phytoremediation. By removing water from the medium, plants help reduce erosion, runoff, and leaching, thereby limiting the movement of contaminants off-site. Some contaminants are taken up in the transpiration stream, where they may be metabolized, and may be eventually volatilized. By removing excess water from the soil profile, plant roots may also create an aerobic environment where metal(loid) mobility is reduced and biological activity is enhanced. Plants stimulate microbiological activity in the root zone by providing a carbon source from root exudates and decaying root materials (Robinson et al., 2003b). Phytoremediation technologies have been grouped into various categories that include phytostabilization, rhizofiltration, and phytoextraction (Cunningham et al., 1995). In phytostabilization, transpiration and root growth are used to immobilize contaminants, including As by reducing leaching, controlling erosion, creating an aerobic environment in the root zone, and adding organic matter to the substrate that binds As. It involves the establishment of metal(loid)-tolerant vegetation on the contaminated site

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT Table IX Microorganisms Proven Capable of Biomethylating Arsenic Compounds in Soil and Aquatic Environments Organisms

Mechanism

Scopulariopsis koningii Methylate As to Fomitopsis pinicola trimethylarsenic(V) Penicillium gladioli species, precursors to volatile trimethylarsine Fusarium oxysporum Accumulates As(V) meloni and converts to dimethylarsine Fucus gardneri Methylates As(V) to dimethylarsine Closterium aciculare Methylates As(V) to methylarsenic(III) species S. brevicaule Transforms As(V) to (CH3)3As species Chlorella vulgaris Biosorption and accumulation of As and converting into compound of (CH3)2AsO(OH) Polyphysa peniculus Methylates As(V) to dimethylarsine Penicillium sp. At pH 5 to 6 methylates CH3AsO(OH)2 and (CH3)2AsO(OH) to (CH3)3As. Aeromonas sp. Methylates (CH3)2AsO(OH) to (CH3)3AsO 3 Alcaligenes sp. Methylates AsO 2 or AsO4 Pseudomonas sp. into AsH3 under aerobic condition Flavobacterium sp. Methylates (CH3)2AsO(OH) to (CH3)3AsO Candida humicola Methylates As(V) into a volatile As species Methanobacteriaum Methylates As(V), As(III) and CH3AsO(OH)2 to (CH3)2AsH under anaerobic condition C. humicola Methylates CH3AsO(OH)2 and (CH3)2AsO(OH) acid to (CH3)3As. Gliocladium roseum 3 [C. humicola uses AsO Penicillium sp. 2 and AsO4 as substrates to produce (CH3)3As]

Reference Lehr et al. (2003)

Granchinho et al. (2002)

Granchinho et al. (2001) Hasegawa et al. (2001) Andrewes et al. (2000) Kaise et al. (1997)

Cullen et al. (1994) Huysmans and Frankenberger (1991) Baker et al. (1983) Cheng and Focht (1979) Chau and Wong (1978) Cullen et al. (1984) McBride and Wolfe (1971)

Cox and Alexander (1973)

47

48

S. MAHIMAIRAJA ET AL.

that is left in perpetuity. The stabilization of As in the root zone could be achieved through the addition of organic matter as well as soil amendments. In rhizofiltration, the roots can be used to adsorb or absorb metal (loid)s, which are subsequently removed by harvesting the whole plant. In this case, metal(loid) tolerance and translocation of the metal(loid)s to aerial parts are largely irrelevant. In phytoextraction, plants can be grown on contaminated soil and the aerial parts [and the metal(loid)s they contain] harvested. In this case, plants need to be tolerant only if the soil metal(loid) content is very high, but they need to accumulate very high concentrations in their aerial parts. Phytoextraction involves repeated cropping of plants until the metal(loid) concentration in the soil has reached the acceptable (targeted) level. Certain plants, termed “hyperaccumulators” (Brooks et al., 1977), accumulate an inordinate concentration of metal(loid)s in their aboveground biomass. These plants may even accumulate metal(loid)s that are nonessential and often toxic to plants. The minimum concentration of As required for a plant to be classified as a hyperaccumulator of As was set at 1000 mg kg1 (0.1%) on a dry weight basis (Ma et al., 2001). The hyperaccumulation of metal(loid)s involves uptake of the soluble metal(loid) species by the root system, translocation to the aerial parts, and storage in a nontoxic form in the aerial portions. Chaney et al. (1997) suggested that this process necessarily requires tolerance to high concentrations of metal (loid)s. Using a combination of techniques, including X-ray absorption spectroscopy, Pickering et al. (2000) studied the biological mechanisms involved in the accumulation of As in Indian mustard (Brassica juncea) and established the biochemical fate of As taken up by this plant. Arsenic was taken up by roots as oxyanions [As(V) and As(III)], possibly via the H2PO 4 transport mechanism, and a small fraction was exported to the shoot via xylem. Once in the shoot, the As is stored as an As-III-tris-thiolate complex. The majority of the As remains in the roots as an As-III-tris-thiolate complex, which is indistinguishable from that found in the shoots and from As-III-trisglutathione. The thiolate donors are thus probably either glutathione or phytochelatins. Addition of the dithiol arsenic chelator dimercaptosuccinate to the hydroponic culture medium caused a fivefold increase in the As level in the leaves, although the total As accumulation was increased only marginally. This indicates that the addition of dimercaptosuccinate to Ascontaminated soils is likely to facilitate As bioaccumulation in plant shoots, a prerequisite for efficient phytoremediation strategy. The high cost of this compound, however, would be an economic concern unless the plants would be able to synthesize it. At present there are about 400 species of known terrestrial plants that hyperaccumulate one or more of several metal(loid)s (Robinson et al.,

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

49

1995). However, until recently no As-hyperaccumulating plants were reported. Ma et al. (2001) discovered an As-hyperaccumulating plant, ladder brake (Pteris vittata L.), a terrestrial fern, which accumulates large amounts (23,000 mg kg1-dry weight basis) of As from soils. The unique property of As hyperaccumulation by the Chinese brake fern is of great significance in the phytoremediation of As-contaminated soils. Therefore, the potential of this fern for phytoremediation of As-contaminated soil was assessed by Tu et al. (2002) in a glasshouse experiment using soils from an abandoned wood preservation site. Results have shown that the Chinese brake accumulated huge amounts of As from soil and that its As concentration increased with the growth period. The As concentration in the fronds was 6000 mg kg1 dry mass after 8 weeks of transplanting and increased to 7230 mg kg1 after 20 weeks. The As concentration increased as fronds aged, with old fronds accumulating as much as 13,800 mg As kg1. Another silver fern [Pityrogramma calomelanos (L.) Link] has also been reported to hyperaccumulate As up to 8350 mg kg1 dry mass from soil containing 135 mg kg1 (Francesconi et al., 2002). It occurs in tropical and subtropical regions of the world and is widely distributed in Thailand where it favors open, high rainfall areas. Some of the studies involving phytoremediation of As in the soil are presented in Table X. Arsenic uptake by plants is associated with the H2PO 4 uptake mechanism, where presumably As(V) is taken up as a H2PO analogue (Pickering 4 et al., 2000). Therefore, there is a growing interest in using P fertilizer to enhance As uptake by plants. Tu and Ma (2003) suggested that phosphate application may be an important strategy for the efficient use of Chinese brake (Pteris vittata L.) to phytoremediate As-contaminated soils. The addition of P fertilizer to As-contaminated soil was found to increase As solubility and mobility and thus increase plant uptake of soil As (Creger and Peryea, 1994). Some selected references on the mobilization of As by phosphate compounds are reported in Table XI. In an hydroponic experiment, Wang et al. (2002) investigated the interactions of As(V) and H2PO 4 on the uptake and distribution of As and P, and As speciation in P. vittata. They found that the plants accumulated As in the fronds up to 27,000 mg kg 1 dry weight, and the frond As to root As concentration ratio varied between 1.3 and 6.7. Increasing the phosphate supply decreased the As uptake markedly, with the effect being greater on root As concentration than on shoot concentration. They concluded that As(V) is taken up by P. vittata via the H2PO 4 transporters, reduced to As (III), and sequestered in the fronds primarily as As(III). In a fly ashamended soil, Qafoku et al. (1999) observed that H2PO 4 displaced both As(III) and As(V), thereby increasing the mobility of As in soils. Thus, the H2PO 4 -induced plant uptake of As could be employed in the phytoremediation of As-contaminated sites.

50

S. MAHIMAIRAJA ET AL. Table X Selected References on Phytoremediation of Arsenic-Contaminated Soil

Plant used Chinese brake ferns (Pteris vittata)

White lupin (Lupinus albus)

Arabidopsis thaliana

Ladder brake (P. vittata L.) Silver fern (Pityrogramma calomelanos) Herb (Mimosa pudica)

Shrub (Melastoma malabrathriccum) Rice (Oryza sativa)

Result and remark As concentration in shoot as high as 20 times the soil As concentration under field condition. Increasing soil pH improved As uptake by plant Fern transfers As rapidly from soil to aboveground biomass with only minimal As in roots Hyperaccumulation of As enhanced by P addition Fronds accumulated as much as 13,800 mg As kg1 (
90% As transported to the fronds) As(V) uptake was high. Roots accumulated As under P deficiency. Potentially a good candidate due to rapid growth and adaptability to varying edaphic status Plants accumulated large amounts of As showing some tolerance Removal of
26% of soil As within 20 weeks after transplanting Accumulating in fronds up to 8350 mg kg1 Tolerated high soil As (
5200 mg As kg1), accumulating in leaves
77 mg As kg1 Tolerated high soil As (
5200 mg As kg1), accumulating in leaves up to 43 mg As kg1 Plants grown on As-treated soil had higher As uptake than plants grown on untreated soil; at concentrations >1500 mg As kg1 plants died

Reference Salido et al. (2003)

Zhang et al. (2002)

Chen et al. (2002) Tu et al. (2002)

Esteban et al. (2003)

Dhankher et al. (2002)

Tu and Ma (2002)

Francesconi et al. (2002)

Visoottiviseth et al. (2002)

Visoottiviseth et al. (2002)

Onken and Hossner (1995)

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

51

Table XI Selected References on the Mobilization of Arsenic by Phosphate Compounds Phosphate compound

Method of investigation

Proposed mechanism

Ca(H2PO4)2

Transport and leaching

Desorption

NaH2PO4

Competitive adsorption

NaH2PO4

Chemical fractionation; transport and leaching studies Chemical fractionation

NaH2PO4

Phytoavailability bioassay

NaH2PO4

Phytoavailability bioassay

NH4H2PO4 Ca(H2PO4)2

Adsorption and desorption

NH4H2PO4

Transport and leaching

Hydroxyapatite

Chemical fractionation

Competitive adsorption

Competitive adsorption Competitive adsorption

Competitive adsorption Competitive adsorption

Reference Qafoku et al. (1999) Creger and Peryea (1994) Reynolds et al. (1999) Woolson et al. (1973) Livesey and Huang (1981) Peryea (1991); Peryea and Kammereck (1997) Davenport and Peryea (1991) Boisson et al. (1999)

Davenport and Peryea (1991) observed that high rates of monoammonium phosphate (MAP) or monocalcium phosphate (MCP) fertilizers significantly increased the amount of As leached from the soil. Mixing high rates of MAP or MCP fertilizers with orchard soil, Peryea (1991) reported that As release from lead–arsenate-contaminated soil was positively related to the level of P input but was not significantly influenced by the P source. Arsenic solubility was regulated by specific H2PO 4 –AsO4 exchange, whereas H2PO solubility was controlled by the equilibria of metastable P miner4 als. Results indicate that the use of P fertilizers on such soils has the potential to greatly enhance the downward movement of As (Peryea and Kammereck, 1997). Thus the increased mobilization of As resulting from phosphate input can result in its increased leaching to groundwater, especially in the absence of active plant growth. Hence attempts to use plants to remove As from soils need to take the multiple effects of phosphate into consideration. Phytoremediation has several advantages over other remediation and metal(loid) extraction technologies. The cost involved in phytoremediation is much lower than other technologies, such as soil removal, capping, and ex situ cleansing. Other advantages include the ultimate fertility of the cleaned site, the high public appeal of “green” technology, and the possibility

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of producing secondary products that offset the cost of the operation or even produce a small profit. However, some of the basic plant physiological processes, such as low biomass production and shallow root growth, nonetheless limit the scope of phytoremediation. Only surface contamination can be removed or degraded and the cleanup is restricted to areas that are amenable to plant growth. Most importantly, it may take a long time for site remediation to be effective. Phytoremediation can only be used if it meets environmental regulation during the operation as well as its end point.

B. REMOVAL OF ARSENIC

FROM

AQUATIC ENVIRONMENTS

As discussed earlier, because most cases of As toxicity in humans have resulted from the consumption of As-contaminated water, there have been intensive research efforts in developing technologies aimed at stripping As from water. A plethora of methods suitable for the removal of As from water at both household and community levels are currently available. These methods are primarily based on (i) removal of solid-phase As through coagulation, sedimentation, or filtration; (ii) removal of solution-phase As through ion exchange, osmosis, or electrodialysis; (iii) oxidation of As(III) to As(V) and its subsequent removal through adsorption and/or precipitation; (iv) biosorption using microorganisms; and (v) rhizofiltration using aquatic plants. Some of the methods that have been tested for the removal of As from water are presented in Table XII.

1.

Physicochemial Methods

Filtration, adsorption, and chemical precipitation are the most common physicochemical methods used for stripping As from water. While the particulate As in water can be removed by simple filtration, the aqueous As can be removed through adsorption or precipitation followed by filtration. a. Filtration. Most of the domestic drinking water treatment systems for As removal involve filtration. For example, the “Pitcher filter” involving porous ceramics (Neku and Tandukar, 2003) and sand filters (Yokota et al., 2001) have been found to be effective in stripping As from water. Seidel et al. (2001) noticed that the porous nanofiltration anion-exchange membrane removed about 90% of As(V) present in water at a concentration of 316
g liter1. Although this technology could achieve a high degree of As removal, it involves a high initial investment and high operation and maintenance costs.

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT

53

Table XII Selected References on Methods of Arsenic Stripping from Water Method 3-Gagri (Pitcher) filter Aeration and sand filtration

Pond sand filter system Negatively charged porous nanofiltration (NF) membrane Using rare earth oxides

Iron oxide-coated sand (IOCS)

Coprecipitation with Fe

Porous NF membrane

Iron oxide-coated sand and ferrihydrite (IOCS and FH)

Iron-sulfide minerals (pyrite and pyrrhotite) Kimberlite tailing (mineral waste from diamond mining) Mesoporous anions traps (metal-chelated ligands immobilized on anionbinding silica material) Aquifer materials (composed of quartz, feldspar, calcite, chlorite, illite, and magnetite/hematite)

Remark

Reference

Removed 76–95% of As. Suitable for household use Removed 62–92% of As containing
240–320
g liter1 Removed >99 % of 5 mg As liter1 60–90% removal of As(V) from water containing
10–316
g liter1 Adsorbed As(V) rapidly and effectively; >90% of adsorption occurred within the first 10 min, adsorbed As (V) could be desorbed by washing with pH 12 solution Very effective in removing As (III) and As(V) from drinking water containing 200 to 1700
g liter1; about 94% removal efficiency Bench scale test showed
88% of As(III) in water removed by settlement over 24 h As removal by 60–90 % from drinking water containing As from 10 to 316
g liter1
90% removal of As from natural water containing 325
g liter1; adsorption of IOCS and FH estimated at 18.3 and 285
g g1, respectively Fe-sulfides are very effective in removing As [both As(III) and As(V)] from water Removed As at a rate of 270
g g1; more efficient at near neutral pH. 90–94% removal in 12 h Most As removed from water containing >120 mg liter1; adsorption at 120 mg g1

Neku and Tandukar (2003)

Removed As(III) from water through adsorption

Berg et al. (2001)

Yokota et al. (2001) Seidel et al. (2001)

Raichur and Panvekar (2002)

Yuan et al. (2002)

Mamtaz and Bache (2000)

Vrijenhoek and Waypa (2000) Thirunavkukkarasu et al. (2001)

Han and Fyfe (2000)

Dikshit et al. (2000)

Fryxell et al. (1999)

Carrillo and Drever (1998)

54

S. MAHIMAIRAJA ET AL.

k

k

k

k

b. Adsorption. A number of compounds, including activated alumina, Fe-coated sand, and ion-exchange resins are used to adsorb As. In most geologic environments, Fe2O3 carries a positive surface charge that preferentially adsorbs As. Similarly, Al(OH)3 and silicate clays also adsorb large amounts of As. Yoshida et al. (1976) investigated the removal of As from water using “brown gel,” which is a silica gel containing 6% of Fe(OH)3, and observed that the maximum adsorption (17 g As kg1) of both As(III) and As(V) occurred at pH 6. Rothbaum and Buisson (1977) found that synthetic Fe-floc [Fe(OH)3], prepared by treating FeSO4 with NaOCl at pH 3.5–5.0, removed a large percentage of As from geothermal discharge water through coprecipitation. Similarly, Yuan et al. (2002) examined the potential value of several Fetreated natural materials such as Fe-treated activated carbon, Fe-treated gel beads, and Fe oxide-coated sand in removing As from drinking water under both laboratory and field conditions. The Fe oxide-coated sand consistently achieved a high degree (>94%) of As(III) and As(V) removal. When the pH was increased from 5 to 9, As(V) adsorption decreased slightly, but As(III) adsorption remained relatively stable. Kimberlite tailings (Dikshit et al., 2000) and iron-sulfide minerals such as pyrite and pyrrhotite (Han and Fyfe, 2000) were also found to be very effective adsorbents in stripping both As(III) and As(V) from water. Hlavay and Polyak (1997) developed and tested novel adsorbents for As stripping. Porous support materials were granulated using Al2O3 and/or TiO2 and then Fe(OH)3 was freshly precipitated onto the surface of these particles. The resulting Fe(OH)3-impregnated porous adsorbent was dried at room temperature and packed into an ion-exchange column. These columns were found to remove >85% of As in water. The As(III) ions can primarily be adsorbed by chemical reaction on the surface of Fe(OH)3. The neutral functional group of { FeOH} reacts with H2AsO 3 ions, and surface compounds of { FeAsO3H2}, { FeAsO3H}, and { FeAsO2} can be formed. Das et al. (1995) demonstrated the practical application of the adsorption technique in stripping As by developing a simple household device to remove As from groundwater used for drinking and cooking purposes. The system consists of a filter, tablet, and two earthen or plastic jars. The tablet contains Fe(III) salt, an oxidizing agent, and activated charcoal. The filter is made of mainly purified fly ash with binder. When the tablet is added to water (one tablet for every 20 liters), the As(III) ions are catalytically oxidized to As(V) ions in the presence of Fe(III), which are subsequently adsorbed onto activated charcoal and hydrous ferric oxide (Fe2O3.2–3H2O). In addition to As(V), As(III) ions are also strongly adsorbed by Fe(III) oxides. The water is allowed to settle for about an hour and is then filtered. This stripping system has been installed in several locations in Bangladesh and

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West Bengal, and analytical results have shown that generally 93–100% of the total As in water (with an initial concentration of 149–463
g liter1) is removed. Khan et al. (2000) evaluated the efficiency of a simple three-pitcher filter system consisting of ceramic filters (locally known as 3-kalshi) in stripping As from groundwater. In the 3-kalshi assembly, the first kalshi (pot) contains Fe chips and coarse sand, the second contains wood charcoal and fine sand, and the third is the collector for the filtered water. Depending on the size of the filtering units, this system has been shown to be capable of reducing the As concentration in water from an initial level of 1100
g liter1 to below the detection limit of 2
g liter1 with a corresponding decrease in dissolved Fe concentration (from 6000 to 200
g liter1). Similarly, Kim et al. (2004) have shown that mesoporous alumina with a wide surface area (307 m2 g1), high pore volume (0.39 m3 g1), uniform pore size (3.5 nm), and interlinked pore system is efficient in stripping As from domestic water. The mesoporous alumina is insoluble and stable within the range of pH 3–7. The maximum As adsorption was seven times higher [121 mg As(V) g1 and 47 mg As(III) g1] than that of conventional activated alumina, and the kinetics of adsorption are also rapid with complete adsorption in less than 5 h as compared to conventional alumina (about 2 days to reach half of the initial concentration). Fryxell et al. (1999) used metal-chelated ligands immobilized on mesoporous silica as a novel anion-binding material to remove As from water. Nearly complete removal of As(V) has been achieved from solutions containing more than 100 mg As (V) liter1. c. Precipitation. Arsenate can be removed by precipitation/coprecipitation using Fe and Al compounds [Eqs. (27–33) in Table VI]. Gulledge and O’Connor (1973) achieved a complete removal of As(V) from water using Fe2(SO4)3 at a pH range of 5 to 7.5 [Eq. (34)]. Hydrolyzing metal salts such as FeCl3 and alum [Al2(SO4)3] have been shown to be effective in stripping As by coagulation. Hering et al. (1997) achieved >90% removal of As(V) from water containing an initial concentration of 100
g As liter1. Shen (1973) removed As from drinking water by dosing with chlorine (Cl2) and FeCl3. Oxidation of As(III) to As(V) by Cl2 and the subsequent removal by precipitation were considered the mechanisms involved in this process. Treating drinking water with Fenton’s reagent (ferrous ammonium sulfate and H2O2) followed by passing through elemental Fe, Krishna et al. (2001) achieved As removal below the USEPA maximum permissible limit of 50
g liter1 from an initial concentration of 2000
g liter1 of As(III). This method is simple and cost effective for use at community levels. Using a bench scale test, Mamtaz and Bache (2000) demonstrated that up to 88% of the As(III) in water could be removed by coprecipitation with naturally

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occurring Fe found in groundwater. One of the advantages in chemical precipitation method is that this can be used at both household and community levels. The materials are readily available and generally inexpensive. However, a problem of disposal of toxic sludge exists and it also requires trained operators.

2. Biological Methods a. Phytoremediation using Aquatic Plants. Phytoremediation of Ascontaminated waters may be readily achieved by the use of aquatic plants because unlike soil, most of the As in water is available for plant uptake. In the case of soils, the plant must first solubilize the metal(loid)s in the rhizosphere and then should have the ability to transport it to the aerial tissue (Brooks and Robinson, 1998). The use of freshwater vascular plants for the removal of metal(loid)s from water has been long established. There are two approaches in using these plants for the remediation of polluted water: The first involves monospecific pond cultures of free-floating plants such as water hyacinth. The plants accumulate the metal(loid)s until a steady state of equilibrium is achieved. They are then harvested by removal from the pond. The second approach involves growing rooted emergent species in trickling bed filters. Rhizosphere microbes usually facilitate the removal of metal(loid)s in these systems. Rhizofiltration usually involves the hydroponic culture of plants in a stationary or moving aqueous environment wherein the plant roots absorb metal(loid)s from the water (Brooks and Robinson, 1998). Ideal plants for rhizofiltration should have extensive root systems and be able to remove metal(loid)s over an extended period. Some of the aquatic plants capable of accumulating large amounts of As are presented in Table XIII. Robinson et al. (2004) undertook a field survey in which a number of terrestrial and aquatic plant samples were taken at several sites within the Taupo volcanic zone (TVZ) in New Zealand. The TVZ covers an area of 600,000 ha in the central North Island of New Zealand and the area is rich in geothermal activity. There have been previous reports of elevated As concentrations in some waterways and associated lands in the TVZ (Liddle, 1982). The known sources of As pollution in the TVZ include (i) As arising from naturally occurring geothermal activity; (ii) geothermal bores that release As-rich water into the aquatic biosphere; (iii) runoff of As-based pesticides; (iv) As from timber treatment sites such as the pulp and paper mill at Kinleith; and (v) As added to lakes to control weeds (e.g., NaAsO2 added to Lake Rotorua). The mean As concentrations in all the plants tested from the TVZ are given in Fig. 6. Data clearly display the difference of As accumulation

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Table XIII Selected Aquatic Plants for Potentially Stripping Arsenic from Water

Name of plant Agrostis capillaris Ceratophyllum demersum C. demersum C. demersum Egeria densa Lagarosiphon major Rorippa naturtium (subsp. Aquaticum) Cynodan dactylon Spergularia grandis Paspalum tuberosum Fern (Pteris vittata) Fern (P. vittata) Silver fern (Pityrogramma calomelanos) Fern (Pteris cretica) Fern (P. longifolia) Fern (P. umbrosa) Watercress (Lepidium sativum) Myriophyllum propinquum Elodea canadensis Agrostis sp a

Level of As accumulation (mg kg1)a

Reference

3470 650

Porter and Peterson (1975) Reay (1972)

265–1121 44–1160 94–1120 11–1200 >400

Liddle (1982) Robinson et al. (1995) Robinson et al. (1995) Robinson et al. (1995) Robinson et al. (1995)

1600 1175 1130 22,630 8960–27,000 8350

Jonnalagadda and Nenzou (1997) Bech et al. (1997) Bech et al. (1997) Ma et al. (2001) Wang et al. (2002) Visoottiviseth et al. (2002)

6200–7600

Zhao et al. (2002)

12–1766

Robinson et al. (2003a)

974–3900 1628–1857 800

Machetti (2003) Machetti (2003) Machetti (2003)

Dry weight basis.

between aquatic and terrestrial plants. Aquatic plants, grouped on the left-hand side of Fig. 6, had As concentrations up to 4000 mg kg1 on a dry matter basis. In contrast, terrestrial plants, on the right-hand side of Fig. 6, showed much lower As concentrations. All the aquatic plants tested accumulated As at concentrations greater than 5 mg kg1 on a dry matter basis, and none of the terrestrial plants tested had As concentrations surpassing 11 mg kg1. Most of the terrestrial plants tested were below the detection limit for As (0.5 mg kg1) even when growing in soil containing up to 89 mg As kg1. The difference in metal(loid) accumulation between aquatic and terrestrial plants was noticed by Outridge and Noller (1991) in their review of hyperaccumulation of elements by aquatic plants. Although they did not provide an explanation of this phenomenon, various reasons could be

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Figure 6 Mean arsenic concentration in plants collected from the Taupo volcanic zone (TVZ) (Robinson et al., 2004).

attributed for the difference in As accumulation between aquatic and terrestrial plants. For instance, in terrestrial systems, the solubilization of As in the rhizosphere is necessary to allow the plant roots to take up and transport this element to the aerial parts of the plant. This is not the case when the plant grows in an aqueous medium, where the metal(loid) is already present in a bioavailable form (Brooks and Robinson, 1998). b. Microbial Removal of Arsenic. Biosorption and biomethylation are the two important processes by which metal(loid)s, including As, are removed from water using microorganisms. The biosorptive process generally lacks specificity in metal(loid) binding and is sensitive to ambient environmental conditions, such as pH, solution composition, and the presence of chelators. Genetically engineered microorganisms (e.g., Escherichia coli) that express a metal(loid)-binding protein (i.e., metallothionein) and a metal(loid)-specific transport system have been found to be successful in their selectivity for accumulation of a specific metal (loid) in the presence of a high concentration of other metal(loid)s and chelating agents in solution (Chen and Wilson, 1997). These organisms also have potential application to remove specific metal(loid)s from contaminated soil and sediments.

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Biosorption is one of the promising technologies involved in removing As from water and wastewater. Several chemically modified sorbents have been examined for their efficiency in removing metalloids. Loukidou et al. (2003) examined the potential of Penicillum chrysogenum, a waste by-product from antibiotic production, for the removal of As(V) from wastewaters. They reported that the pretreatment of biomass with common surfactants (as hexadecyl-trimethylammonium bromide and dodecylamine) and a cationic polyelectrolyte was found to remove a significant amount of As(V) from waters. At pH 3, the removal capacities of modified biomass ranged from 33.3 to 56.1 mg As g1 biomass. Methylation is the most reliable biological process through which As can be removed from aquatic medium. Certain fungi, yeasts, and bacteria are known to methylate As to gaseous derivatives of arsine. Commercial application of biotransformation of metal(loid)s in relation to the remediation of metal(loid)-contaminated water was documented by Bender et al. (1995). They examined the removal and transformation of metal(loid)s using microbial mats, which were constructed by combining cyanobacteria with a sediment inoculum from a contaminated site. When water containing high concentrations of metal(loid)s was passed through the microbial mat, there was a rapid removal of the metal(loid)s from the water. The mat was found to be tolerant of high concentrations of toxic metal(loid)s such as Cd, Pb, Cr, Se, and As (up to 350 mg liter1). Management of toxic metal(loid)s by the mat was attributed to the deposition of metal(loid) compounds outside the cell surfaces, as well as chemical modification of the aqueous environment surrounding the mat. Large quantities of metal(loid)-binding polysaccharides were produced by the cyanobacterial component of the mat. Photosynthetic oxygen production at the surface and heterotrophic consumption in the deeper regions resulted in steep gradients of redox condition in the mat. Additionally, sulfur-reducing bacteria colonized the lower strata, removing and utilizing the metal(loid) sulfide. Thus, depending on the biochemical characteristics of the microzone of the mat, the sequestered metal(loid)s could be oxidized, reduced, and precipitated as sulfides or oxides.

C.

MULTISCALAR-INTEGRATED RISK MANAGEMENT

A number of challenging issues need to be taken into consideration when devising strategies to manage As contamination of the environment. These include the following. i. Complexity of As contamination—the severity and long-term persistence of As contamination are influenced by factors such as medium characteristics, site hydrogeology, land and water use, source term, chemical form and speciation, and target organism.

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ii. Presence of multichemical species—As undergoes several biogeochemical transformation processes, resulting in the release of an array of chemical species that differ in their biogeochemical reactions, bioavailability, and biotoxicity. iii. Extent and magnitude of As contamination of groundwater resource— for example, in Bangladesh, As in groundwater is derived from geological weathering of parent rock materials from the Indo-Gangetic alluvial plains spread over an area of millions of hectares iv. Multipurpose end use of contaminated resources—water is used for drinking, cooking, and other household purposes and for irrigation; similarly, soil is used for agricultural production and recreational activities. It is therefore important to formulate and/or devise integrated risk management strategies involving source avoidance, source reduction, and remediation. Source avoidance, which refers to avoiding the most contaminated source of the groundwater relative to certain geological strata, can be practiced to minimize the risk resulting from As contamination of soil and water resources. For example, in Bangladesh, shallow dug wells are increasingly becoming popular as an alternative to pump water from deeper strata. In some cases, the relatively contaminant-free strata are below 250-m deep zones. However, sanitation of these shallow wells is paramount to avoid gastroenteritis and other pathogenic-borne diseases. Another strategy is source reduction, which refers to removing or stopping the source of contamination. Source reduction can be achieved easily when the contamination source is of anthropogenic origin, such as those in landfills or similar point sources. As discussed earlier, in most regions, As contamination of groundwater is largely of geogenic origin, and source reduction may not be a feasible option to manage As contamination. Remediation of contaminated soil and water resources requires both short-term and long-term solutions to the As problem. Therefore, the remediation strategies should be aimed at multiscalar levels, i.e., household level to community and regional levels, representing the various levels of complexicity. Depending on the efficiency and cost effectiveness of the system, a combination of technologies may be required at certain levels. The potential technologies for remediation of As-contaminated soil and water resources at different scales in relation to the end use of the resources are depicted in Fig. 7. For example, at the least complex household level, remediation strategies involving only a simple filter (sorptive) system can be used to remove As (i.e., As stripping) from water used for drinking and cooking purposes, whereas at a more complex community level, more sophisticated precipitation technologies should be used to strip As from the community water supply so that cost can be shared and the system can be managed

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Figure 7 Multiscalar risk management for arsenic-contaminated soil and aquatic ecosystems.

efficiently. More sophisticated stripping methods, which may require a series of a filtering–sorptive (precipitation) setup, are necessary in order to cope with the enormous volume of groundwater that needs to be treated before distribution to the community. Even at the community scale, the situation becomes even more complex when dealing with impacted soils, especially those geared for food production. In this case, land use is a very important factor to address. For example, in parks, applying soil amendments such as those high in Fe2O3 may suffice to mitigate As risk. In contrast, technologies might be paired in a situation when the food chain might be compromised, as typified by rangeland, rice paddy, and so on. A viable approach in this circumstance is to apply phytoremediation during the initial period (1 to 2 years) to strip the “bioavailable” fraction, subsequently followed by soil amendments before committing to the intended land use. It is very important to observe that as the level of contamination becomes more complex, a monitoring scheme should be in place. Hence, a successful remediation scheme for an As-contaminated environment should aim for an integrated approach involving the possible combination of physical, chemical, and/or biological mechanisms. It is essential that the integration of remediation technologies should enhance efficiency, both technologically and economically, resulting in a

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Figure 8 Conceptual integrated approach for remediation of arsenic-contaminated soil and aquatic ecosystems, focusing on phytoremediation.

reduction in the time required for achieving targeted levels of As. For example, phytoremediation is a promising new technology, which is relatively inexpensive and has been proven effective in the large–scale remediation of both soil and water resources. Further, it would also add “green” value (aesthetic) to the environment. Integrating physical, chemical, and/or bioremedial measures with phytoremediation as depicted in Fig. 8 could enhance a higher uptake of As by plants, can more effectively minimize biotoxicity through microbial and chemical immobilization, and can potentially eliminate As through the inducement of biomethylation and subsequent volatilization from the system.

VII. SUMMARY AND FUTURE RESEARCH NEEDS Arsenic is an extremely toxic and carcinogenic metalloid contaminant that adversely affects the environment and human health. Widespread As contamination of terrestrial and aquatic environments from both geogenic

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and anthropogenic sources has been reported in many countries. Although not anthropogenic, drinking of As-contaminated water has already affected millions of people, particularly in developing countries with the biggest known As calamity occurring in Bangladesh and West Bengal in India. Arsenic in soil and water exists in a different valence state, but predominantly as toxic As(III) and less toxic As(V). The biogeochemistry of As in soil and water is complex and is mostly determined by its chemical speciation resulting from chemical and biological transformations. The chemistry of soil and water (i.e., pH and Eh) and predominantly microbial assemblages play a major role in As dynamics. Although bioaccumulation of As in plants and organisms has been reported, its biochemical transformations within the plant and other biota are still largely unknown. Risk management of As-contaminated soil and aquatic ecosystems is an important issue and a great challenge; its success is necessary to promote sustainable environmental health and also to minimize the adverse impact on humans. A number of physical, chemical, and biological technologies involving simple filtration, precipitation, biosorption, and rhizofiltration have been developed to remediate As-contaminated soil and water. Conventional physical and chemical remedial measures usually are quite expensive but may prove highly effective. However, most of these technologies have been tested only at the laboratory and pilot scale levels. Large-scale application of such technologies requires trained personnel for the operation of equipment to treat soils and waters. However, phytoremediation, which is relatively inexpensive, has been proven effective in the remediation of metal (loid)-contaminated sites. Certain As-hyperaccumulating plants offer a wide scope for the phytoremediation of As-contaminated soil and water. Nonedible crops, such as ornamental and fuel crops, may be suitable for phytoremediation through which the entry of As into the food chain could largely be avoided. Bioremediation, using biological wastes and/or microbial strains, offers another avenue for remediation. However, as in the case of physical and chemical technologies, most of the research involving bioremediation has been demonstrated in the laboratory only. As such, its feasibility should be tested under diverse field conditions. Remediation of As-contaminated soils and As stripping from potable and irrigation waters require a multiscalar approach. This involves an “end-use” specific (i.e., drinking vs irrigation and agricultural vs recreational sites) integrated approach, involving a combination of physical, chemical, and biological technologies for the successful and effective management of Ascontaminated environments. Future research is, therefore, needed for the following: • Biogeochemical mechanisms governing As dynamics in different media using advanced spectroscopic-based techniques.

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• Elucidation of soil and water environmental factors (e.g., pH and Eh) that govern chemical and biological transformations of As. • Examination of solid-phase and solution-phase speciation of As in soil and water. • Identification of biochemical mechanisms involved in the accumulation of As in specific tissues or organs in plants, animals, and humans. This includes the interactive effects of As(V) and H2PO 4 on hyperaccumulators such as Chinese brake and water cress. • Evaluation of As phytotoxicity under field conditions. • Rhizosphere processes underpinning effective phytoremediation technologies. • Mycorrhizal role in the bioremediation of As regarding biomethylation, biooxidation, and immobilization of As. • Developing genetically engineered microorganisms and genetically modified plants to detoxify As in contaminated soil and water. • In situ immobilization techniques in contaminated soils/sediments using inexpensive industrial by-products high in metallic oxides; effect of aging on the release of As from the immobilized media. • Biomonitors of As as a tool in the risk assessment of As-contaminated sites. • Highly effective and expensive stripping methods for the removal of As in domestic water supplies destined for irrigation and human consumption.

ACKNOWLEDGMENTS The senior author thanks Massey University Research Foundation for the award of the Postdoctoral Fellowship. The U.S. Department of Energy Contract Number DE-FC-09-96SR18546 with the University of Georgia’s Savannah River Ecology Laboratory supported Drs. Bolan and Adriano’s writing/editing time.

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THE CONTRIBUTION OF BREEDING TO YIELD ADVANCES IN MAIZE (ZEA MAYS L.) Donald N. Duvick Iowa State University Ames, Iowa 50011

I. Introduction A. Maize Yield Trends During the Past Century B. Factors Responsible for Upward Yield Trends II. Genetic Gains in Grain Yield of Hybrids A. Previously Reported Genetic Yield Gains B. Recent Estimates of Genetic Yield Gains C. Estimates of the Contribution of Breeding to Total Yield Gains D. Changes that Have Accompanied Genetic Yield Gains in Hybrids III. Genetic Gains from Population Improvement A. Comparisons with Genetic Gains in Hybrids B. Relative Contributions of Population Improvement and Pedigree Breeding IV. Analysis and Conclusions A. Possible Reasons for Genetic Yield Gains B. Potential Helps or Hindrances to Future Gains in Yield C. Predictions References

Maize (Zea mays L.) yields have risen continually wherever hybrid maize has been adopted, starting in the U.S. corn belt in the early 1930s. Plant breeding and improved management practices have produced this gain jointly. On average, about 50% of the increase is due to management and 50% to breeding. The two tools interact so closely that neither of them could have produced such progress alone. However, genetic gains may have to bear a larger share of the load in future years. Hybrid traits have changed over the years. Trait changes that increase resistance to a wide variety of biotic and abiotic stresses (e.g., drought tolerance) are the most numerous, but morphological and physiological changes that promote efficiency in growth, development, and partitioning (e.g., smaller tassels) are also recorded. Some traits have not changed over the years because breeders have intended to hold them constant (e.g., grain maturity date in U.S. corn belt). In other instances, they have not changed, despite breeders’ intention to change them 83 Advances in Agronomy, Volume 86 Copyright 2005, Elsevier Inc. All rights reserved. 0065-2113/05 $35.00

84

DONALD N. DUVICK (e.g., harvest index). Although breeders have always selected for high yield, the need to select simultaneously for overall dependability has been a driving force in the selection of hybrids with increasingly greater stress tolerance over the years. Newer hybrids yield more than their predecessors in unfavorable as well as favorable growing conditions. Improvement in the ability of the maize plant to overcome both large and small stress bottlenecks, rather than improvement in primary productivity, has been the primary driving # 2005, Elsevier Inc. force of higher yielding ability of newer hybrid.

I. INTRODUCTION A. MAIZE YIELD TRENDS DURING

THE

PAST CENTURY

Maize yields began to rise markedly in many countries during the past century, first in the United States in the 1930s and then in other parts of the world in the 1950s and 1960s. For example: • U.S. yields, level at approximately 1.5 mg ha
1 in the first three decades of the 20th century, started to rise significantly in the 1930s, reaching 8.5 mg ha
1 by the end of the century (USDA-NASS, 2003b). The U.S. yield gains averaged 63 kg ha
1 year
1 from 1930–1960 and 110 kg ha
1 year
1 during the next 40 years (Troyer, 2000). • Maize yields in Canada tripled during the period 1940–2000, increasing from 2.5 to 7.5 mg ha
1, a linear increase of 80 kg ha
1 year
1 (Bruulsema et al., 2000). • Maize yields in Germany doubled in the period 1965–2000, going from 4 to 8 mg ha
1 (Frei, 2000). • Maize yields in France quadrupled in the period 1950–1984, increasing from 1.5 to 6.0 mg ha
1 (Derieux et al., 1987). • In Argentina, the national mean maize yield increased “at a rate of 2.3% per year from 1970–1992” (Eyhe´ rabide et al., 1994). Table I summarizes yield gain data for several regions of the world during the period 1961–2002. Globally, maize yields doubled during this time, from 1.9 to 4.3 mg ha
1, a linear increase of 61 kg ha
1 year
1. Different regions varied in the size of annual gain, as well as in average yields at the beginning and the end of the interval, but all showed positive and significant gains with the exception of eastern Europe (highly variable in the past decade) and southern Africa (minimal gain and highly variable during entire period). Yields in south Asia did not start to rise significantly until the 1980s; annual gains since 1985 have averaged 38 kg ha
1 year
1.

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85

Table I Maize Yield Trends in Selected Regions (1961–2002)a Region European Union (15) USA China Canada World South America Eastern Europe South Asia Southern Africa

1961 mean (mg ha
1)

2002 mean (mg ha
1)

Annual gainb (kg ha
1 year
1)

R2c

2.5 3.9 1.2 4.6 1.9 1.4 1.8 1.0 0.7

9.1 8.2 5.0 7.6 4.3 3.4 4.2 1.7 1.3

169 109 103 69 61 48 42 20 8

0.98 0.83 0.96 0.77 0.95 0.87 0.38 0.78 0.26

a

From FAO Statistical Databases (2004) http://apps.fao.org/default.htm. Linear regression coefficients, calculated from annual means, 1961–2002. c Coefficient of determination. b

These examples and other data show that maize yields have increased significantly in many regions of the world during the latter half of the 20th century, especially in those places where maize is grown as a commercial crop.

B. FACTORS RESPONSIBLE FOR UPWARD YIELD TRENDS 1.

Cultural Practices

Changes in cultural practices have been responsible for a significant portion of maize yield gains. Crop management practices, such as weed and pest control, timeliness of planting, and increased efficiency of harvest equipment, have improved over the years, especially (but not exclusively) in the industrialized countries (e.g., Cardwell, 1982; Edmeades and Tollenaar, 1990). Perhaps most importantly, the use of synthetic nitrogen fertilizers increased markedly starting in the years after World War II when plentiful and affordable supplies became available, first in the industrialized countries and then in many (but not all) of the developing countries (e.g., Cardwell, 1982; Edmeades and Tollenaar, 1990; Miquel, 2001). Total fertilizer applications on all crops worldwide increased fivefold during the period 1961–1992. The linear increase started from an average application of about 20 kg ha
1 in 1962 and reached 105 kg ha
1 in 1992 (USDA-ERS, 2003). However, in some countries, application amounts of synthetic nitrogen fertilizer did not fit this general trend; they began to level off in the 1980s. Application of

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commercial nitrogen fertilizer to maize plantings in the United States rose from an average of 58 kg ha
1 in 1964 to 157 kg ha
1 in 1985, but since then has stabilized at approximately 145–150 kg ha
1 (Daberkow et al., 2000; USDA-ERS, 2003). It would seem, therefore, that yield gains of U.S. maize since the mid-1980s cannot be attributed to application of increasing amounts of nitrogen fertilizer on maize plantings. Plant density—the number of maize plants per hectare—also increased steadily through the years following World War II in the United States as well as in other countries. The increase was more or less in step with increases in application amounts of fertilizer nitrogen. In the central U.S. corn belt, plant density averaged about 30,000 plants hectare
1 (or less) in the 1930s; it began to increase in the late 1940s and 1950s, reaching about 40,000 plants hectare
1 in the 1960s, 60,000 plants hectare
1 in the 1980s, and is often at 80,000 plants hectare
1 or higher at present (Duvick, 1977, 1984a, 1992; Duvick et al., 2004b; Paszkiewicz and Butzen, 2001; USDA, 1949–1992). During the past 50 years, plant density in the central U.S. corn belt has increased at an average rate of about 1000 plants hectare
1 year
1.

2.

Plant Breeding

a. Farmer Breeding. Genetic improvements, as well as cultural improvements, can contribute to an increased yield of maize. Farmer breeders, beginning with the people who first domesticated maize, have selected plants and cultivars to fit their wants and needs and, in so doing, have developed thousands of landraces adapted to a multitude of environments, as well as with a wide range of morphological and quality traits (e.g., Goodman and Brown, 1988; Grobman et al., 1961; Paterniani and Goodman, 1977). We can assume that a higher yield, or at least an acceptable and dependable level of yield, was always a desired trait for maize cultivars, as well as for those of other staple grain crops. Although long-term yield trends are not recorded for specific farmer breeding programs, a general observation indicates that when crop varieties are grown in a new environment (e.g., when migrants carry their favorite cultivars to a new land), the cultivars often do not perform as well as intended. Careful selection in the unadapted cultivars, often coupled with hybridization to cultivars from elsewhere, then is used to develop genetically different cultivars that are better adapted to the new environment and therefore yield more (and more dependably) than the first introductions. Examples in U.S. history are the 19th century development of hard red winter wheat (Triticum aestivum L.) cultivars for Kansas (Malin, 1944) and “Corn Belt Dent” maize open pollinated cultivars (OPCs) for U.S. corn belt states such as Illinois and Iowa (Wallace and Brown, 1988).

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Figure 1 United States maize yields, annual average, 1900–2003. From USDA-NASS (2003a).

Farmers developed adapted maize OPCs for the U.S. corn belt states in a relatively short time (Hallauer and Miranda, 1988; Wallace and Brown, 1988). Within a few decades after settlement of the region in the early years of the 19th century, maize yields and general performance of the new “Corn Belt Dent” cultivars were at acceptable levels in most parts of the region. However, from then on, gains in yield were small or nonexistent. This is evidenced by the lack of gain in U.S. maize yields during the first three decades of the 20th century (Fig. 1). One could suppose that the lack of yield gain during those decades was because maize-growing areas in the country changed in location and extent over time and therefore were not always equivalent in productivity. However, in the states of Iowa and Illinois, where maize-growing areas and cultural practices were relatively constant during this period, yields were essentially unchanged also. Yields in those states were level at approximately 2.3 mg ha
1 during the years 1900–1930 (USDA-NASS, 2003a). It would seem that farmer breeders in the corn belt, using selection techniques of that time [primarily mass selection based on individual plant performance (Sprague, 1952)], could not raise maize yields further than the levels attained in the initial development of adapted cultivars. New breeding methods were tried in the late 19th and early 20th centuries. The production of varietal hybrids (first generation crosses of two maize OPCs) was tried and abandoned because of unreliable results (e.g., Crabb, 1993; Richey, 1922). A few professional breeders in the public sector (USDA) worked on variety improvement in the 1920s using relatively

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unsophisticated methods of mass selection or ear-to-row breeding (Crow, 1998; Russell, 1991; Sprague, 1946, 1994). Their efforts did not increase yields either, except when a program provided adaptation to a new environment. These breeders, working in the first decades of the 20th century, lacked access to the present-day knowledge of experimental design, statistical analysis, and quantitative genetics. Lack of these tools must have hindered their progress. b. Hybrids. U.S. maize yields started to increase when maize hybrids made from crosses of inbred lines were introduced in the early 1930s. During the next few years the increase in maize yield was correlated with the increase in the proportion of maize area planted to hybrids (USDA, 1944 – 1962; USDA-NASS, 2003a). Yields in Iowa increased from 2 mg ha
1 to 3.5 mg ha
1 in the period 1933–1943, as the percentage of maize area planted to hybrids went from 0.7 to 99%. U.S. maize yields rose from 1.5 mg ha
1 in 1933 to 2.4 mg ha
1 in 1950, as the percentage of area planted to hybrids went from 0.1 to 78%. In either case, yield gains took place before a significant increase in use of synthetic nitrogen fertilizers or chemical control of weeds and insects (Cardwell, 1982; USDA, 1956), so it seems likely that the yield gains primarily were caused by genetic improvements; the new hybrids yielded more than the OPCs that they replaced, and successive hybrids yielded even more. Maize yields began to rise in conjunction with the introduction of hybrids in other countries as well (Cunha Fernandes and Franzon, 1997; Derieux et al., 1987; Eyhe´ rabide et al., 1994; Frei, 2000; Tollenaar, 1989), although, as in the United States, improved crop management techniques usually accompanied the introduction of hybrid maize; plant breeding and crop management jointly contributed to the sharp increases in maize yields. The proportion of gain attributed to genetic improvements is treated in more detail in later sections, with emphasis on hybrids and how sequential changes in their breeding and genetics have contributed to increased on-farm yield. c. Improved Populations. In the United States, the first hybrids were made from inbreds that had been developed by selfing some of the better OPCs of the 1920s. Breeders then worked to develop a second generation of improved hybrids using new inbreds made by selfing the same OPCs. They found that the second round of hybrids yielded little or no more than the first; it seemed that breeders must have selected most of the superior genotypes in the initial round of selfing in the OPCs. Some of the breeders conjectured that it might be possible to make new “synthetic” OPCs, with a potential for production of a superior second generation of inbred lines, by intercrossing some of the best inbreds from the first round of OPC selfing (Baker, 1990).

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To this end, the breeders made several “synthetics” by intercrossing the better inbreds of the day. Research in maize quantitative genetics had begun by this time, and some of the populations were subjected to various kinds of selection to make genetic improvements in the populations as such. The selection procedures were based on various assumptions about gene action and genetic variability (Hallauer and Miranda, 1988; Sprague, 1946, 1966). The Iowa State University Stiff Stalk Synthetic (BSSS) (Eberhart et al., 1973; Sprague, 1946) is one of the best known of these populations. Sprague (1946) lists the 16 progenitor inbred lines of this synthetic. Breeders practiced population improvement on other kinds of populations as well, such as locally adapted OPCs, exotic landraces, or composites of exotic landraces and/or inbred lines (e.g., Hallauer and Miranda, 1988; Sriwatanapongse et al., 1985). The name “recurrent selection” was coined (Sprague, 1952) to distinguish these kinds of population improvements from pedigree breeding (i.e., developing improved inbred lines from crosses of proven inbreds). Depending on the prospective end user, breeders intended to develop improved populations that would serve as sources of superior inbred lines or that could be used directly as productive cultivars per se. Results of their work are discussed in a later section.

II. GENETIC GAINS IN GRAIN YIELD OF HYBRIDS A. PREVIOUSLY REPORTED GENETIC YIELD GAINS Russell (1991) has summarized 16 independent estimates of genetic yield gains of sequentially released maize hybrids. Most of the estimates are based on comparisons of U.S. hybrids and were reported at intervals during the 20-year period of 1971–1991. Estimates ranged from 25–92 kg ha
1 year
1 with a mean of 57 kg ha
1 year
1. It seems likely that the wide range in values was caused, in part, by differing growing conditions among the several investigations and consequent differential interactions with old or new genotypes. Other factors, as well, might explain some of the variation, as follows: • Breeding might have been less effective in some regions (such as those with erratic and often severe abiotic stress) than in others. • Choice of the time series of hybrids for comparison could have had major effect on size of measured gain. For example, a short time series might show less improvement than a long one if the short time series happened to sample a period with small genetic gain.

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• Plant density of trials could affect the results differentially; older hybrids could have been disadvantaged if the plant density at which their yield was measured was higher than that for which they were bred or new hybrids could be disadvantaged if the density was below that which they required for maximum yield. • Harvest technology could be another source of difference; e.g., combine harvested trials (as compared with hand-harvested trials) could underestimate yields of older hybrids if combines failed to pick up all downed stalks (and ears) of older hybrids with poor standability. Conversely, hand-harvested trials could overestimate yields of the older hybrids if a standard shelling percentage was used to convert ear corn weight to grain weight instead of shelling the ears and weighing the shelled grain. Use of a standard shelling percentage could inflate estimates of grain weight on poorly pollinated nubbins of the older hybrids. However, these possibilities must remain conjecture. The salient fact is that all of the experiments listed by Russell showed positive and linear genetic yield gains, fluctuating around a mean of about 60 kg ha
1 year
1. Additional estimates of genetic gain in hybrids have been made since Russell’s review and are summarized in the following section.

B.

RECENT ESTIMATES 1.

OF

GENETIC YIELD GAINS

Argentina

Elite experimental maize hybrids tested in 154 regional trials in the Argentine corn belt during the 1979–1991 period had an estimated linear genetic gain of 105 kg ha
1 year
1 (Eyhe´ rabide et al., 1994). Estimates were based on comparisons with a common check. A second series of estimates extended the period (1979–1998) and showed an estimated genetic gain of 107 kg ha
1 year
1, or 2.9% year
1. Further analysis of these data indicated that gains were not linear during the entire period; gains were greater in the second decade than in the first, perhaps in part because of the introduction of single cross hybrids in the 1990s (Eyhe´ rabide and Damilano, 2001). 2.

Brazil

Analysis of 30 years of national maize trials in Brazil (1963–1993) indicates linear genetic progress of 123 kg ha
1 year
1 (Cunha Fernandes and Franzon, 1997). Trials were grown in three locations, and estimates were based on comparisons with a moving base of common entries.

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3.

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United States

Duvick (1997), updating previous reports for hybrids adapted to central Iowa in the U.S. corn belt, stated that a time series of hybrids and one OPC representing the period from 1930–1991 showed a linear gain for grain yield of 74 kg ha
1 year
1. The estimate was based on data from trials comparing 36 hybrids and one OPC, conducted over a period of 4 years, three locations per year, at three plant densities per location. Yield for each hybrid was for its “optimum density” in the trials: the plant density at which it gave its highest mean yield. A further update extended this time series through the year 2001; it showed an estimated linear gain of 77 kg ha
1 year
1 (Duvick et al., 2004b). This estimate applied “best linear unbiased predictors” (BLUPs) of hybrid grain yield; it was based on trials of 51 hybrids and four OPCs grown at three plant densities in the years 1991–2001, using yield of each hybrid at its “optimum density” as described earlier.

C. ESTIMATES

OF THE CONTRIBUTION OF TO TOTAL YIELD GAINS

BREEDING

Russell (1991) listed 14 estimates of genetic yield gain of hybrids as percent of total yield gain. (Total yield gain was defined as on-farm gain for appropriate regions during the time span of hybrids that were compared.) Most of the comparisons were for the U.S. corn belt but the list also included estimates for Ontario (Canada), France, and Yugoslavia. Estimates of genetic gain varied from 29 to 94%, with a mean of 66%. As noted by Russell (1991), several reasons can be advanced to show that this broad variability could be caused by inconsistencies in planning and executing the experiments, such as machine harvest vs hand harvest, or whether experimental estimates of genetic gain were adjusted to on-farm state averages. Nevertheless, all estimates agree in showing that hybrid maize breeding (i.e., genetic improvement) has played a major part in raising maize yields. Among the reports of genetic gain since Russell’s summary (reviewed in Section II.B), Cunha Fernandes and Franzon (1997) estimated that 57% of total gain in yield in Brazil was due to genetics. The other reports did not contain such an estimate, but further examination of data in Duvick et al. (2004b) provides an estimate of 51% for the contribution of genetics, when trial yields are adjusted to the equivalent of average on-farm yields for Iowa during the period 1930–2001. Based on these and earlier estimates, one can state that hybrid maize breeding during the past six or seven decades has been responsible for 50 to

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60% of the total on-farm yield gain. However, one also must acknowledge that the interaction between breeding and management (cultural practices) is such that neither tool could have caused the gains without aid of the other; changes in breeding and management continually have interacted in positive fashion.

D. CHANGES THAT HAVE ACCOMPANIED GENETIC YIELD GAINS IN HYBRIDS Breeders have noted that genetic gains in grain yield of hybrids may be accompanied by changes in other traits, sometimes as a result of direct selection, sometimes without direct intention by the breeders. And some traits have stayed essentially unchanged over the generations. Three reviews in the previous decade (Edmeades and Tollenaar, 1990; Russell, 1991; Tollenaar et al., 1994) have given detailed accounts of such changes and are recommended as sources of information and informed commentary on the topic prior to the early 1990s. The following sections update those accounts, as well as provide summaries and commentary for some of the earlier research reports.

1.

Plant and Ear Traits

a. Plant and Ear Height. Plant and ear height were reduced in the second era but not thereafter in a study of single cross hybrids representing U.S. corn belt hybrids of three eras: 1930s, 1950s, and 1970s (Meghji et al., 1984). A study of 28 hybrids and four OPCs adapted to Iowa, representing seven decades culminating in the 1980s, found no trend to reduction in plant height but a continuing trend to reduction in ear height (Russell, 1984). Plant height for a 1930–2001 time series of 51 hybrids and four OPCs adapted to central Iowa likewise was essentially unchanged over the years, but ear height showed a weak trend toward reduced height, approximately
3 cm decade
1 (Duvick et al., 2004b). b. Leaf Angle. Leaves became more upright in the 1970s era in a comparison of single crosses representing U.S. corn belt hybrids of three eras: 1930s, 1950s, and 1970s (Meghji et al., 1984). Leaf orientation below and above the ear became more upright with time in a study of U.S. Midwestern hybrids representing the decades from 1930–1970 (Crosbie, 1982; Russell, 1991). The trend to upright leaf orientation was greatest above the ear. Russell (1991) stated that the distinct increase in upright leaf orientation in the1970s decade was probably because inbred B73, with upright leaves for its time, was

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a parent in the set of 1970s single cross hybrids. The previously mentioned 1930–2001 time series of 51 hybrids and four OPCs for central Iowa (Duvick et al., 2004b) showed a similar trend toward more upright leaf habit. Ratings (as scores) in this study were for the entire plant. c. Tassel Size. Tassel weight was least in the most recent era in comparisons of single cross hybrids representing U.S. corn belt hybrids of the 1930s, 1950s, and 1970s; tassel branch number decreased consistently over the eras (Meghji et al., 1984). Tassel branch number and tassel weight decreased over time in a 1930 to 1991 time series of hybrids for Iowa (Duvick, 1997). Tassel branch numbers in the series averaged 2.5 fewer branches per decade, and tassel dry weight declined, on average, 0.5 g per decade. Reduction of tassel size continued in hybrids released during the next 10 years, as evidenced by scores for tassel size of hybrids in the 1930–1991 time series extended to 2001 (Duvick et al., 2004b). d. Leaf Number. Number of leaves per plant neither increased nor decreased in a 1930–1991 time series of Iowa hybrids and OPCs (Duvick et al., 2004b). Leaf number increased from 12.2 in the 1930s to 13.8 in the 1970s in comparisons of single cross hybrids representing U.S. corn belt hybrids of the 1930s, 1950s, and 1970s (Meghji et al., 1984). e. Leaf Area Index (LAI). Russell (1991) suggests that changes in LAI “may be specific to the particular cultivars used, rather than a general occurrence of all germplasm representative of similar eras.” This statement is borne out by the lack of consistent trends across experiments conducted by different researchers. LAI tended to be higher for recent hybrids than for older ones in a time series of four hybrids grown in Ontario (Canada) from 1959 to 1989 (Dwyer et al., 1991; Tollenaar, 1991). In another investigation, LAI increased over time in a set of eight maize hybrids that were commercially important in central Ontario between 1959 and 1988 (Tollenaar, 1989). However, a set of Iowa hybrids (20 single cross hybrids) representing the decades of 1930–1970 showed no obvious trend (Crosbie, 1982; Russell, 1991), and a 1930–1991 time series of 36 commercial hybrids and one OPC for Iowa also showed no change in LAI over time (Duvick, 1997). f. Leaf Rolling. Leaf rolling of plants, especially in the vegetative stage, is often seen when plants are subjected to drought. Leaf rolling consistently increased in newer hybrids in a set of 18 commercial hybrids adapted to central Iowa and representing the period 1953–2001 when the hybrids (grown in a rain-free environment in Chile) were compared with and without managed drought stress at various stages of development (Barker et al., 2005; Edmeades et al., 2003). Commenting on this observation, Barker et al.

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(2005) said “Apparently elite hybrids can reduce radiation interception and water use by leaf rolling, while generating sufficient assimilate flux to the ear to set adequate kernel numbers and conserving water for later in the season.” g. Staygreen. Staygreen, also called delayed leaf senescence, or resistance to premature death from unidentified causes, is consistently improved in newer hybrids (Crosbie, 1982; Duvick et al., 2004b; Meghji et al., 1984; Russell, 1991; Tollenaar, 1991). The improvement in each of these trials was greatest under environmental stress such as that induced (or accentuated) by high plant density. Staygreen improved over time in a set of 18 commercial hybrids adapted to central Iowa and representing the period 1953–2001 when the hybrids, grown in a rain-free environment in Chile, were (a) well watered, (b) subjected to induced drought at flowering time, or (c) subjected to drought during the final grain-fill period (Barker et al., 2005). Genetic gain for staygreen was greatest in the well-watered treatment and was least under drought imposed during the grain-fill period. h. Tillers. Number of tillers per 100 plants varied from hybrid to hybrid, but decreased slightly on average in a 1930–1991 time series of hybrids and OPCs for Iowa (Duvick et al., 2004b). i. Anthesis. Date of anthesis varied among decades, but showed no trend toward earlier or later dates in an Iowa series of four OPCs and 24 single cross hybrids representing the 1930s through 1980s (Russell, 1985). Similarly, heat units from planting to anthesis varied among hybrids but showed no general trend toward earlier or later in a 1930–2001 time series of 51 hybrids and four OPCs adapted to central Iowa (Duvick et al., 2004b). j. Silk Emergence. Silk emergence date trended toward earliness in an Iowa series of four OPCs and 24 single cross hybrids representing the 1930s through 1980s (Russell, 1985) and also in a 1930–1991 time series of 36 hybrids and one OPC for Iowa (Duvick, 1997). In the latter case, there was little or no trend to an earlier silk date in absence of stress, such as at low plant density, whereas higher plant density accentuated the trend, not because the new hybrids had earlier silking dates, but rather because the stress of high plant density delayed silk emergence of the older hybrids. k. Anthesis-Silking Interval (ASI). Anthesis usually precedes silk emergence, and the interval between the two events is called the anthesissilking interval. (The term “silk delay” is also used.) ASI was unchanged in hybrids representing earlier decades but was significantly shorter in hybrids

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of the 1970s in a set of Iowa hybrids (20 single cross hybrids) representing the decades of 1930–1970 (Crosbie, 1982). ASI became shorter in each decade except the 1980s in an Iowa-adapted series of four OPCs and 24 single cross hybrids representing 1930–1980 (Russell, 1985). ASI was significantly shorter in each interval in comparisons of single cross hybrids representing U.S. corn belt hybrids of the 1930s, 1950s, and 1970s (Meghji et al., 1984). ASI showed a highly significant linear trend to shorter intervals in a 1930–2001 time series of 51 hybrids and four OPCs adapted to central Iowa (Duvick et al., 2004b). The trend was greater in trials grown at higher plant densities. ASI became shorter over time in a set of 18 commercial hybrids adapted to central Iowa and representing the period 1953–2001 (Barker et al., 2005; Edmeades et al., 2003). This trend was exhibited when the hybrids were well watered and was accentuated when they were subjected to induced drought at flowering time. The experiment was conducted in a rain-free environment in Chile. l. Ears per Plant. Both total and harvestable ears per plant increased over the decades in a set of Iowa hybrids (20 single cross hybrids) representing the decades of 1930–1970 (Crosbie, 1982). A 1930–2001 time series of 51 hybrids and four OPCs adapted to central Iowa showed a highly significant trend toward more ears per 100 plants (+3.6 ears decade
1) (Duvick et al., 2004b). However, ears per plant showed no change over the decades in an Iowa-adapted series of four OPCs and 24 single cross hybrids representing 1930–1980 (Russell, 1985). The Russell experiment was planted at a single density (51670 plants ha
1), whereas data for the other two experiments were expressed as means of three densities in which the medium and high densities were higher than optimum for the older hybrids and, therefore, were more likely to cause barrenness in those hybrids. The end result would be a trend toward more ears per 100 plants (i.e., fewer barren plants) in the newer hybrids. m. Grain-Filling Period. Newer hybrids had a longer period of grain fill, calculated as time from silk emergence to black layer (physiological maturity), in observations of four discrete time series of hybrids adapted to the Midwestern United States (Cavalieri and Smith, 1985; Crosbie, 1982; Meghji et al., 1984; Russell, 1985). The newer hybrids flowered at approximately the same time as the older hybrids, and although their grain-fill periods were longer, they also exhibited a faster final dry-down rate, and so had little or no delay in relative maturity (based on grain moisture percentage at harvest time). The newer hybrids thus have more time to devote to grain fill; they exhibit increased efficiency in use of the growing season in the U.S. Midwest, which is limited on either end by average date of last frost in spring and first frost in autumn.

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n. Kernel Weight. Weight per 300 kernels increased in each decade except the final one in an Iowa-adapted series of four OPCs and 24 single cross hybrids representing seven eras from pre-1930s through the 1980s (Russell, 1985). Kernel weight did not change significantly over the decades except for a significant increase in the final (1970s) decade in comparisons of 20 single cross hybrids representing each decade from 1930–1970 (Crosbie, 1982). Weight per 100 kernels increased linearly in an Iowa-adapted series of 36 hybrids and one OPC representing the years 1930–1991, while number of kernels per ear decreased slightly but not significantly (Duvick, 1997). Weight per kernel exhibited a marked linear increase under well-watered conditions and also under drought stress at flowering, early, and midfill stages, but showed little or no increase under drought in late-fill and terminal stages in a set of 18 Iowa-adapted hybrids (evaluated in Chile) representing the period 1953–2002 (Barker et al., 2005; Edmeades et al., 2003). In appraisal of the results summarized in this section: the general trend to increased weight per kernel (and no increase in number of kernels per ear, in the one series where this was measured) may indicate that assistance in achieving genetic yield gain over time (and also gain in yield stability) is given more efficiently by plants with increased kernel weight than by plants with increased kernel number. o. Grain Protein Percentage. Grain protein percentage declined consistently in a series of 36 hybrids and one OPC for central Iowa spanning the period 1930–1991 (Duvick, 1997). The loss averaged 0.3% protein decade
1, with a series mean of 9.8% protein. p. Grain Starch Percentage. Grain starch percentage increased consistently in a series of 36 hybrids and one OPC for central Iowa spanning the period 1930–1991 (Duvick, 1997). The increase averaged 0.3% starch per decade, with a series mean of 70.4% starch. Because production of starch requires less energy than production of protein, selection for yield without attention to protein or starch percentage may have indirectly selected genotypes with less grain protein and more grain starch, giving a net increase in efficiency of grain production. q. Harvest Index (HI). HI did not change consistently over time in comparisons of single cross hybrids representing U.S. corn belt hybrids of the 1930s, 1950s, and 1970s (Meghji et al., 1984). HI did not change consistently in a set of 20 single cross hybrids representing Iowa hybrids of the decades of the 1930s through 1970s (Crosbie, 1982) or in a series of nine hybrids representing three decades (1959–1988) of maize production in Ontario when hybrids were compared at optimum plant density for yield for each hybrid (Tollenaar, 1989). HI did not change consistently over the decades in an Iowa-adapted series of four OPCs and 24 single cross hybrids

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representing 1930–1980 (Russell, 1985). HI improved on average to a small degree in successive hybrids in a 1934–1985 time series of Iowa-adapted hybrids (Duvick et al., 2004b) and in the same series extended to 1991 (Duvick, 1997). Higher plant density accentuated the trend. However, the superior HI of the newer hybrids at higher plant densities was not because of increased HI per se in the newer hybrids, but because of reduced HI in the older hybrids—the result of barrenness induced by stress. At higher densities the older hybrids maintained plant size but lost yield because of increased percentages of barren or partially barren plants. 2.

Resistance to Root Lodging

Hybrids improved over the years in resistance to root lodging in a series of Iowa hybrids representing the decades 1930–1960 (Russell, 1974). However, a later examination of a longer series of hybrids (1930–1980) showed no significant improvement in root lodging resistance, although all hybrids were decidedly more resistant than the OPCs of the 1920s (Russell, 1984). Four examinations of a successively lengthened time series of commercial hybrids for central Iowa showed linear increases in resistance to root lodging, in each examination (Duvick, 1977, 1984a, 1997; Duvick et al., 2004b). The four experiments contained hybrids released in the years 1939–1971, 1934–1978, 1934–1991, and 1934–2001, respectively. However, in two other trials of this series (for hybrids released in 1934–1989 and 1934–2000), improvement of root strength ceased in the final decade at about the 95% nonroot-lodged level (Duvick, 1992; Duvick et al., 2004a). The intensity of root lodging in a given trial can influence the differentiation between the older and the newer hybrids. Low levels of lodging (e.g., because of lack of the right combination of rain and wind or because of insufficient plant density) will make it impossible to differentiate among the more resistant hybrids because all will be in the range of 95 to 100% upright. Also, from time to time new hybrids might be released with less resistance to root lodging than intended, following which genetic improvements are implemented in newer releases. Either of these conditions (abiotic or genetic) could explain why apparent cessation of linear improvement in one time series is followed by a later time series in which gains are linear. 3.

Resistance to Stalk Lodging

Lodging resistance (not differentiated between root or stalk lodging) improved significantly in a series of hybrids grown in France from 1950–1985 (Derieux et al., 1987). Higher plant densities accentuated the difference between older and newer hybrids.

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Stalk lodging resistance improved consistently in a time series of Iowaadapted hybrids representing 1930–1960 (Russell, 1974). However, in a longer series (1930–1980), resistance to stalk lodging improved until the 1970s but did not improve in the 1980s (Russell, 1984). Five different examinations of a successively lengthened time series of commercial hybrids for central Iowa showed linear improvements in resistance to stalk lodging (Duvick, 1977, 1984a, 1992, 1997; Duvick et al., 2004b). The five series contained hybrids released in 1939–1971, 1934–1978, 1934–1989, 1934–1991, and 1934–2001. However, in one other trial for this series (hybrids released from 1934–2000), improvement ceased in the final decade at about the 95% nonstalk-lodged level (Duvick et al., 2004a). So for both root lodging and stalk lodging, one can conclude that although the overall trend is toward improved resistance to lodging, improvement may seem to stop from time to time. Additional experiments involving further extensions of the time series will be needed to test the validity of such conclusions.

4.

Tolerance to Abiotic Stress

a. High Temperatures. A 1930–1991 time series of 36 hybrids and one OPC for Iowa exhibited a linear increase in grain yield in a low yield season with a “hot and dry” summer, as well as in two highly favorable (exceptionally high yield) seasons (Duvick, 1997). Weather records for the “hot and dry” year (1991) indicate that temperatures during the flowering period were higher than normal and precipitation was exceptionally low (Iowa State University, 2003). b. Low Temperatures. The aforementioned 1930–1991 time series also exhibited a linear increase in grain yield in a “very cool and wet season” (Fig. 2) (Duvick, 1997; Duvick et al., 2004b). Weather records for that trial year (1993) indicate that precipitation amounts during the summer months were at record-breaking high levels, and daytime high temperatures were well below normal (Iowa State University, 2003). Dwyer and Tollenaar (1989) stated that “genetic improvement in the response to cold stress . . . has significant consequences for yield of fieldgrown maize, since many Canadian seasons are subject to short seasons or cool growing periods.” They showed (for a series of eight hybrids, released during the years 1959–1988) that reduction in photosynthetic response to irradiance (PRI) following a cold period during kernel fill was greater in older than in newer hybrids. A subsequent study (Tollenaar et al., 2000) showed similar results for a series of eight U.S. maize hybrids representing the 1930s, 1950s, 1970s, and 1990s.

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Figure 2 Grain yield per hybrid regressed on year of hybrid introduction for trials grown in 1992, 1993, and 2001. Seasons: 1992, highly favorable; 1993, cool and extremely wet; 2001, hot and dry. Yield per hybrid is for the density giving the highest average yield. From Duvick et al. (2004b). Copyright # 2004 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc.

Frei (2000), reporting for maize production in northwestern Europe, stated, “Breeding for adaptation to long and cool growing season has [led] to changes in growth behavior and yield physiology. . . . There is good evidence that low base temperature genotypes exist in northern breeding programs. . . . Breeding for lower base-temperature or cold tolerance can alleviate the stover versus grain antagonism.” [On a personal note, the author has seen some short-season inbred lines from the northern U.S. and Canada fail to make chlorophyll (white or striped seedling plants) in the cool early summer of central Germany, while locally bred lines in the same nursery were green and vigorous.] c. Drought. Russell (1974) stated that in high stress drought environments, a group of commercial hybrids representing the most recent era yielded considerably more than any other group. Hybrids and OPCs in the trial were adapted to Iowa and represented the approximate period 1930–1970. Examination of another set of hybrids comparing decades 1930–1980 showed that the hybrids of the 1970s and 1980s had superior

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yields in all environments, which included two drought-stress locations and two high-yielding environments (Russell, 1991). Comparison of a series of U.S. corn belt hybrids and OPCs representing the decades 1930–1980 showed linear gains in grain yield under either drought stress or irrigated treatments (Castleberry et al., 1984). The mean yield of the 1930s group was equal to 60% of the mean yield of the 1980s group when both groups were subjected to drought stress, and 63% of the mean yield of the 1980s group when both groups were given full irrigation. In Ontario, Canada, a newer hybrid was more tolerant of short drought periods than an older hybrid (Dwyer et al., 1992). During a drought period, the newer hybrid continued photosynthesis for about 2 h longer than the older one before starting to decline. A further study indicated that the two hybrids might adopt different mechanisms to tolerate moisture stress (Nissanka et al., 1997). The newer hybrid maintained relatively higher rates of photosynthesis and transpiration at a lower stem water potential. Although one cannot consider a comparison of only two hybrids as a “time series” that demonstrates trends over the years, examinations like these can give hints of possible trends and suggest profitable fields for future investigation. Derieux et al. (1987), comparing 33 maize hybrids (of three maturity groups) grown in France from 1950–1982, stated that modern hybrids are more adapted to stress, such as low temperature and drought. Regressions of mean yield per decade of release on mean yield per location of trial consistently showed that the newer the decade, the higher the yield at all locations. Water stress limited yield in some locations, particularly for hybrids in the semiearly category. As noted earlier in the section “High Temperatures,” a 1930 to 1991 time series of 36 hybrids and one OPC for Iowa exhibited a linear increase in grain yield in a season (year 1991) with exceptionally low precipitation during flowering, as well as in highly favorable seasons (Duvick, 1997). The same series, further extended (1930–2001), showed a linear increase in grain yield in another season (year 2000) when “heat and drought at silking time caused reduced yields” (Duvick et al., 2004a), and also in a third season (year 2001) when yields were low “because of a season-long drought, especially severe at the sensitive anthesis-silking period” (Fig. 2) (Duvick et al., 2004b). Weather records show that rainfall was well below average during the anthesis-silking period in 2000, and also in 2001 (Iowa State University, 2003). A time series of 18 commercial hybrids adapted to central Iowa and representing the period 1953–2001 showed linear gains in grain yield in each of three different watering regimes. The hybrids (grown in a rain-free environment in Chile) were (a) well watered, (b) subjected to drought at

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flowering time, or (c) subjected to drought during the grain-fill period (Barker et al., 2005; Edmeades et al., 2003). The hybrids in this experiment were a subset of the series studied by Duvick et al. (2004b), discussed previously. Gains in grain yield under optimal conditions were about twice as large as gains when stress coincided with flowering or grain filling. A time series of 2 OPCs and 52 hybrids adapted to central Iowa and representing the years (for the hybrids) 1934–2001 was subjected to a managed drought trial in Woodland, California (Barker et al., 2005). The hybrids in this experiment were the same as those studied by Duvick et al. (2004b), discussed previously. Watering regimes were similar to those described for the experiment in Chile (described earlier). Trials were grown at two plant densities. Both of the densities showed linear gains in grain yield for all three watering regimes. Figure 3 shows results of the trial at high density. Yield gain was greatest in the well-watered regime, although differences among the three regimes were not large. Annual genetic gains for all watering regimes were greater in the trial grown at the higher density, typical also of multidensity trials in rain-fed environments. All of the experiments described in this section show that genetic yield gains over time are expressed in drought as well as in favorable growing

Figure 3 Grain yield of two OPCs and 52 hybrids regressed against year of release. Hybrids were grown in Woodland, California, at 90,000 plants ha
1 in three managed stress environments: full irrigation, flowering drought stress, or grain-filling drought stress. Adapted from Barker et al. (2005).

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seasons. On average, the newer the hybrid, the greater is its drought tolerance. Discussion in later sections suggests possible causes of this improvement. d. Excessive Soil Moisture. As noted earlier in this section (“Low Temperatures”), a 1930 to 1991 time series of Iowa hybrids showed a linear gain in grain yield in a “very cool and wet season” (Duvick, 1997). That growing season, 1993, was one of the wettest on record for the state of Iowa (precipitation was two to three times normal), and soils were excessively moist (and in some cases flooded, although not in these trials) during much of the summer (Corrigan, 2003; Iowa State University, 2003). The linear gain in yield when the 1930 to 1991 time series was grown in this unusually wet growing season (see Fig. 2) indicates that although breeders had not selected directly for such abnormally wet growing conditions, they must have done so indirectly, perhaps through improvement in the ability of plants to set and develop kernels in the presence of reduced photosynthesis per plant or in the ability to tolerate a reduced uptake of key soil nutrients. One should note, however, that yield gain was least (59 kg ha
1) in the flood year of 1993 (the lowest yielding year) and greatest (82 kg ha
1) in the most favorable season, 1992. e. Deficiency of Soil Nitrogen. Maize cultivars (OPCs and commercial hybrids) typical of those grown in the U.S. corn belt in the decades 1930s through 1980s were compared at high and low soil fertility levels (in trials receiving approximately 200 kg ha
1 N, 90 kg ha
1 P2O5, and 150 kg ha
1 K2O versus trials in an area that, for two decades, had received no fertilizer and was planted to continuous maize) (Castleberry et al., 1984). Yield gains by decade were linear and positive under both of the soil fertility treatments (high and low), although the average annual gain was greater in the high fertility trial. Single cross hybrids representing four decades (1940–1970) of U.S. corn belt hybrids were compared at three levels (70, 130, and 200 kg ha
1) of nitrogen (N) fertilizer application (Duvick, 1984a). The l970s decade gave the highest grain yield at all N levels, and the 1960s decade produced the second highest yield at all N levels. A second experiment, described in the same report, compared five commercial hybrids spanning the period 1940–1978 at two treatments: high N, high plant density (215 kg N ha
1 and 54,000 plants ha
1) and low N, low plant density (70 kg N ha
1 and 35,000 plants ha
1) The two newest hybrids yielded more than the older ones at either treatment level. In both experiments, the interaction of hybrids  N rates was not statistically significant. Carlone and Russell (1987) compared OPCs and a series of single cross hybrids at three plant densities (34,445, 51,661, and 68,889 plants ha
1) and four N fertilizer levels (0, 80, 160, and 240 kg ha
1). The single crosses were

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chosen to represent hybrid genotypes of the decades 1930–1980. The trials suffered severe moisture stress in both years of trial, 1983 and 1984. Comparisons used the yield of each era at its optimum plant density. Hybrids of the older eras had their highest yield at lower densities; the newer hybrids had their highest yield at the higher densities. The 1980s era had the highest yield at each N level, and the 1970s era had the second highest yield at each N level. Carlone and Russell (1987) reported that levels of N fertilizer (0–240 kg ha
1) interacted with plant densities and with hybrid genotype. The optimum N level (level with highest yield) for hybrids of the 1940s, 1950s, and 1960s was higher than the optimum N level for hybrids of the 1970s and 1980s. However, the highest yields of the older group were lower than those of the newer group at all N levels, so one might conclude that the newer hybrids used N more efficiently than the older hybrids. Carlone and Russell (1987) also showed that hybrids within an era differed in response to densities and N levels. Two hybrids of the 1970s group increased in yield as densities and N levels increased, but one hybrid increased in yield significantly more than the other, such that the greatest difference in yield between them was at the highest plant density and the highest N level. McCullough et al. (1994a) stated that when two hybrids were compared in controlled environment chambers, an old hybrid (release year 1959) was more sensitive than a new hybrid (release year 1988) to stress caused by low soil N (0.5 mM) during early development. The new hybrid also maintained a higher rate of leaf photosynthesis per unit of N regardless of N supply. A second experiment (McCullough et al., 1994b) indicated that the higher N-use efficiency of the new hybrid under low N supply “is associated with higher N uptake and a higher leaf N per unit leaf area.” Field trials confirmed that the new hybrid yielded more than the old hybrid under both high N and low N treatments (Tollenaar et al., 1994, 1997). The yield difference between hybrids was accentuated when weeds were present, as compared with weed-free conditions; one might conclude that the new hybrid was also more “weed tolerant” than the old hybrid. As stated earlier, comparison of only two hybrids representing “early” and “late” eras is not equivalent to the study of trends in a time series of several hybrids, but the comparison can indicate possible changes over time and may suggest profitable areas of future research to discover trait changes that accompany sequential improvements in hybrid performance. f. Unspecified Abiotic Stress—“Stress versus Nonstress” Environments. Yield trial results can be categorized according to the average yield at each test site. One can assume that the lower the yield at a given site (in absence of obvious disease or insect problems), the greater the amount

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of “unspecified” abiotic stress. A stability analysis of the kind proposed by Eberhart and Russell (1966) can be used to compare yield response of individual hybrids or of groups of hybrids such as those released in a given decade. Yields of groups of hybrids (as in a decade) can be regressed on mean yield at each test site (e.g., Figs. 4 and 5). Russell (1991) cited such comparisons in several experiments. In general, all experiments showed that the newest groups of hybrids had the highest yields in all sites, regardless of average yield level at the site. However, linear regressions (b), showing degree of response of each group of hybrids to increasing site productivity, demonstrated no consistent trend of response. In some cases, b values were similar for all eras, whereas in other cases, b values were greater for new than for old eras, and in still other experiments, the b values differed randomly among eras (e.g., Fig. 4). Russell concluded that “there seems to be no distinct relationship between response and era of the hybrids. More likely, the responses were specific for the genotypes.” He

Figure 4 Yield response, b, for open-pollinated cultivars (OPCs) and six hybrid groups of 10-year eras, 1930–1980, to eight environment indexes (four locations  2 years). Reprinted from Russell (1991), # 1991, with permission from Elsevier, and also with permission from W. A. Russell and the Iowa State Journal of Research.

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Figure 5 Mean grain yield of hybrids released within two-decade spans, and of three OPCs, regressed on mean yield of all hybrids per environment. Trials were grown in a total of 13 environments during the years 1996–2000. Means of three densities per environment: 30,000, 54,000, and 79,000 plants ha
1. From Duvick et al. (2004b). Copyright # 2004 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc.

also considered the possibility that hand harvest vs machine harvest could have introduced a bias in some of the results that he reviewed. (Combines might fail to gather ears of lodged plants, and because older hybrids tend to lodge more than newer hybrids, yields of older hybrids would be underestimated.) Since the Russell (1991) report, Duvick et al. (2004b) presented results for 42 commercial hybrids and four OPCs tested in 13 environments in central Iowa during the years 1996–2000. They were grouped for stability analysis as follows: OPCs, 1930s and 1940s, 1950s and 1960s, 1970s and 1980s, and 1990s (Fig. 5). The regression for the OPCs was well below that for the hybrids, at 0.65. Regression values were similar for all hybrid eras (b ¼ ca. 1.0), although with a slight increase for the newest era. Thus, in this experiment the OPCs showed markedly less response than the hybrids to higher yield environments and the newest hybrid group gave the greatest response. However, in all cases, the newer the era, the higher the yield in any location, low yield or high. Stress tolerance increased significantly over the years. In conclusion, experiments described in this section (“Tolerance to Abiotic Stress”) have shown that hybrid tolerance to abiotic stress has

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increased consistently over the years. Although results are contradictory regarding whether newer hybrids are more or less responsive than older hybrids to higher yield environments, newer hybrids tend to be the most responsive, sometimes strikingly so (e.g., Barker et al., 2005; Duvick, 1984a, 1992). Reasons for such variability in response are not known but probably depend, as do most results, on interactions of genotype and environment.

5.

Tolerance to Biotic Stress

a. Insects. A 1930–1991 time series of 36 hybrids and one OPC for Iowa exhibited a linear increase in resistance to second-generation European corn borer (Ostrinia nubilalis Hubner) (ECB2), as measured by tunnel length following artificial infestation and by scores for evidence of natural infestation in yield trials (Duvick, 1997). This improvement took place even though breeders had not selected directly for resistance to ECB2. The same series showed no improvement in resistance to first-generation borer. Breeders and entomologists in the United States have collaboratively produced inbreds and breeding populations with improved natural tolerance and/or resistance to both generations of borer (see review in Russell, 1991), but there is no record of how or if these materials were used in commercial hybrids. They were not the source of increased resistance in the aforementioned 1930–1991 time series. In recent years (starting in 1996), seed companies have commercialized transgenic maize hybrids that are resistant to ECB. These hybrids, commonly called Bt hybrids, have been genetically engineered to incorporate a gene of Bacillus thuringiensis (Bt). Most of the first Bt hybrids contained the gene that produces the insecticidal protein Cry1Ab. The toxic Bt protein is effective against larvae from both first and second ECB generations (Peferoen, 1992; Traore et al., 2000). When subjected to artificial infestation, Bt hybrids showed significantly less tunneling from second-generation borer than non-Bt hybrids (Traore et al., 2000). They also had 9.7% more total plant weight in 1997 and 9.4% more grain yield in 1998 than their non-Bt counterparts. However, the amount of difference depended on the cultivar. Under natural on-farm ECB infestation, Bt hybrids usually yield significantly more than their isogenic counterparts in seasons when infestation is relatively heavy, but not when infestation is light. In 14 yield trials in Iowa in 1997, nine Bt hybrids yielded 7% more than their near-isogenic counterparts (Rice, 1997). Similar advantage for Bt hybrids was measured in several other corn belt states in 1997, but in 1998 with lighter infestation the average yield advantage was about one-fifth that of the 1997 amount (Gianessi and Carpenter, 1999).

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These data indicate that for Bt hybrids, as with other types of biotic and abiotic stress tolerance, the amount of yield gain contributed by the beneficial trait depends on the severity of the pertinent stress (in this case ECB infestation). Thus, James (2003a) stated that global yield gains due to Bt maize are currently estimated at 5% in the temperate maize-growing areas and 10% in the tropical areas. The tropical areas have more and overlapping generations of pests, leading to higher infestations and subsequently greater yield loss, in absence of resistance contributed by Bt. An additional restriction on potential yield gain from Bt hybrids is the need to plant “refuge areas” (perhaps 20–30% of total) of non-Bt maize to help prevent the development of resistance in the corn borer population (Ostlie et al., 2002). Biologists theorize that the pest population will eventually develop/increase new genotypes that are not susceptible to the Bt resistance genes, as has happened repeatedly (often in only a few seasons) in other instances of major gene resistance [also called vertical resistance (Simmonds, 1985; van der Plank, 1963)]. The use of refuge areas is intended to delay such genotypic change as long as possible. The refuge areas of course cannot provide the genetic yield advantage in the presence of corn borer that is provided by the Bt hybrids. More recently (in 2003), approval has been granted for use of a Bt transgene that prevents root injury by larvae of two different species of rootworm (Diabrotica barberi Smith & Lawrence, and Diabrotica virgifera virgifera LeCont) (James, 2003b; Rice et al., 2003). This Bt protein is called Cry3Bb1; it controls the rootworm larvae but not the adult beetle. As with Bt transgenic protection against corn borer, genetic yield advantage of rootworm resistance depends on the severity of infestation and its interaction with the environment. “Yield trials demonstrated that under heavy rootworm pressure and moisture stress the lack of corn rootworm larval injury in the [genetically engineered] corn resulted in substantially higher yields than [in] corn without the Bt protein. As rootworm pressure and moisture deficits declined, the yield advantage of . . . genetically engineered corn declined.” (Rice et al., 2003). Another similarity between the two kinds of Bt resistance is that refuge areas will be needed to delay the development of rootworm populations that are resistant to Cry3Bb1 (Rice et al., 2003). As with the corn borer Bt, Cry3Bb1 imparts vertical resistance and presumably will lose its effectiveness at some future date, thus necessitating replacement with a new genetic form (or forms) of resistance. b. Diseases. Frei (2000) stated that the minor presence of leaf diseases in northern Europe allows increased emphasis on selection for yield performance of maize hybrids for that area. This statement indirectly acknowledges that maize breeders in other regions must select hybrids with tolerance or resistance to locally prevalent diseases. The list of important diseases changes

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from time to time, as new cultural methods and/or new genotypes encourage diseases that had been absent or relatively unimportant (Dodd, 2000; National Research Council (U.S.) Committee on Genetic Vulnerability of Major Crops, 1972; Tatum, 1971). Dodd (2000), speaking for maize in the United States, stated that during the past 40 years at least 14 diseases of maize have had significant increase in importance, although not all have endured or have proved to be widespread. Their emergence as a problem is often encouraged by changes in cultural practice, such as an increase in continuous maize growing and/or in minimum tillage. At other times, widespread planting of a single genotype will encourage spread of a particular disease. Breeders and farmers react promptly to new disease problems; susceptible hybrids are dropped in favor of resistant ones (if they are on hand) and further breeding ensures that new releases have the needed level of resistance to the problem disease(s). This battle will never end. Breeding for disease resistance shows its success (and yield-enhancing contribution) most clearly when the disease is active on susceptible hybrids (comparable to breeding for insect resistance). It would be difficult or impossible to plot gradual gains in yield due to gradual increases in disease resistance alone; nevertheless, the cumulative effects of successful breeding for disease resistance surely must contribute to the general increase in the level of on-farm yields. As Russell (1993) said, “Selection for disease resistance has been an integral component of maize breeding for many years, yet there are few data reflecting directly how the success of this selection affects grain yield.” However, he does note that “. . . improvement for stalk quality has been well documented . . . and stalk quality is highly dependent on plant health.” One must acknowledge that interactions of disease resistance traits with other beneficial genetic changes are perhaps the rule rather than the exception. For example, Clements et al. (2003) stated, “These results suggest that Bt transformation events like MON810 are a useful supplement to hybrid resistance to fumonisin contamination and fusarium [Fusarium spp.] ear rot.” They went on to say that such benefits (reduced borer damage and therefore less chance for disease entry) may accrue to susceptible hybrids but not to hybrids with a relatively high level of resistance to fusarium. The interactions of the two traits (disease resistance and insect resistance) determine the outcome. One cannot credit either trait by itself.

6.

Response to Changes in Plant Density

a. High Density. Genetic yield gain as a result of adaptation to continual increases in plant density is perhaps the most clear-cut and quantifiable change in maize hybrids over the years. Cardwell (1982) calculated that

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increased plant densities contributed 21% of the gain in maize yield in Minnesota from 1930–1970. One must assume that not only the increase in plant density but also the introduction of maize genotypes that could withstand and profit from the higher densities was essential to achieving the gain. High plant density increases the deleterious effects of various kinds of stress —abiotic and biotic—and so increases the need for genetic improvements in stress tolerance (Troyer, 1996). Several examinations of U.S. hybrids, summarized by Russell (1991), showed that OPCs and old hybrids made their highest yields at lower densities typical of their era, whereas the newest hybrids yielded the most at the densities (always higher) typical of recent years. In other words, a hybrid usually gave the highest yield when grown at the density for which it was bred. Similar results have been shown for late-maturing hybrids in France and Ontario, Canada (essentially the same genotypes as grown in the United States), but not so for early maturing hybrids in France or Ontario (Derieux et al., 1987; Tollenaar et al., 1994). Tollenaar et al. (1994) suggested that because newer hybrids of the early maturity group have greater leaf area per plant as compared with the older hybrids of the same maturity, they do not respond to (or need) higher plant density. He stated that, in contrast, because the newer hybrids of the later maturity groups do not have increased leaf area per plant compared with older hybrids in their maturity group, the newer hybrids of the later maturity groups require more plants per hectare to increase leaf area (and thereby photosynthetic surface) per hectare. As mentioned in Section II.D.4, optimum plant density can be affected by the level of fertilizer N as well as by the hybrid genotype; hybrids differ within and between eras in their response to various combinations of N level and plant density (Carlone and Russell, 1987). A 1930–1991 time series of 36 hybrids and one OPC for Iowa (Duvick, 1997) showed the same general trends as in earlier trials of shorter versions of this series of hybrids (Duvick, 1977, 1984a, 1992); i.e., the older hybrids yielded more at lower densities typical of their era, whereas the newer hybrids yielded more at higher densities typical of their era. However, the newest hybrids in the 1930–1991 time series made only a very small gain in yield when planted at the highest density (79,000 plants ha
1) as compared with their performance at the intermediate density (54,000 plants ha
1). This suggests the possibility that future yield gains from breeding for adaptation to higher plant densities will come at a slower pace and/or will require more breeding effort, at least with the present breeding strategy. Breeders intending to increase genetic yield potentials may need to modify or replace current breeding strategies and/or selection criteria.

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Figure 6 Grain yield per hybrid regressed on year of hybrid introduction at each of three plant densities: 10,000, 30,000, and 79,000 plants ha
1. Best linear unbiased predictors (BLUPs) for hybrid grain yield based on trials grown in the years 1991–2001, three locations per year, one replication per density. From Duvick et al. (2004b). Copyright # 2004 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc.

b. Low Density. Duvick (1997) also showed that yields of the 1930–1991 series of hybrids did not significantly increase over time when the hybrids were planted at an extremely low plant density of 10,000 plants ha
1. In this nearly stress-free environment, all hybrids were able to express maximum yield potential per plant (or at least a close approach) and, under these conditions, the older hybrids showed virtually as much yield potential per plant as the newer hybrids. A further report, with the hybrid time series extended to 2001 (Duvick et al., 2004b), showed essentially the same results (Fig. 6); breeders have not significantly increased yield potential per plant, even though they have greatly increased maize yield potential per unit area.

7.

Herbicide Tolerance

An experiment designed to compare eight maize hybrids representing three decades of yield improvement in Ontario, Canada, showed that the hybrids reacted differentially to the herbicide bromoxynil (4-hydroxy-3,5-dibromobenzonitrile)

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(Tollenaar and Mihailovic, 1991; Tollenaar et al., 1994). The hybrids in this experiment, dating from 1959–1988, showed continuing improvement in tolerance to bromoxynil, with a statistically significant trend of decreasing phytotoxicity. They also showed continuing and significant improvement in grain yield, especially at higher plant densities. Commenting on these results, Tollenaar et al. (1994) suggested that improved antioxidant defense mechanisms may be associated with increased tolerance to bromoxynil and also with increased grain yield over the decades. They also said, “The small and, in particular, gradual nature of the increased bromoxynil tolerance suggests a highly complex, polygenic inheritance of this particular kind of stress tolerance.” Some maize hybrids now contain deliberately bred-in herbicide tolerance, primarily as transgenic resistance to broad-spectrum herbicides such as glyphosate (e.g., Hetherington et al., 1999). Herbicide-tolerant maize covered about 15% of the U.S. maize acreage in 2003 (ERS, 2003) and in 2002 was planted on about 4% of all land planted to transgenic crops globally (James, 2002). Strictly speaking, herbicide tolerance is intended to improve the efficiency of weed management and not necessarily to increase maize productivity, although better weed control could indirectly result in higher yields, if weed levels were high with other kinds of management. In extreme cases, herbicide tolerance/resistance can increase maize yield significantly and in strikingly large amounts. For example, initial experiments in several African countries indicated that when maize is bred to be resistant to a herbicide that normally is toxic to maize, seed coated with that herbicide can provide effective season-long control of Striga spp. (Kanampiu et al., 2003). Striga, a parasitic weed (sometimes called “witchweed”), can cause devastating crop loss in maize as well as other grain crops in those countries. The herbicide resistance (imadazolinone resistance, “IR”) is nontransgenic; it results from a mutation in an acetolactate synthase gene. The specific herbicides used in these experiments were imazapyr and pyrithiobac. When Striga density was high, the herbicide treatment resulted in a three- to fourfold increase in yield. Kanampiu et al. (2003) stated, “When the IR gene is incorporated into locally adapted varieties as in Kenya, this can result in improvements in maize growth and hence high maize yield benefits to small-scale farmers.” Herbicide tolerance, indirectly, can produce undesired results and lower yields. King and Hagood (2003) showed that postemergence control of johnsongrass with glyphosate increased the severity of maize chlorotic dwarf virus and maize dwarf mosaic virus in glyphosate-tolerant hybrids that were susceptible to those diseases. They said, “The increased disease severity resulted from greater transmission by insect vectors, which moved from dying johnsongrass to the crop.” However, disease severity did not

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increase in a virus-tolerant (and glyphosate-tolerant) hybrid subjected to the same conditions. The authors concluded that for fields infested with johnsongrass, the hybrid choice should be primarily for disease resistance and secondarily for herbicide resistance.

8.

Other Physiological Traits

a. Photosynthesis. As noted in earlier sections, leaf photosynthesis seems to be more efficient in newer hybrids than in older hybrids when they are compared in a range of stress conditions such as drought, low temperature, or low N supply. Such an increase in efficiency could help maize plants recover more rapidly from transient stresses such as those induced by cold weather, overly wet soils, or drought. As summarized by Tollenaar et al. (p. 215, 1994), “[These] findings, some of them preliminary in nature, suggest that although hybrid differences in leaf photosynthesis under unstressed conditions may not be indicative of actual or potential yield, hybrid differences in response of leaf photosynthesis to stress conditions may be a useful physiological indicator of high stable yields. To date, selection for yield per se has apparently provided a selection pressure in favor of stress-tolerant leaf photosynthesis.” b. Canopy Gas Exchange, Temperature. Nissanka et al. (1997) compared an old and a new hybrid (1959 vs 1988) in regard to whole plant gas exchange and stem water potential throughout a water-deficit stress cycle and during the subsequent recovery period upon rehydration. Under moisture stress, the new hybrid maintained relatively higher rates of photosynthesis and transpiration at a lower stem water potential than the old hybrid. During the recovery day, canopy photosynthesis was 53% higher and canopy transpiration was 31% higher in the new hybrid than in the old hybrid. Respiration per unit CO2 fixed was lower in the new than in the old hybrid in all conditions. The authors concluded that the new hybrid was more tolerant to water stress and recovered faster upon rehydration than the old hybrid. (As noted previously, comparison of only two hybrids is not evidence of a long-term trend, but it may give useful suggestions for further investigation.) Canopy temperature under drought stress consistently decreased, going from older to newer hybrids, in measurements of a set of 18 commercial hybrids adapted to central Iowa and representing the period 1953 to 2001 (Barker et al., 2005). The hybrids were grown in a rain-free environment in Chile and were subjected to managed drought stress at various stages of development. Barker et al. (2005) suggested that the trend to lower canopy temperature under drought stress may result from the lower

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radiation intensity on the more upright leaves of modern hybrids or on a greater capacity by these hybrids to capture soil water.

9.

Parentage and Genetic Diversity

As new hybrids replace those that preceded them, pedigrees and genotypes change. It can be instructive to know more about the nature of these changes. Which founder inbreds and/or OPCs remain in the pedigrees of current hybrids and which ones disappear? Has genetic diversity decreased, increased, or stayed about the same over the years? In a limited way some of these questions were answered by Duvick et al. (2004a,b) with respect to the time series of Iowa hybrids used for their studies of changes in hybrid performance over time. For example: • The 51 hybrids in the trials traced back to 53 founder sources: OPCs, synthetic populations, and inbred lines. The founders came primarily from the U.S. corn belt but a few were from the southeastern and northeastern United States or from Latin America. • Some families have persisted over the years and have contributed relatively large amounts (by pedigree) to present-day hybrids, whereas others appeared in pedigrees for only a few decades and then declined or disappeared. For example, Reid Yellow Dent, Iowa Stiff Stalk Synthetic, and Reid Iodent have been important contributors since they first appeared in pedigrees and they now contribute 33, 22, and 15%, respectively, to hybrids of the 2000s. However, Maryland Yellow Dent, Boone Country White, and the inbred Hy contributed briefly to pedigrees in the 1950s and 1960s but then disappeared completely from pedigrees of subsequent hybrids in the time series. Krug reached a peak use of 23% in the 1940s but declined rapidly to a steady level of about 3%, and some families appeared late but have made significant, if not large, contributions; for example, Argentinian Maiz Amargo appeared in the 1980s and has contributed 4 to 5% in each of the past two decades. • The pedigree information shows, therefore, that although certain lineages have predominated over the years of hybrid improvement and replacement, they have been supplemented significantly by additional, and diverse, lineages. On the whole, pedigree contributions have been broad and volatile; the record provides strong evidence for “genetic diversity in time” [as defined by Duvick (1984b)] in this 70-year time series of 51 hybrids for central Iowa. Genetic diversity, including genetic diversity in time (also called temporal genetic diversity), is widely acclaimed for its ability to provide beneficial genetic response (timely and wide-ranging) to new and/or unusual kinds of biotic or abiotic stress (FAO, 1996; Gollin and Smale, 1998;

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National Research Council (U.S.) Committee on Genetic Vulnerability of Major Crops, 1972; Rosenow and Clark, 1987; Simmonds, 1962; Smale et al., 2002).

10.

Molecular Markers

Pedigree data, although informative, do not identify genetic materials in the pedigree lineages, either qualitatively or quantitatively. Molecular marker data, tracing a given DNA fragment from one generation to the next, can enable quantification of the amount of founder germplasm that persists in successive generations. Application of this technology to the Iowa time series of hybrids (Duvick et al., 2004a,b) using simple sequence repeats (SSR) showed that • The number of alleles fluctuated from decade to decade, with about 40 to 50% of the total number of alleles present in any one decade. The study identified 969 alleles at 100 SSR loci in the array of hybrids and OPCs. • The number of alleles per locus was similar for the female and male parents of hybrids. • Large-scale turnover of alleles took place in the first decades (1930s and 1940s) of hybrid breeding (which agrees with pedigree data), indicating that many of the first inbred lines were not useful as parents for the next generation of breeding. They were dropped from breeding pools, and new and more successful breeding materials were brought in. • The initial large-scale turnover of alleles was followed by a relatively steady state of replacement until the 1970s (corresponding with the changeover from double cross to single cross hybrids) when the number of new alleles per decade again declined to what may be a new and lower steady state of replacement. • The alleles of the inbred parents of the modern hybrids (primarily single crosses) could be separated (with multidimensional scaling analysis) into two groups (called “stiff stalk” and “nonstiff stalk”), whereas alleles of the older hybrids (primarily double crosses) sorted into an undifferentiated third group (Fig. 7). This confirms the general observation that breeders (using pedigree and experiential data) have established two breeding pools to balance important traits (including those that enable use of inbreds as either seed parent or pollen parent) and/or to maximize heterosis when inbreds from the two groups are crossed with each other. The primary goal of such divergent selection is to enable the development of economically producible hybrids with improved on-farm yield and general performance.

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Figure 7 Scores for 94 inbreds contributing to Era hybrids on the first two dimensions of the multidimensional scaling analysis of SSR polymorphism data for 298 SSR loci (R2 ¼ 0.45 for the two-dimensional model). From Duvick et al. (2004b). Copyright # 2004 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc.

11.

Heterosis: Hybrid and Inbred Performance

a. Heterosis for Grain Yield. The phenomenon of heterosis in maize stimulated the initial research that led to the development and introduction of hybrid maize (e.g., Crow, 1998; Hayes, 1952; Shull, 1952), and maize breeders sometimes seem to have considered that breeding for higher yield is synonymous with breeding for increased heterosis. Few researchers have gathered data, however, to measure the degree to which the proportionate contribution of heterosis to grain yield has changed over the years of hybrid breeding (Duvick, 1999). b. Absolute Heterosis. Schnell (1974) summarized data comparing single cross yield and parental inbred yield from 17 experiments designed for other purposes. He stated that heterosis for the decades 1920–1970 showed “only a modest increase . . . as compared to the large simultaneous increase in the yields of inbreds. . . .” Schnell refers here to “absolute

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heterosis,” the difference between the yield of a single cross and the mean yield of its parental inbreds (midparent yield). The amount of annual increase in midparent yield was nearly as great as that of the single cross hybrids. Schnell also calculated heterosis as “relative heterosis” (absolute heterosis divided by single cross yield) and noted that it decreased from 75% in the 1920s to about 50% in the 1970s. This is because the denominator (single cross yield) increased at a faster rate than the numerator (absolute heterosis). Meghji et al. (1984) studied changes in heterosis for inbreds and their single crosses representing three decades (1930s, 1950s, and 1970s) of U.S. corn belt hybrid germplasm. Six inbreds per decade represented the 1930s and 1950s (two inbreds, WF9 and Os420, were in both decades) and seven inbreds represented the 1970s (four of the six single crosses for the 1970s contained the inbred Mo17). The trials were grown in Illinois; the year(s) of the trial is not indicated. Yields of inbreds and single crosses (averaged across densities) increased simultaneously over the decades. Absolute heterosis also increased over the decades; the increase averaged 51 kg ha
1 year
1 (Experiment 1, Table II). The increase was greater at a high density typical of the 1970s than at a low density typical of the 1930s. Duvick (1984a) compared inbreds and single crosses representing successful Iowa hybrids for the decades 1930–1970. Five unrelated inbreds for each decade were crossed in all possible combination to give 10 single crosses per decade; trials were grown in 3 years (1977–1979) at three densities Table II Contributions of Absolute Heterosis and Relative Heterosis to Grain Yield in Three Experimentsa 1930s Experimentb

Categoryc

1

SX yield Het Abs Het (%) SX yield Het Abs Het (%) SX yield Het Abs Het (%)

2

3

a

1940s

1950s

1960s

1970s

1980s


1

bd

kg ha 7097 4112 (58) 4600 2700 (59) 5941 3787 (64)

5300 3200 (60) 6371 3754 (59)

7407 4438 (60) 6900 4100 (59) 6865 4143 (60)

7000 3600 (51) 7174 4188 (58)

9538 6138 (64) 7900 4300 (54) 7929 4102 (52)

61 51 83 36 9164 4658 (51)

60 13

Adapted from Duvick (1999), with permission from American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. b Experiment 1: Means of two densities, data from Meghji et al. (1984). Experiment 2: Means of three densities grown in 1977–1979, data from Duvick (1984). Experiment 3: Means of three densities grown in 1992–1993, data from Duvick (1999). c SX yield, single cross yield; Het Abs, absolute heterosis; Het (%), relative heterosis. d Linear regression coefficient (kg ha
1 year
1).

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(30,000, 47,000, and 64,000 plants ha
1) representing densities of the 1930s, 1950s, and 1970s. Yields of inbreds and their single crosses (averaged across densities) increased simultaneously in each decade. Absolute heterosis increased in each decade, except in the 1960s. The increase averaged 36 kg ha
1year
1 (Experiment 2, Table II). In a second experiment, Duvick compared inbreds and single crosses representing successful Iowa hybrids for the decades 1930–1980. Results of the experiment are reported in Duvick (1999) and Duvick et al. (2004b). Seven representative single crosses per decade were compared with their parental inbreds during 2 years (1992 and 1993), at three locations per year, and three densities (30,000, 47,000, and 64,000 plants ha
1) per location. In 1993, a very wet year, one location was lost because of flooding. Yields of inbreds and their single crosses (as averaged across densities and years) increased simultaneously and by nearly the same amount in each decade (Fig. 8). Absolute heterosis (SX–MP) increased minimally

Figure 8 Yields of single crosses (SX), their inbred parent means (MP), and heterosis (as SX – MP). Single cross pedigrees are based on heterotic inbred combinations in Era hybrids during the six decades, 1930–1980, 12 inbreds and six single crosses per decade. Means of trials grown in three locations in 1992 and two locations in 1993 at three densities, 30,000, 54,000, and 79,000 plants per hectare, one replication per density. From Duvick et al. (2004b). Copyright # 2004 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc.

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(13 kg ha
1year
1) during the six-decade period (Fig. 8 and Experiment 3, Table II). However, the two growing seasons gave contrasting results. Absolute heterosis averaged over densities was constant over the decades in the 1992 trial, but it increased significantly (32 kg ha
1 year
1) in the 1993 trial (Fig. 9). The year 1992 was an optimal growing season with very high yields; whereas 1993 was a high-stress, low-yield year, with extremely wet and cool growing conditions. The trials of this experiment also exhibited contrasting outcomes when grown at different plant densities. Absolute heterosis, averaged over the two seasons, showed no trend over the decades at the lower density, increased slightly but unevenly at the medium density, and increased consistently (b ¼ 32 kg ha
1 year
1) at the higher density (Table III). Data from this experiment show, therefore, that yielding ability under stress has been improved to a greater degree in hybrids than in inbreds, even though (as shown in this and in other experiments) yield under stress is greatly improved over time for both of the categories (inbreds and hybrids).

Figure 9 Heterosis (as SX – MP) in two seasons: 1992 and 1993. Single cross pedigrees based on heterotic inbred combinations in Era hybrids during the six decades, 1930–1980, 12 inbreds and six single crosses per decade. Trials were grown in three locations in 1992 and two locations in 1993. Means of three densities: 30,000, 54,000, and 79,000 plants ha
1, one replication per density. From Duvick et al. (2004b). Copyright # 2004 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc.

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Table III Interaction of Plant Density with Decadal Changes in Absolute Heterosisa 1930s Densityb

Categoryc

Low

SX MP Abs. Het SX MP Abs. Het SX MP Abs. Het

Medium

High

1940s

1950s kg ha

6717 2062 4655 6569 2337 4232 5708 2308 3400

6703 2373 4330 7033 3065 3968 6648 3003 3645

7099 2395 4703 7960 3174 4786 6823 3063 3760

1960s

1970s

1980s


1

7387 2658 4730 8171 3493 4679 7192 3390 3802

bd 7187 3309 3877 8747 4352 4396 9098 4463 4635

8174 3875 4298 10024 4969 5055 10492 5476 5016

26 35
8 64 50 15 90 59 32

a

Adapted from Duvick (1999), with permission from American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. Data for means of seven single crosses and corresponding midparents per decade grown in five locations over 2 years (1992 and 1993). b Plant densities: Low, 30,000 plants ha
1; medium, 54,000 plants ha
1; and high, 79,000 plants ha
1. c SX, single cross; MP, midparent; Abs. Het, absolute heterosis. d Linear regression coefficient (kg ha
1 year
1).

These results agree with those of Meghji et al. (1984), who stated that the increase of absolute heterosis over the decades was greater at higher than at lower plant density. An intriguing area of research might be to look for the genetic and physiological changes that have accompanied the increases in absolute heterosis under stressful growing conditions. Can the needed genetic combinations be present only in heterozygous individuals or can they be gradually gathered into a single genome? Discoveries of intraspecific violation of genetic colinearity in maize (Fu and Dooner, 2002) may have implications for this area of investigation. To review this section, limited data indicate that absolute heterosis for grain yield has increased over the years to a small extent (more so under abiotic stress) but that its annual gain is less (sometimes much less) than total genetic gain in hybrid yield. Of course, one must recognize that one way to increase absolute heterosis would be to reduce inbred yields without increasing hybrid yields; this is not a desirable outcome. The current situation seems to be that yields of inbreds have increased in line with those of their hybrids, but at a slightly slower rate such that absolute heterosis is gradually increasing, especially when plants are grown under stress. c. Relative Heterosis. Calculations of relative heterosis (absolute heterosis as percentage of single cross yield) for the aforementioned three experiments indicate that although absolute heterosis increased over time

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in most comparisons, relative heterosis did not increase in the two Iowa experiments (Experiments 2 and 3, Table II), although it did increase in the Illinois experiment (Experiment 1, Table II). Relative heterosis in the Iowa experiment of 1992–1993 (Experiment 3, Table II) declined from 64% in the 1930s to 52% in the 1970s and 51% in the 1980s. Although absolute heterosis increased minimally over the decades in this experiment, the gain in single cross yield was greater than the gain for absolute heterosis, and so, as with Schnell data, the proportionate contribution of heterosis to grain yield was reduced over time. Interestingly, also, Schnell’s estimate of 50% for relative heterosis in the 1970s corresponds closely with values of 54 and 52% for the 1970s in the two Iowa experiments. Data summarized in this section suggest that relative heterosis for grain yield has not increased markedly over the years; it more likely has stayed constant or declined. d. Heterosis for Other Traits. Plant height and flowering date exhibit heterosis to a large degree in maize; crosses between two inbreds are always taller and earlier than the mean of the parents. Heterosis for these traits may (or may not) be related to some of the genetic interactions that produce heterosis for grain yield and so it may be informative to examine changes over time in heterosis for plant height, or other plant size measurements, and flowering date. Mean values for inbreeding depression in ear height and plant height decreased over time, in comparisons made by Meghji et al. (1984). This indicates that absolute heterosis for ear height and plant height decreased over time. In the same experiment, means for inbreeding depression of tassel weight and tassel branch number increased in the 1950s but decreased in the 1970s to levels lower than in the 1930s. This would indicate reduced heterosis for tassel weight and tassel branch number in the 1970s genotypes. Small but statistically significant trends toward reduced absolute heterosis for plant height (
3 cm 10 year
1), ear height (
4 cm 10 year
1), and heat units to anthesis (
11 heat units 10 year
1) were exhibited in the aforementioned comparison of inbreds and single crosses representing successful Iowa hybrids for the decades 1930–1970 (Duvick, 1984a). Absolute heterosis was reduced to a small degree for plant height but was not reduced for heat units to anthesis in the aforementioned comparison of inbreds and single crosses representing successful Iowa hybrids for the decades 1930–1980 (Duvick et al., 2004b). Data from these experiments indicate that, to a small degree, the size and maturity differences between inbreds and their hybrid progeny were reduced over time. However, the differences between the two classes remain (and probably will remain) large. For example, reexamination of data for plant

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height heterosis summarized in Duvick et al. (2004b) shows that the height difference between the two classes was reduced from about 85 cm in the 1930s to about 70 cm in the 1980s, primarily because of a reduction in height of the single crosses. If this rate of reduction in height difference could be maintained (
0.3 cm year
1 or
15 cm 50 year
1), it would take about five more 50-year cycles of selection to equalize inbred and hybrid height. Data for changes over time in heterosis for plant size and maturity agree in one respect with those for grain yield—neither category has exhibited major increases (or decreases) in absolute heterosis. However, absolute heterosis for grain yield has increased to a small degree (at least, under stress), whereas absolute heterosis for plant size and maturity has decreased to a small degree. Superficially, the two categories of heterosis do not seem to answer to the same genetic stimuli.

III. GENETIC GAINS FROM POPULATION IMPROVEMENT A. COMPARISONS

WITH

GENETIC GAINS IN HYBRIDS

Although the emphasis of this review is on maize hybrids and how successive changes in their breeding and genetics have contributed to increased on-farm yield, recurrent selection to make improved populations has interacted with and sometimes contributed to genetic improvements in hybrids (e.g., via useful inbred lines bred from improved populations). Additionally, for some farmers in some parts of the world, annual purchase of hybrid seed is not an option. For these people, improved populations, maintained by saving seed, are the only practical option for access to improved cultivars. Therefore, this section briefly summarizes genetic gains achieved by recurrent selection for population improvement in comparison with genetic gains in hybrid performance and comments briefly on the contribution of improved populations to hybrid maize yield. A comparison of genetic gain for four recurrent selection experiments with genetic gain for two time series of hybrids indicated that both methods produced about the same annual genetic gain for grain yield: 71 kg ha
1 year
1 for recurrent selection and 68 kg ha
1 year
1 for the hybrids (Duvick, 1977). Duvick described the two sets of experiments as follows: “Both took place in central Iowa; both occurred in about the same time frame; both had as a primary goal maximum improvement in yield.” For these reasons he thought it appropriate to compare the outcomes of the two kinds of breeding program. He also suggested, however, that selection pressure in the recurrent selection programs might have placed less weight on nonyield

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traits (e.g., root and stalk lodging) than was the case in the hybrid breeding programs, thus allowing greater progress for yield per se in the recurrent selection programs. So the programs were not completely equivalent in selection goals. Duvick (1977) called for more comparisons of recurrent selection with hybrid breeding (which typically is based on pedigree breeding), suggesting that “Maize breeding probably could be helped by the results of quantitative genetics studies specifically designed to compare ‘recurrent selection using the pedigree method’ and ‘recurrent selection using the population pool method.’ Good data, demonstrating the strong and weak points of these two related and proven methods, would help the entire hybrid maize breeding effort in its goal of producing good hybrids as quickly and efficiently as possible.” This request was easier to make than to grant, however, and to the author’s knowledge, no such paired breeding programs have been designed and executed. Even to compare estimates of genetic gain for hybrids with estimates of genetic gain for recurrent selection is difficult because most reports of progress in recurrent selection express yield gains in units cycle
1 rather than units year
1, and number of years per cycle usually is not stated and must be inferred (if possible) from descriptions of the breeding cycle. However, Edmeades and Tollenaar (1990) summarized 17 estimates of genetic gain in temperate environments and 10 estimates of genetic gain in tropical environments, with all estimates expressed as kg ha
1 year
1. With one or two exceptions, the estimates for temperate environment are for time series of commercial hybrids and the estimates for tropical environments are for recurrent selection programs intended to produce improved populations. Genetic gain in grain yield for the temperate programs averaged 66 kg ha
1 year
1, whereas genetic gain for the tropical programs averaged 145 kg ha
1 year
1. The average gain for the temperate experiments is identical to the average from the previously mentioned summary by Russell (1991). This result is not too surprising because for the most part the two lists cite the same reports, although the two lists are not identical. The list of tropical experiments shows a broad range of estimates, from 51–310 kg ha
1 year
1. Edmeades and Tollenaar (1990) explained the high values for the estimates of the tropical programs (primarily recurrent selection) as follows: “The higher average rate of gain reported from the tropics is generally the result of one, sometimes two and very occasionally three selection cycles per year, the use of relatively unimproved germplasm with a broad genetic base, and a selection scheme that was based on family performance.” Although it is probably true that the first gains are the easiest in any professional breeding program that starts with landrace materials, it also seems likely that some of the high gains reported for the recurrent selection programs in

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the tropics result from effective selection technology for important traits such as drought tolerance (e.g., Ba¨ nziger et al., 1999; Bolan˜ os and Edmeades, 1992), combined with rapid turnaround of breeding generations. Edmeades and Tollenaar (1990) presented evidence for the possibility that first gains are the easiest. They said that “. . . tropical maize . . . in its unimproved state is tall, leafy, lodging-prone and has a harvest index of about 0.35.” They stated that initial selection in unimproved populations in the tropics results in shorter plants and reduced lodging, improved HI, and reduction in barrenness. The present review has shown that temperate hybrids have shown little or no change over the years in plant height, leaf number, or HI when hybrids are grown at the plant density for which they were bred. This may indicate that farmer selectors had already changed these traits to a close approximation of “optimum” levels when they developed the corn belt OPCs that were the basis of hybrid breeding. However, the first hybrids clearly surpassed parent OPCs in root and stalk strength and in resistance to barrenness. Although the stress of constantly increasing plant density continues to sort out hybrid genotypes with increasingly greater resistance to lodging and barrenness, these improvements are not as dramatic as those of the initial hybrids compared with their parent OPCs. Taking into account these changes (or lack thereof) in temperate breeding programs, one might predict that annual yield gains of population improvement programs for tropical materials eventually will move to lower (but nevertheless acceptable) levels, similar to those for hybrid improvement in the temperate zones. Following the relatively easy gains resulting from initial reductions in plant size and lodging and from increases in HI, yield gains will need to come from more gradual improvements in tolerance to locally important kinds of abiotic and biotic stress. Leaving aside comparisons between hybrid breeding and recurrent selection, numerous published reports testify clearly that recurrent selection for grain yield and/or general performance can give positive results in temperate as well as in tropical materials, and it can do so with acceptable investments of time and effort (e.g., Hallauer and Miranda, 1988; Lamkey, 1992; Russell, 1991; Sriwatanapongse et al., 1985). Several methods have been tried; some worked well and some did not (e.g., Edwards and Lamkey, 2002; Lamkey, 1992), much as has been true for various kinds of pedigree breeding applied to hybrid development. One difference between recurrent selection and hybrid breeding has been that breeders sometimes have used recurrent selection primarily to intensify expression of a single trait such as resistance to ECB or high grain oil percentage (Klenke et al., 1986; Sprague, 1952). They often discovered that other important traits such as grain yield or stalk digestibility could deteriorate, sometimes as an indirect response to strong selection for the intensified

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trait or sometimes simply because of insufficient selection pressure for the other important trait(s) (Hallauer and Miranda, 1988; Ostrander and Coors, 1997; Russell, 1991). Such populations could have only limited value as sources of commercially useful inbred lines because inbreds (and the hybrids they produce) must be as well balanced as possible for a full selection of important traits. Transfer of the improved trait to useful inbred lines may require a long-term effort or may not even be worth doing if its intensification depends on the deterioration of another important trait.

B. RELATIVE CONTRIBUTIONS OF POPULATION IMPROVEMENT AND PEDIGREE BREEDING “Pedigree selection is the most widely used breeding method to develop inbred lines for use as parents of hybrids.” . . . “Pedigree selection will always be an important component of modern corn-breeding programs (Hallauer et al., 1988, pp. 470–471),” “Pedigree selection was and is the most commonly used selection method of line development (Hallauer and Miranda, 1988, p. 10).” These statements, although in agreement with the general experience of hybrid maize breeders, should not be construed to say that recurrent selection for population improvement has not made vital contributions to hybrid maize breeding. Inbred lines such as B14, B37, and B73 have, in their time, been parents of hybrids that dominated maize plantings in the U.S. corn belt, and they also have been important sources of germplasm for further breeding by pedigree selection. These inbreds are direct products of the previously described population, BSSS (Russell, 1991). Other elite inbreds derived from improved populations could be named as well (e.g., Hagdorn et al., 2003), although their impact has been more limited than that of the “big three.” Nevertheless, as stated earlier, pedigree breeding has been and remains the backbone of hybrid maize breeding. [See Troyer (1996) for a detailed and first-hand description of pedigree breeding in action.] Planned single crosses, successful commercial hybrids, and crosses (or backcrosses) of an elite line to an improved population are typical starting points for pedigree selection to produce new inbred lines. The author knows of no detailed, data-based exposition of the reasons for predominance and persistence of pedigree breeding to develop inbred lines and so can only speculate about reasons for this situation. Perhaps one reason for the predominance of the pedigree method is that its parental materials—inbred lines—have been very widely tested, not only in breeders’ performance trials, but also by thousands of farmers. Breeders typically have started selfing and pedigree selection from crosses of inbreds (or their progeny) that were used in widely successful hybrids. Each hybrid can be considered as a “test cross” for its parental inbreds. An unexpected

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weakness in one or both parents is more likely to be discovered when a hybrid is grown by thousands of farmers over a period of years, as compared with growing an improved population in a relatively small number of yield trials for one or two seasons. Conversely, one also can be more confident of identifying genotypes that can give top performance over a wide variety of environments if the replication number is in the thousands rather than in the dozens (or fewer). (Commercial seed companies have a unique advantage here in that they can gather trial data from hundreds or thousands of onfarm “strip trial” comparisons. Although these data may be intended primarily for potential use in sales promotion, they also provide the company’s breeders with a deep mine of information about comparative performance of a given genotype over a broad range of environments.) A second consideration is that the odds of getting a superior inbred—with good balance for all traits—from selfing a cross of two currently topperforming inbreds are probably higher than the odds of getting a line of equivalent merit from selfing an excellent but relatively heterogeneous improved population, even though truly superior (and novel) genotypes may well exist in the improved population. This second possibility leads to further speculation that a new program (such as some of those in the tropics) may have greater success in extracting useful inbred lines from improved populations than has been exhibited in mature temperate breeding programs. One reason could be that some of today’s improved populations for the tropics are very high quality; they have benefited from years of experience in designing and/or choosing proper environments for performance trials and in the development of improved designs for recurrent selection. The potential utility of such populations (e.g., for production of stress tolerant hybrids) has been predicted by Edmeades et al. (1997), who said “The probability of obtaining a hybrid that yielded 40% greater than the trial mean under severe stress was 4-fold greater when lines were extracted from a drought-tolerant source population than from its conventional counterpart. . . . We conclude that droughtor N-tolerant elite source populations provide a greater proportion of drought- or N-tolerant inbred lines and hybrids.” A second reason could be that there will be few or no truly superior adapted inbred lines for a new breeding locality. If improved populations (improved for the traits needed in the area where hybrids are to be grown) are on hand, they may be the best available source of germplasm for the development of inbred lines. They will be better than local OPCs and better than crosses of unadapted inbreds that may be “elite” elsewhere but are not well suited to the local environment. (This scenario contrasts with the course of events in the U.S. corn belt, where two or three decades of pedigree breeding had brought out many superior inbreds by the time improved populations from recurrent selection programs were ready for use.)

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In years to come, pedigree selection based on planned crosses of inbred lines may become more competitive in new breeding localities (such as in the tropics); however, further expertise in population improvement via recurrent selection may enable continued development of populations that are valuable sources of elite inbred lines for those environments. A final speculation about the utility of improved populations is that as expertise grows in molecular biology, breeders may learn how to “mine” improved populations for valuable genes or gene combinations with more precision and better odds of success than can be done with current methods of breeding and selection. The improved populations could provide a wider range of useful genetic diversity than can be achieved with pedigree breeding and would have the diversity in much more useful forms than exist in unadapted exotic cultivars and landraces. These latter materials are high in genetic diversity but are also high in “useless” genetic diversity. Remarks from Hallauer et al. (1988, pp. 531–532) make an appropriate conclusion for this section. They said “Recurrent selection and pedigree selection . . . should not be considered in opposition to one another. Rather, the two systems should complement each other. The goals of the two systems are different, but the ultimate objective is the same—contribute to genetic gain.” It seems safe to predict that as experience and technology progress, breeders will find increasingly profitable ways to utilize recurrent selection for development of a genetically diverse assortment of superior inbred lines that can be parents of successful hybrids.

IV. ANALYSIS AND CONCLUSIONS A. POSSIBLE REASONS

FOR

GENETIC YIELD GAINS

This review has shown that hybrid maize breeders have consistently increased the yielding ability of hybrids during the past 70 years and that genetic gains in grain yield are still linear. As the yielding ability of the hybrids has increased, other traits have changed as well, in directions that were sometimes intended and sometimes unintended or at least unplanned. Conversely, some traits have not changed (or have changed very little), sometimes at the intention of the breeders and sometimes despite the breeders’ intent to make a change. It will be instructive to categorize the various trait changes (or stabilities) as described in Section II.D. They can be categorized as (1) trait changes that promote the efficiency of grain production, (2) trait changes that increase tolerance to biotic and abiotic stress, (3) intended trait stabilities, and (4)

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unintended (or unplanned) trait stabilities. The various trait changes are briefly summarized and arbitrarily sorted into these four groups as follows.

1.

Trait Changes that Promote Efficiency of Grain Production

• Leaf angle has become significantly more upright, especially since about the 1960s. • Tassel size has been markedly reduced. • Newer hybrids have longer period of grain fill but faster dry down; therefore they are not later in harvest maturity and make better use of the latter part of the growing season. • Kernel weight is greater in newer hybrids except under drought stress at late or terminal periods of grain fill. • Newer hybrids have lower percentage grain protein. • Newer hybrids have higher percentage grain starch. • In some experiments, newer hybrids are markedly more responsive to favorable environments (they make more efficient use of bountiful inputs), although results are not consistent in this regard.

2.

Trait Changes that Increase Tolerance (or Exhibit Evidence of Increased Tolerance) to Biotic and Abiotic Stress

• Grain yield has increased in linear fashion; increases are greatest at high plant density and are exhibited in high stress as well as low stress environments, in poorly fertilized as well as in well-fertilized environments. • Leaf rolling during drought stress is increased, perhaps because of changed leaf orientation; potentially this can help maintain lower leaf temperature and reduce water use. • Staygreen (resistance to stress-induced premature death) is markedly improved. • Anthesis-silking interval is shortened, especially when hybrids are subjected to conditions of abiotic stress such as drought or high plant density. • Newer hybrids show increased resistance to barrenness when trials are subjected to abiotic stress such as drought at flowering time or higher plant density. • Newer hybrids have higher HI than older ones if trials are subjected to biotic stresses that induce barrenness. • Hybrids show linear improvements in resistance to root lodging, although some trials indicate a ceiling at about 95% nonroot-lodged plants.

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• Hybrids show linear improvements in resistance to stalk lodging, although some trials indicate a ceiling at about 95% nonstalk-lodged plants. • Hybrids show linear improvement in yield in seasons with above-average temperature during the growing season. • Hybrids show linear improvement in yield in seasons with below-average temperature during the growing season. • Newer hybrids are more drought tolerant. • Newer hybrids are more tolerant of excessive soil moisture (water-logged soils). • Newer hybrids are more tolerant of soil nitrogen deficiency. • Newer hybrids are more tolerant of unspecified abiotic stresses (“lowyield” sites). • Newer hybrids are more tolerant of ECB2, and, recently, transgenic hybrids have expressed a sharply increased level of resistance to both generations of European corn borer and (separately) to two species of rootworm. • Circumstantial records show that new kinds of disease resistance are added continually in response to new disease problems, but the contributions to the yield of sequential changes in disease resistance are not documented. • Newer hybrids, more tolerant of the stresses of higher plant density, enable the use of higher plant density to maximize yield and therefore the grain yield potential per unit area is increased. • Newer hybrids show increased tolerance to a specific herbicide, apparently correlated with increased antioxidant defense mechanisms; hybrids can be bred (using conventional genetics) to be resistant to another specific herbicide; and in recent years transgenesis has been used to impart tolerance to a third herbicide. • A newer hybrid has more efficient photosynthesis than an older one, especially under stress, and shows an improved capacity to recover the photosynthetic rate after stress. • A newer hybrid has more efficient canopy gas exchange, stem water potential, transpiration, and respiration than an older hybrid when plants are subjected to water stress. • Canopy temperature under drought stress is decreased. • Pedigree contributions have been diverse and are in a state of constant change, although with a steady core of persistent lineages. The consequent increase in genetic diversity (in time and in place) theoretically will provide an increased stability of performance in the presence of diverse biotic and abiotic stresses. • Molecular marker studies validate the pedigree information and show, further, that parent inbreds in recent years of the hybrid time series can be divided into two genetically different groups called stiff stalk and nonstiff stalk.

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• Absolute heterosis for grain yield usually has increased to a small degree, with the greatest increase when trials are grown under stress of high plant density or drought.

3.

Intended Trait Stabilities

• Plant and ear height have been relatively stable with a weak trend to lower plant and ear height. • Anthesis date is relatively unchanged. • Date of silk emergence is unchanged over time in absence of stress, but newer hybrids silk earlier than older hybrids when trials are subjected to abiotic stress such as drought or high plant density; this is because silk emergence is delayed (or fails entirely) in the older hybrids when subjected to these kinds of abiotic stress. • Tillering ability is rarely expressed at modern plant densities; tillering is slightly reduced at low plant density.

4. Unintended (or Unplanned) Trait Stabilities • Leaf number is unchanged. • LAI is unchanged in the U.S. corn belt, but may be increased in early maturity regions of Ontario (Canada). • Number of ears per plant is not changed in absence of stress. • HI of temperate hybrids is not changed if hybrids are grown at the density for which they were bred. • Yield potential per plant is not increased; i.e., newer hybrids do not yield more than older hybrids at super-low plant density in absence of abiotic stress. • Relative heterosis for grain yield has not increased and, in some cases, is slightly reduced. • Absolute heterosis for plant height, ear height, and flowering date has not increased and, in some cases, is slightly reduced. Comparison of the categories in this summary shows that the list of improvements in stress tolerance is by far the longest. This may indicate that yield advances in hybrid maize depends primarily on increase in stress tolerance—more specifically, on increased tolerance to the stresses that typically occur in the environments where the hybrids are grown. It is true that yields of both older and newer hybrids are reduced in the presence of stress, either biotic or abiotic, but it also is true that the newer hybrids

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always yield more than the older ones in the presence of stress and so, by this definition, are more stress tolerant. Changes that impart efficiency, such as smaller tassels, more upright leaves, faster dry down of grain (to enable longer kernel-fill period), and lower percentage grain protein, may have also enabled higher yields. These changes were not selected directly, but they might have been selected indirectly as a consequence of selection for increased grain yield per unit area because they (presumably) improve the efficiency of transforming sunlight, CO2, and soil nutrients into plant constituents, and so help increase yields. The author is not surprised by the stability of maturity and plant size over the years despite the fact that increased plant size and later maturity correlate positively with increased grain yield. The average date of first frost and farmer prejudice against tall plants have automatically set the limits to which breeders can select for harvest maturity and plant height, at least for U.S. corn belt hybrids. Some of the unintended (or unplanned) stabilities present surprises, or at least do not agree with conventional wisdom. Probably the breeders’ intended constraint on plant and ear height has indirectly held leaf number and leaf area index constant. In theory, the more leaf area per unit land area (up to a maximum LAI of about four or five), the more photosynthesis and consequently the higher the grain production per unit land area. However, additional leaf area per unit land area has been achieved not by increasing leaf area per plant, but by crowding more plants together. One could hypothesize that shorter internodes could allow more leaves and more leaf area per plant without increasing plant and ear height. This could substitute for (or extend) the effect of increased plant density. However, plant architecture (e.g., leaf dimensions, shape, or angle) might need to be changed if such an approach were used. Because leaf number usually is positively correlated with time to flowering, it might not be possible to increase leaf number and still hold the flowering date constant (a requirement for nearly all temperate maize production). Some may express surprise that HI of maize hybrids in the United States has not increased (in absence of stress-induced barrenness) because of frequent statements that an increase in HI was an important reason for the higher yields of green revolution wheat and rice cultivars (e.g., Donald, 1968; Peng et al., 1999; Reynolds et al., 1999; Swaminathan, 1998). However, the first maize hybrids (as well as their parent OPCs) had about the same HI as the initial high yield rice and wheat cultivars. It would appear that farmer selection (at least in U.S. corn belt OPCs) had already brought maize plants to an approximation of the 40–50% HI of initial green revolution rice and wheat cultivars. Interestingly, rice and wheat breeders at the international centers now suggest that an increase in biomass should receive major (perhaps primary) emphasis as they strive to effect further increases in yield for

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their crops (e.g., Peng et al., 1994, 1999; Reynolds et al., 1999). “Clearly, there are limits to how far HI can be further increased in improved varieties [of rice] (Peng et al., 1994).” The lack of increase in yield potential per plant is surprising until one reflects on the fact that up until now, the sole method of increasing yield per unit area has been to increase plant density while maintaining constant ear size (grain weight per plant). Although theoretically it may be possible to raise yields per unit area by increasing yield per plant while holding population constant (at lower densities than present norms), for one reason or other this has not been done except in experimental studies (e.g., Fasoula and Fasoula, 2000; Tokatlidis et al., 2001). Such a goal might be practical, however, for hybrids suited for drought-prone environments, where planting at lower density is prudent but the ability to utilize occasional higher rainfall by increasing yield per plant would be desirable. The relative lack of increase in heterosis, either absolute or relative, also will surprise those of us who have supposed that the primary way to increase hybrid yield is to increase heterosis for grain yield. It would appear that comments by Hallauer (1999, p. 486) about recurrent selection can apply to hybrids as well. He stated, “the additive effects of alleles with partial to complete dominance were of greater importance but dominant and epistatic effects could not be discounted.” It is also intriguing to note that absolute heterosis for grain yield is greatest under conditions of stress, in company with the knowledge that an increase in stress tolerance of all kinds has strongly accompanied gains in hybrid yield over the years. Both inbreds and hybrids are greatly improved in stress tolerance, but hybrid gains are greater that those of their parental inbreds.

B. POTENTIAL HELPS OR HINDRANCES GAINS in YIELD

TO

FUTURE

For the past 70 years, breeders have improved the yielding ability of hybrid maize by selecting new genotypes with adaptation to the ever-increasing stresses of constantly increasing plant density as well as to other kinds of prevalent abiotic and biotic stress. They have done so by exposing these hybrids to an increasing diversity of environments as the capacity for wide area testing (especially in the commercial sector during the past few decades) has been dramatically increased by investments in mechanization and information management. Breeders consistently have selected for higher average yield with acceptable grain moisture, improved standability, resistance to local diseases and insect pests (that often change in kind or intensity over the years), and tolerance to increased plant density. (Farmers continually plant the newest hybrids at a density higher than recommended, thus forcing

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breeders to continually raise the density at which they select the next round of hybrids.) Newer hybrids have managed the stress of high plant density (which usually accentuates other kinds of stress) in two ways: increased stress tolerance and increased efficiency of grain production. Efficiencies in grain production that presumably are provided by more upright leaves, smaller tassels, and lower grain protein percentage may have gone about as far as they can go; leaves cannot be much more vertical without clasping the stem, tassels on some hybrids have no side branches at all, and it is possible that livestock feeders will not be willing to accept grain with a smaller percentage of protein than is now at hand. Therefore, breeders will need to make even greater progress in improving traits for stress tolerance if they are to continue the linear increase in grain yield that has prevailed during most of the past 70 years of hybrid maize breeding. Increased emphasis on such traits as tolerance to extremes of temperature, to drought, to excess soil moisture, and to deficiency of soil nitrogen (without neglecting simultaneous selection under nonstressed, highyield conditions) will probably be worth the effort. For each of these traits, development and deployment of managed stress levels (such as managed irrigation in a rain-free climate) may increase the precision and reliability of selection for the trait. However, widespread on-farm testing in a full range of “natural” environments, from high yield to high stress, must be the rock on which all other selections are based. Past experience has shown that overemphasis on a single trait may produce correlated changes in other traits, sometimes with unintended (and unwanted) results. There is no substitute for extensive trials, in both small plot and strip test format, of hybrids in final stages before release (and also just after release). Although one may not be able to identify the different kinds of stress (or nonstress) in those trials with precision, one can be sure that such testing will subject the genotypes to a multitude of stresses common to the area of adaptation. Some of the stresses will be severe to catastrophic and some will be so minimal that only the hybrids can sense them. In the end the genotypes with the broadest tolerance to these stresses will give the highest yields in both low-yield and high-yield environments.

C.

PREDICTIONS

Mark Twain is supposed to have said, “Prophecy is a good line of business but it is full of risks.” This caution surely applies to predictions about prospects for future yield gains in hybrid maize, or in other kinds of maize cultivars.

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Increased grain yield per se may be less important in the future than in the past for an increasingly large part of maize production. Specialty products such as maize with altered or higher oil or protein content, or high extractable starch, or maize bred for use as a biofuel may rise in importance in addition to or sometimes in place of commodity feed grain production (e.g., Lambert et al., 1998; Ng et al., 1997; Whitt et al., 2002). Conceivably, some of these novel kinds of maize could command a premium price. Although yield of some kind would be important for these specialty categories of maize, grain yield per se would take second place to yield of a specified product—yield of a specific kind of oil, protein, starch, etc. However, despite these possible new markets for specialty types of maize, the demand for maize as a feed grain will increase robustly if the developing world continues to improve its economy and therefore its appetite for meat, milk, and eggs (Rosegrant et al., 2001; Taha, 2003). Consequently, production of maize as a commodity grain for animal feed will continue to dominate commercial maize production. Increasing the on-farm grain yield of maize hybrids will persist as a primary goal of maize breeders. Farmers will require (and demand) hybrids that dependably produce maximum yield with minimum inputs—a key requirement for the profitable production of commodity maize grain. Although the past does not necessarily predict the future, 70 years of linear genetic yield gain in many parts of the maize-growing world would seem to predict that similar gains will continue for at least the next few decades. This prediction is more likely to hold for regions that have recently adopted hybrids and complementary intensive management practices. Production in those regions will not be as near to the theoretical maximum yield potential (Cassman, 1999; Duvick and Cassman, 1999) as may be true for regions with a longer period of constantly increasing yields. However, even in regions with longer periods of yield increase such as the U.S. corn belt, continuation of the long-standing practice of remolding adapted germplasm, and slowly and carefully importing useful pieces of exotic germplasm, will guarantee increased yield potential and increased stability of yield for years to come. On-farm yields may not always rise in line with genetic improvements, however. In the coming decades, residents of the wealthier countries may force their farmers to reduce (or, in some cases, eliminate) applications of synthetic fertilizers and/or pesticides, with the intention to improve environmental and human health. Such reductions could reduce maize yields. Even though the newer hybrids would yield more than the older ones (including the OPCs) following such a reduction of inputs, their yields could very well be lower than before reductions were put into effect, although the amount of loss (if any) would depend on the extent of the input reductions.

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If this speculated mandatory reduction of management inputs should come to pass, one can envision a future in which genetic yield gains will continue but on-farm yields will stagnate or decline. In other words, the genetic improvement of critical traits might be needed simply to maintain yields at an even level or to minimize reductions in yield. Without genetic improvements, yields would drop even more. This scenario highlights the importance of breeding for resistance to disease and insect pests, tolerance to deficiency of soil nutrients, and tolerance to other locally important kinds of abiotic stress. One should note, however, that breeders have already made good progress in breeding for such kinds of tolerance/resistance. As shown repeatedly in this review, breeding for increased resistance to abiotic and biotic stress has been the basis for 70 years of yield increase and dependability in hybrid maize. With stimulus from farmers and the marketplace, it seems reasonable to suppose (and predict) that breeders can and would increase the intensity of breeding for stress tolerance, with special emphasis on specific stresses that were amplified by the reduction of specific inputs. For example, data reviewed in earlier sections of this report indicate that successive hybrids have shown steady and significant genetic improvement in the efficient use of soil nitrogen, although the selection for improvement was indirect (and unintentional). If application of nitrogen fertilizers should be curtailed, maize breeders could select directly for efficient use of soil nitrogen, and should be able to make even faster progress than in earlier years. Such progress might enable a continued increase (or at least prevent a decline) in on-farm yields, despite mandated reductions in fertilizer use. Likewise, with regard to pesticides, as noted earlier, a small number of effective aids from biotechnology for genetic improvements in disease and insect resistance are already in place and more are contemplated (Fernandez-Cornejo and McBride, 2002; James, 2003a; Rice et al., 2003; Runge and Ryan, 2003). Continuation and enhancement of these transgenic breeding efforts could incrementally and significantly increase the ability of farmers to maintain yields without the use of pesticides. (An example of enhancement of transgenic protection would be to progress from the construction of vertical resistance genotypes to building systems of horizontal— more durable—resistance.) Importantly, the transgenic improvements will be most useful if they are integrated with continuing achievements in conventional breeding for pest resistance (which itself will be enhanced by new knowledge and tools, contributed by molecular biology). In time, there will be no distinction between “biotechnology protection” and “conventional protection.” For some maize producers, an even more drastic reduction in inputs may occur in future years, as water for irrigation becomes less available in regions where irrigation is important (and sometimes essential) for maize production

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(Rosegrant et al., 2002). As with breeding for tolerance to nutrient imbalance or biotic stresses, breeders in regions of water shortage will need to increase their emphasis on breeding for drought tolerance, either by moving from indirect to direct selection or by increasing the emphasis on already existing direct selection for drought tolerance. Past experience indicates that this trait can be improved without sacrificing the ability to produce high yields with favorable water balance, and evidence now accumulating indicates that these breeding efforts may someday be made even more efficient because of new insights provided by molecular biology investigations. So, as with postulated reductions in soil nutrient and pesticide application, breeders should be able to mitigate yield reductions, or even maintain on-farm yields, in many of the areas where irrigation is reduced or eliminated. A less optimistic prediction, based on past experience, is that the price of successive increases in genetic yielding ability will continue to rise, just as it has risen during the past 70 years. In the United States, for example, today’s crew of maize breeders (broadly defined to include those who work in biotechnology applied to plant breeding) is many times larger than the crew that made advances during the first two or three decades of hybrid maize breeding (Crosby et al., 1985; Duvick, 1984a; Fernandez-Cornejo, 2004; Frey, 1996), yet the genetic yield gain per year is no larger than in past times—the gain is linear. (And therefore the expenditure per unit gain is many times larger now than in early years.) Judging from this past experience, today’s plant breeding crew will need to be enlarged even further if future gains are to be made at the same pace as is now achieved unless much more efficient methods of breeding are developed and implemented. Some have predicted that significant gains in breeding efficiency will occur as various tools of biotechnology are employed, utilizing new genetic discoveries and new knowledge of genes and gene action in the maize plant. However, the current state of the art primarily is in the development of techniques and data (e.g., Emrich et al., 2004; Jansen et al., 2003; Lawrence et al., 2004). Biotechnology is not the primary tool for the development of improved cultivars. Although useful new traits have been added via transgenesis, the number actually in use is still small (but growing) and is limited to such defensive traits as pest resistance and/or herbicide tolerance. Breeders must continue to use routine empirical breeding methods to effect broad-scale yield improvements in the “base germplasm,” which they then can enhance with useful transgenes. Today’s maize breeders cannot reduce the effort devoted to “conventional plant breeding” without also reducing the rate of progress in the development and release of higher-yielding cultivars, cultivars with a full and well-balanced spectrum of the important traits that in sum govern maize yield. Additionally, the present large investment in the testing of transgenic products for safety adds significantly to the cost of their use for genetic

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improvement. Comments by soybean breeders on the use of biotechnology for soybean breeding are relevant to its use in maize breeding, as follows: “Despite all the opportunities, biotech soybeans face numerous challenges. Because of the cost of technology and regulatory clearance, it is difficult for developers to earn sufficient returns on research investment for many biotech traits. Gaining acceptance of crops and grain derived through biotechnology, particularly in Europe, is yet another challenge. Although biotechnology acceptance is increasing around the world, significant challenges will be faced by those wanting to bring new transgenic traits to market (Soper et al., 2003).” One hesitates to predict how much time must pass before the current investment in biotechnology can bring about significant savings in time and money per unit gain in maize yield, even though it is obvious that biotechnology research and development indeed will give significant and innovative support to maize breeding. New techniques, based on new knowledge in molecular biology, are increasing breeding efficiency incrementally, and with time the number and use of such new techniques can only grow. As stated by Runge and Ryan (2003), “Plant biotech R&D in the pipeline as of 2001 through mid-2003 indicates almost a hundred new traits in testing. Represented in these activities are about 40 universities (mainly land grants) and about 35 private sector companies. Without question, more research and development as measured by field tests has been devoted to biotech traits in corn than to any other crop, attracting scores of public and private institutions. Among the traits in testing for corn were 19 new agronomic properties, four traits for fungal resistance, seven for herbicide tolerance, four for insect resistance, ten trials focusing on some form of marker genes, and over 30 for output and other end-use traits.” This leads to the author’s final prediction, that despite the efforts of some segments of society (e.g., Turning Point Project, 1999a,b) to stop or otherwise hinder the use of biotechnology as an aid in food production (for detailed description of this subject, see Charles, 2001), the tools of molecular biology increasingly will aid maize breeders in their efforts to develop superior hybrids. The most important and long-reaching aid will come not so much from transgenes per se as from the use of a wide range of biotechnology-based tools to give breeders a deeper knowledge of the genetics and physiology of the maize plant; with this knowledge they will be able to fine-tune maize genomes to achieve desired ends with much greater speed and efficiency. Valuable assistance will continue to come directly from some classes of transgenes, e.g., new and more broadly effective versions of Bt transgenes (James, 2003a; Rice et al., 2003). Breeders in the tropics and subtropics will have particular use for transgenes that impart effective resistance to the wide array of disease and insect problems in those regions, especially for instances

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in which adequate genetic resistance cannot be found in maize itself. In all cases, these transgenes will prevent yield loss in the presence of epidemics and infestations of the pest in question. In those places where pest depredation is chronic, yield levels on average will advance. However, as noted earlier, the use of transgenes for pest resistance must move beyond changes that contribute vertical resistance to those that impart more durable kinds of horizontal resistance, not an easy task but one that will become possible as biotechnology-based knowledge and insights accumulate. As biologists move beyond genomics to proteomics, metabolomics, and other related disciplines (some as yet unnamed or undiscovered), they will help maize breeders identify key genes and gene systems/interactions in the maize plant, and then, working together, the molecular biologists and breeders will learn how to regulate or reconstruct them in ways that will intensify the expression of key traits, whether for tolerance to heat and/or drought, to chronic disease problems, or to tolerance of deficiency of soil nutrients such as nitrogen. Breeders will learn how to mine genetically diverse exotic maize populations for improved versions of key genes or (more likely) their regulator systems and, with aid of molecular markers, to move them into elite germplasm with precision and efficiency (see Tuberosa et al., 2002). (Marker-assisted selection is already used extensively in some crops, including maize, to move useful genes or linkage groups from exotic to adapted germplasm and/or elite cultivars.) In some cases, knowledge of the identity and/or function of important genes in other species (such as for tolerance to certain kinds of abiotic stress) will enable biologists to identify their counterparts in maize, enabling breeders and molecular biologists, collaboratively, to fine-tune the actions of the maize genes, sometimes by using key regulatory sequences from the exotic organism (e.g., Appenzeller et al., 2004; Shou et al., 2004). Of course, individual genetic changes will be useful only when they efficiently interact with the complete genetic complex in ways that improve the overall performance of the plant according to goals set by the breeder. Knowledge of the ways in which expression of a key gene affects the action and products of other genes (i.e., the pleiotropic and epistatic effects), and consequent interactions with the environment, will be critical to the success of improving the action of any individual gene. Finally, beyond all these conjectured advances, the maize breeders can always hope for the Holy Grail of plant physiologists, major improvement in the efficiency of the primary steps of converting intercepted solar radiation into stored carbon, effected without disrupting the rest of the infinitely complicated network of interacting genetic systems and ensuing physiological processes that operate the functioning maize plant or any other organism.

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However, in the end, after all the modern tools have been employed to the maximum degree, maize breeders will still need to walk the fields, observing their latest creations under the widest possible range of conditions that commonly occur in the intended region of adaptation. (One could describe this activity as “personal perusal and evaluation of the genotype  environment interaction.”) The breeders will collate this subjective and highly personal information with objective information obtained from widespread performance trials, laboratory analyses, and other factual tests of performance. In brief, maize breeders will need to practice the art as well as the science of breeding if they are to continue the genetic progress that has been achieved by their predecessors during the past three-quarters of a century. “As the joy of artistic creation begins to assert itself we may expect many interesting developments in the newer methods of corn breeding (H. A. Wallace, 1930, unpublished manuscript).”

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Frei, O. M. (2000). Changes in yield physiology of corn as a result of breeding in northern Europe. Maydica 45, 173–183. Frey, K. J. (1996). “National plant breeding study. I. Human and financial resources devoted to plant breeding research and development in the United States in 1994”. Rep. No. 98. Iowa Agriculture and Home Economics Experiment Station, Ames, IA. Fu, H., and Dooner, H. K. (2002). Intraspecific violation of genetic colinearity and its implications in maize. Proc. Natl. Acad. Sci. USA 99, 9573–9578. Gianessi, L. P., and Carpenter, J. E. (1999). “Agricultural Biotechnology: Insect Control Benefits”. National Center for Food and Agricultural Policy, Washington, DC. Gollin, D., and Smale, M. (1998). Valuing genetic diversity: crop plants and agroecosystems. In “Biodiversity in Agroecosystems” (W. Collins and C. O. Qualset, Eds.), pp. 237–265. CRC Press LLC, Boca Raton, FL. Goodman, M. M., and Brown, W. L. (1988). Races of corn. In “Corn and Corn Improvement” (G. F. Sprague and J. W. Dudley, Eds.), pp. 33–79. American Society of Agronomy, Madison, WI. Grobman, A., Salhuana, W., Sevilla, R., and Mangelsdorf, P. (1961). “Races of Maize in Peru: Their Origins, Evolution, and Classification”. National Academy of Sciences – National Research Council, Washington, DC. Hagdorn, S., Lamkey, K. R., Frisch, M., Guimaraes, P. E. O., and Melchinger, A. E. (2003). Molecular genetic diversity among progenitors and derived elite lines of BSSS and BSCB1 maize populations. Crop Sci. 43, 474–482. Hallauer, A. R. (1999). Heterosis: What have we learned? What have we done? Where are we headed? In “Genetics and Exploitation of Heterosis in Crops” (J. G. Coors and S. Pandey, Eds.), pp. 483–492. American Society of Agronomy, Inc., Crop Science Society of America, Inc., Soil Science Society of America, Inc., Madison, WI. Hallauer, A. R., and Miranda, J. B. (1988). “Quantitative Genetics in Maize Breeding”, 2nd Ed., Iowa State University Press, Ames, IA. Hallauer, A. R., Russell, W. A., and Lamkey, K. R. (1988). Corn breeding. In “Corn and Corn Improvement” (G. F. Sprague and J. W. Dudley, Eds.), pp. 469–565. American Society of Agronomy, Inc., Crop Science Society of America, Inc., Soil Science Society of America, Inc., Madison, WI. Hayes, H. K. (1952). Development of the heterosis concept. In “Heterosis” (J. W. Gowen, Ed.), pp. 49–65. Iowa State College Press, Ames, IA. Hetherington, P., Reynolds, T., Marshall, G., and Kirkwood, R. (1999). The absorption, translocation and distribution of the herbicide glyphosate in maize expressing the CP-4 transgene. J. Exp. Bot. 50, 1567–1576. Iowa State University (2003). University Extension Weather Information: Iowa Averages, Climatology Data [Online]. Available by ISU Extension http://mesonet.agron.iastate.edu/ climodat/ (viewed November 6, 2003). James, C. (2002). “Preview: Global Status of Commercialized Transgenic Crops 2002. ISAAA Briefs”. Rep. No. 27. ISAAA, Ithaca, NY. James, C. (2003a). “Global Review of Commercialized Transgenic Crops: 2002 Feature: Bt maize”. The International Service for the Acquisition of Agri-biotech Applications (ISAAA), Ithaca, NY. James, C. (2003b). “Preview: Global Status of Commercialized Transgenic Crops: 2003. ISAAA Briefs”. Rep. No. 30. ISAAA, Ithaca, NY. Jansen, R. C., Jannink, J.-L., and Beavis, W. D. (2003). Mapping quantitative trait loci in plant breeding populations: Use of parental haplotype sharing. Crop Sci. 43, 829–834. Kanampiu, F. K., Kabambe, V., Massawe, C., Jasi, L., Friesen, D., Ransom, J. K., and Gressel, J. (2003). Multi-site, multi-season field tests demonstrate that herbicide seed-coating herbicideresistance maize controls Striga spp. and increases yields in several African countries. Crop Prot. 22, 697–706.

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King, S. R., and Hagood, E. S. (2003). The effect of johnsongrass (Sorghum halepense) control method on the incidence and severity of virus diseases in glyphosate-tolerant corn (Zea mays). Weed Technol. 17, 503–508. Klenke, J. R., Russell, W. A., and Guthrie, W. D. (1986). Recurrent selection for resistance to European corn borer in a corn synthetic and correlated effects on agronomic traits. Crop Sci. 26, 864–868. Lambert, R. J., Alexander, D. E., and Han, Z. J. (1998). A high oil pollinator enhancement of kernel oil and effects on grain yields of maize hybrids. Agron. J. 90, 211–215. Lamkey, K. R. (1992). Fifty years of recurrent selection in the Iowa Stiff Stalk Synthetic maize population. Maydica 37, 19–28. Lawrence, C. J., Dong, Q., Polacco, M. L., Seigfried, T. E., and Brendel, V. (2004). MaizeGDB, the community database for maize genetics and genomics. Nucleic Acids Res. 32, 393–397. Malin, J. C. (1944). “Winter Wheat in the Golden Belt of Kansas”. University of Kansas Press, Lawrence, KS. McCullough, D. E., Aguilera, A., and Tollenaar, M. (1994a). N uptake, N partitioning, and photosynthetic N-use efficiency of an old and a new maize hybrid. Can. J. Plant Sci. 74, 479–484. McCullough, D. E., Giradin, P., Mihajlovic, M., Aguilera, A., and Tollenaar, M. (1994b). Influence of N supply on development and dry matter accumulation of an old and a new maize hybrid. Can. J. Plant Sci. 74, 471–477. Meghji, M. R., Dudley, J. W., Lambert, R. J., and Sprague, G. F. (1984). Inbreeding depression, inbred and hybrid grain yields, and other traits of maize genotypes representing three eras. Crop Sci. 24, 545–549. Miquel, P. (2001). “La France et ses paysans: Une histoire du monde rural au XXe sie`cle”. L’Archipel, Paris. National Research Council (U.S.) Committee on Genetic Vulnerability of Major Crops (1972). “Genetic Vulnerability of Major Crops”. National Academy of Sciences, Washington, DC. Ng, K.-Y., Pollak, L. M., Duvick, S. A., and White, P. J. (1997). Thermal properties of starch from 62 exotic maize (Zea mays L.) lines grown in two locations. Cereal Chem. 74, 1997. Nissanka, S. P., Dixon, M. A., and Tollenaar, M. (1997). Canopy gas exchange response to moisture stress in old and new maize hybrid. Crop Sci. 37, 172–181. Ostlie, K. R., Hutchison, W. D., and Hellmich, R. L. (2002). “Bt Corn and European Corn Borer: Long-Term Success Through Resistance Management”. Rep. No. BU-07055-GO 1997. Regents of the University of Minnesota, St. Paul, MN. Ostrander, B. O., and Coors, J. G. (1997). Relationship between plant composition and European corn borer resistance in three maize populations. Crop Sci. 37, 1741–1745. Paszkiewicz, S., and Butzen, S. (2001). Crop Insights Vol. 11, No. 6: Corn Hybrid Response to Plant Population [Online]. Available by Pioneer Hi-Bred International, Inc. http://www. pioneer.com/usa/agronomy/corn/1106.htm (viewed January 13, 2004). Paterniani, E., and Goodman, M. M. (1977). “Races of Maize in Brazil and Adjacent Areas”. CIMMYT, Mexico D.F. Peferoen, M. (1992). Engineering of insect-resistant plants with Bacillus thuringiensis crystal protein genes. In “Plant Genetic Manipulation for Crop Protection” (A. M. R. Gatehouse, V. A. Hilderand, and D. Boulter, Eds.), Vol. 7, pp. 135–153. CAB International, Wallingford, UK. Peng, S., Cassman, K. G., Virmani, S. S., Sheehy, J., and Khush, G. S. (1999). Yield potential trends of tropical rice since the release of IR8 and the challenge of increasing rice yield potential. Crop Sci. 39, 1552–1559. Peng, S., Khush, G. S., and Cassman, K. G. (1994). Evolution of the new plant type for increased yield potential. In “Breaking the Yield Barrier: Proceedings of a Workshop on

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METABOLIC ENGINEERING OF ISOFLAVONE BIOSYNTHESIS Oliver Yu1 and Brian McGonigle2 1

2

Donald Danforth Plant Science Center, St. Louis, Missouri 63132 Crop Genetics, E.I. du Pont de Nemours and Company, Wilmington, Delaware 19880

I. II. III. IV. V.

VI.

VII. VIII. IX. X. XI.

The Health Benefits of Isoflavones in Soybeans Biological Functions of Isoflavonoids in Plants Targets of Isoflavone Engineering The Pathway Leading to Isoflavone Biosynthesis The Entry Point Enzyme: Isoflavone Synthase A. The Discovery of Isoflavone Synthase B. The Mode of Action of Isoflavone Synthase Other Key Enzymes in Isoflavone Biosynthesis A. Chalcone Isomerase B. Chalcone Reductase Transcriptional and Posttranscriptional Regulation of Related Pathways Metabolic Engineering of Isoflavone Accumulation in Legumes Metabolic Engineering of Isoflavone Accumulation in Nonlegumes The Bottleneck of Isoflavone Pathway Engineering: “Metabolic Channeling?” Conclusions References

Isoflavones are phenolic secondary metabolites found mostly in legumes. These compounds play key roles in many plant–microbe interactions and are associated with the health benefits of soy consumption. Because of their biological activities, metabolic engineering of isoflavonoid biosynthesis in legume and nonlegume crops have significant agronomic and nutritional impact by enhancing plant disease resistance and providing dietary isoflavones for the improvement of human health. This review first outlines the current understanding of isoflavone biosynthetic pathways, with focus on key structural enzymes and transcription factors that directly relate to the pathways. Then it summarizes recent progress on metabolic engineering of isoflavone biosynthesis in both legume and nonlegume plants. The major limitations of these approaches, as well as the “metabolic channeling” theory, which is proposed to explain some of the results from the engineering ß 2005, Elsevier Inc. works, are also discussed.

147 Advances in Agronomy, Volume 86 Copyright 2005, Elsevier Inc. All rights reserved. 0065-2113/05 $35.00

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I. THE HEALTH BENEFITS OF ISOFLAVONES IN SOYBEANS Soybean (Glycine max) has been cultivated in China for nearly 4000 years. Soybeans, along with rice, wheat, and two kinds of millet, were regarded as the five sacred crops. For centuries in China, soybean provided the majority of dietary proteins. Along with the spread of Chinese culture, soybean became a staple legume in almost all of the eastern and southeastern Asian countries. Today in these countries soybean is consumed in a variety of traditional forms, such as tofu (bean curd), doufugan (dried bean curd), doujiang (soy milk), tempeh (fermented bean cake), and miso (fermented bean paste). The daily per capita consumption of soybean in east Asia ranges from 12 to 36 g depending on the study (Fukutake et al., 1996; Holt, 1998; Khor, 1997). Even as the standard of living has improved significantly in this part of the world since the mid-1950s and animal-derived protein has become more accessible, soybean continues to be an important food crop. In contrast, in the United States, soybean was not grown on a large scale until World War II, and then only as a result of the search for alternative vegetable oils. Soybean used for human consumption was mostly limited to certain ethnic minorities at that time. However, since the mid-1990s, the food consumption of soybean has increased dramatically from approximately $900 million in the early 1990s to $3,100 million in 2001 (data from the United Soy Board). In North America and western Europe, soy protein is more typically consumed as a highly flavored soymilk, in meat replacements, or as a soy protein isolate, which can be added to a variety of foods. Among the many reasons for the phenomenal growth of the soy foods market, the perceived health benefits of soy and soy-related food products is the most important factor. Epidemiological studies have long revealed striking differences in the occurrence of hormone-dependent cancers between east Asian and Western populations. For example, the incidence of breast cancer is approximately six-fold lower in east Asia than in the United States, and prostate cancer rates are 12-fold lower (Messina, 1999a). These differences must arise from multiple factors, such as genetics and lifestyles. However, many studies suggest that dietary differences, particularly in the consumption of soybean, are one of the major contributors to the prevention of certain cancers in Asian populations. More specifically, one of the unique components of soybean that might play a vital role in health benefits is the isoflavones. Isoflavones are a group of diphenolic secondary metabolites produced by a limited number of higher plants. Although there are at least 22 families of plants that produce and accumulate isoflavones (Dewick, 1993), they occur most frequently in the Papilionoideae subfamily of the Leguminosae.

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Isoflavonoids are compounds derived from the basic 3-phenylchroman backbones of isoflavones by various modifications, such as methylation, hydroxylation, or polymerization. These modifications lead to simple isoflavonoids, such as isoflavanones, isoflavans, and isoflavanols, as well as more complex structures, such as rotenoids, pterocarpans, and coumestans (Dewick, 1993). In soybean, the three major types of isoflavones are daidzein, genistein, and glycitein (Fig. 1). The amount of each isoflavone in soybean seeds varies significantly, with the ratio of daidzein:genistein:glycitein typically being 4:5:1 (Wang and Murphy, 1994b). Most isoflavones in soybean seeds are conjugated with glucose or malonyl-glucose at the C7 position (Fig. 1). Acetyl-glucose

Figure 1 Structure of common isoflavones, estrodiol, and conjugates. (A–H) Genistein, daidzein, glycitein, glyceollin I, coumestan, estrodiol, genistin (glucose conjugate), and malonyl-genistin.

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conjugates have been detected, but mostly in processed or fermented soybean products, which suggests that they may be degradation products of malonylglucose conjugates (Reinli and Block, 1996). Like many conjugated flavonoid compounds, the conjugated isoflavones are stored in vacuoles and are immobile without enzymatically removing the conjugated moieties. Among common edible legumes, soybean contains the highest level of isoflavones, which is more than 100-fold higher than many other legumes (Table I). The physiological function of isoflavones in humans and animals continues to be the subject of intense investigation. As a glimpse of the breadth of public interest to this subject, a keyword search of “isoflavone” in Medline returned 3701 references as of February 2004. Previous reviews have covered the health Table I List of Isoflavone Content in Common Legumesa Legumes Kidney beans Navy beans

Isoflavones (mg/100 g) 0.06 0.21

Pinto beans

0.27

Broad beans Chickpeas

0.03 0.10

Cowpeas

0.03

Lentils

0.01

Lima beans

0.03

Mung beans

0.19

a

Reference Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998) Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998)

Legumes

Isoflavones (mg/100 g)

Peanuts

0.26

Peas

2.42

Pigeon peas

0.56

Reference Franke et al. (1995); Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998) Franke et al. (1995); Mazur et al. (1998)

Soybean, Korea

144.99

Choi et al. (1996)

Soybean, Japan

118.51

Soybean, Taiwan

59.75

Franke et al. (1995); Wang and Murphy (1994a) Franke et al. (1995)

Soybean, U.S. food quality

Franke et al. Soybean, (1995); Mazur U.S. et al. (1998) commodity

128.35

153.40

Franke et al. (1995); Mazur et al. (1998); Wang and Murphy (1994a,b) Eldridge and Kwolek (1983); Franke et al. (1995); Wang and Murphy (1994a)

Data adopted from USDA—Iowa State University Database on the Isoflavone Content of Foods, Release 1.3 – 2002. http://www.nal.usda.gov/fnic/foodcomp/Data/isoflav/isoflav.html).

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benefits of isoflavones extensively and thus are not discussed in detail here (Davis et al., 1999; Messina, 1999b; Messina et al., 1994; Nestel, 2003; Setchell and Cassidy, 1999; Taylor, 2003; Watanabe et al., 2003). In summary, the health benefit claims can be grouped into four main categories. 1. Isoflavones may reduce the occurrences of certain types of cancers. In vitro, animal and epidemiological data have established a relationship between isoflavone intake and breast, prostate, and colon cancer occurrence. Inhibition of tyrosine kinases and DNA topoisomerases by isoflavones may contribute to cancer preventions (Messina et al., 1994). 2. Isoflavones may reduce postmenopausal symptoms. Many animal and human studies have evaluated the health effects of isoflavones on menopause-related symptoms and diseases related to menopause/aging. Data are inconclusive regarding whether the observed health effects in humans are attributable to isoflavones alone or to isoflavones plus other components in whole foods. Although some data seem to support the efficacy of isoflavones in reducing the incidence and severity of hot flashes, many studies have not found any difference between isoflavone recipients and controls. Still, the consensus opinion of the North American Menopause Society concludes that foods or supplements that contain isoflavones have some physiologic effects (Taylor, 2003). Since the discovery of increased cancer risks associated with estrogen-based hormone replacement therapy, the use of isoflavones as an alternative for menopausal women has received renewed public and scientific interest (Albertazzi and Purdie, 2002; Barnes, 2003). 3. Isoflavones may prevent coronary heart disease by reducing low-density lipoprotein (LDL) and increasing high-density lipoprotein (HDL). In 1999, the Food and Drug Administration (FDA) approved a health claim that “diets low in saturated fat and cholesterol that include 25 g of soy protein a day may reduce the risk of heart disease” that can be included on packages containing at least 6.25 g of soy protein per serving. It remains the only health claim associated with soybean that has been approved by the FDA. However, recent reviews suggest that soy protein may have more of a significant hypocholesterolemic effect than isoflavones, especially in humans (Demonty et al., 2003). In fact, one study has shown that proteins from other isoflavone-poor legumes can also reduce cholesterolemia, at least in rats (Sirtori et al., 2004). 4. Isoflavones may have positive effects on other physiological processes such as neurobehavioral activities. With the well-known significance of estrogens in neuron and brain functions, studies have started on the neurobehavioral effects of isoflavone consumption in animals and humans (Lephart et al., 2002).

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Despite wide-ranging efforts, the exact nature of the function and mode of action(s) of isoflavones are still not clear. Most investigators appear convinced that the molecular structure of isoflavone, which mimics the hormone estrogen, drives at least part of their physiological functions (Fig. 1). Therefore, many isoflavonoids are commonly categorized as “phytoestrogens.” Indeed, isoflavones can be a ligand of estrogen receptors (Kuiper et al., 1998). The function of isoflavone, however, appears to be both agonistic and antagonistic of estrogen depending on the tissues (Doerge and Sheehan, 2002). It is necessary to emphasize that not all studies demonstrate that isoflavone intake is correlated with health benefits. In fact, a significant portion of research suggests that even some well-known health claims are hard to prove under defined experimental conditions. Like many other nutrient supplements, current understanding of the health benefits derived from isoflavone consumption is based on the meta-analysis of extensive literature, which summarizes the majority of the research carried out on a specific subject. Most importantly, additional research is required to address the molecular nature of the function of isoflavones in animals and humans. Although the health benefits of isoflavones are generally accepted, they are not without controversy. Some observations and experiments have even demonstrated adverse effects under specific conditions (Doerge and Sheehan, 2002). For example, during the early 1980s, when a group of cheetahs at the Cincinnati Zoo were fed a soy-based diet, all of the females became sterile. Other cheetahs of the same family that remained in South Africa and were fed animal-derived protein reproduced normally (Setchell et al., 1987). Later it was discovered that when zoos in North America switched to soy-based diets for cheetahs during the same period, less than 10% of adult females produced live cubs, compared with 60–80% in other countries, suggesting isoflavones in the soy protein may have had a dramatic effect on some carnivores’ reproductive systems. One particular area in which isoflavones have stirred public concern is soy-based infant formula. Approximately 7% of infants born in the United States are lactose intolerant, thus requiring formula that is not milk based. However, due to various reasons, about 25% of the infant formula sold in the United States is soy based (Mendez et al., 2002). When an infant consumes 8 ounces of soy formula, his or her blood isoflavone level can increase up to 22,000-fold, a much higher increase than in adults because of the infant’s lower body weight (Irvine et al., 1995). As a result, the public has been left to ponder the long-term effects of isoflavone on child development. On June 9, 2000, the ABC news program “20/20” reported a story “The Dark Side of Soy” that emphasized the role of soy-based infant formula in promoting the early onset of puberty. More recently,

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Strom et al. (2001) reported the results of a long-term study in which 248 individuals fed soy formula and 563 individuals fed cow milk formula during infancy and now between the ages of 20 and 34 were examined. They concluded that exposure to soy formula does not appear to lead to different general health or reproductive outcomes than exposure to milk formula. Further long-term studies need to be carried out. In the meantime, it is clear that developing an isoflavone-null soybean, in addition to a high-isoflavone soybean, may have a significant economic outcome for soy farmers and industries. In addition to concerns about isoflavone intake for infants, there are concerns surrounding the safety levels of isoflavones, especially when isoflavones are taken in relatively pure form as a food supplement (Barnes, 2003). However, the levels under discussion are almost certainly beyond the levels that plants can biologically synthesize (Munro et al., 2003), as discussed in this review.

II. BIOLOGICAL FUNCTIONS OF ISOFLAVONOIDS IN PLANTS The function of isoflavones in plants is somewhat better understood than the effects of their consumption in animals. Two of the best-studied functions involve plant–microbe interactions: defense and symbiosis. In defense responses, isoflavones are involved in phytoalexin production. Phytoalexins are a group of chemically diverse, low-molecular mass natural products that possess antimicrobial and/or antiherbivore activities. They are the main chemical compounds plants deploy to combat pathogens and disease (Dixon et al., 1995; Graham, 1995; Hammerschmidt, 1999). Different families of plants often produce different types of phytoalexins. Many leguminous plants synthesize isoflavonoid phytoalexins. Isoflavones themselves have antimicrobial effects when tested in vitro (Graham and Graham, 1996). However, the more potent phytoalexins are other isoflavonoids that are derived from isoflavones, such as coumestans and pterocarpans (Hammerschmidt and Dann, 1999; Heath, 2000). Generally, phytoalexins are not detectable in healthy tissue. They are produced by cells immediately adjacent to infected sites and accumulate in dead and dying cells within this localized region. These compounds are synthesized rapidly after infection due to the de novo activation of secondary metabolic pathways, which divert primary metabolic precursors into the production of phytoalexins. In soybean, phytoalexins known as glyceollins increase drastically within hours of elicitor treatment (Graham, 1991, 1995). Analyses of the temporal and spatial distributions of induced

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glyceollins suggest a complex regulation network that controls the hydrolysis of conjugated daidzein pool, de novo synthesis of isoflavones and glyceollins, and the establishment of competency in neighboring cells (Graham and Graham, 1994, 2000; Guo et al., 1998). As part of the hypersensitive response, the increased production of isoflavonoids is correlated with increased disease resistance (for reviews, see Dixon, 2001; Dixon and Paiva, 1995; Mansfield, 2000). However, little molecular data exist to explain how isoflavonoids inhibit a microbial invasion. Symbiosis is the intimate association of two dissimilar organisms. Legumes and symbiotic soil rhizobia communicate using small diffusible molecules (for reviews, see Dixon et al., 1996; Gualtieri and Bisseling, 2000; Pueppke, 1996). The signal molecules that plants excrete from roots are flavonoids and isoflavonoids, which are chemotaxic to rhizobia and other microbes (Barbour et al., 1991; Dakora, 2000). When rhizobia encounter these compounds, the nodD protein in the bacterial membrane binds them and transcriptionally activates the nod operons (Pueppke, 1996; Smit et al., 1992). The specific binding of nodD with particular flavonoids/ isoflavonoids is the main determinant of host specificity of rhizobia (for a review, see van Rhijn and Vanderleyden, 1995). The proteins encoded by the nod operons synthesize and release a group of lipo-chitooligosaccharides called Nod factors. These compounds can induce a series of physiological changes in plants that eventually lead to nodule morphogenesis and N2 fixation (Downie and Walker, 1999; Pueppke, 1996). Among the biological effects of Nod factors, isoflavonoid biosynthesis is highly induced, presumably creating positive signal feedback cycles between the plant and the microbe (Recourt et al., 1991; Schmidt et al., 1994; van Brussel et al., 1990). This feedback response is essential in establishing a symbiotic relationship because other plants may also secrete flavonoid compounds from the roots, but only legumes distinguish themselves by responding to Nod factors with increased flavonoid/isoflavonoid secretion. The exact mechanisms and pathways that respond to Nod factors are not clear, although a receptor-mediated signal transduction pathway may exist (Bloemberg and Lugtenberg, 2001; Bonfante et al., 2000; Gualtieri and Bisseling, 2000; Stougaard, 2001; van Rhijn and Vanderleyden, 1995). In experiments using Arabidopsis thaliana, two nitrogen-fixing bacteria, Azorhizobium caulinodans and Herbaspirillum seropedicae, colonized the roots by entering through lateral root cracks at the junction of primary and lateral roots. This colonization was significantly enhanced by the application of isoflavone daidzein and genistein (Gough et al., 1997). It is intriguing to note that these bacteria regularly colonize rice and wheat roots as well (Cocking et al., 1995).

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III. TARGETS OF ISOFLAVONE ENGINEERING Due to the traditional limited consumption of soybean in Western cultures (currently about 2 g per capita per day; Reinli and Block, 1996), the idea of increasing isoflavone concentrations to provide health benefits has gained widespread interest in recent years (Dixon and Steele, 1999; Forkmann and Martens, 2001). If a higher isoflavone soybean exists, people may get sufficient healthful compounds without drastically changing their dietary habits. In addition, the isoflavone levels in soybean vary significantly among different varieties. Even for the same variety in the same field, different crop years might bring about more than a threefold difference in isoflavone levels (Wang and Murphy, 1994a). The food industry requires stable and predictable isoflavone contents in soybean-derived products if its health benefits are to be a selling point (Head et al., 1996). However, reducing or eliminating isoflavones in soybean may be valuable for certain sectors of soy food markets, such as infant formulas. Some of the activities attributed to isoflavones, such as inhibition of tyrosine-specific protein kinases, are specific to genistein (Akiyama et al., 1987). The transcriptome of human gut epithelial cell lines challenged with either daidzein or genistein was characterized using microarray technology, and this characterization shows further evidence that the biochemical activities of genistein and daidzein are distinct (Gillies et al., 2003). Independent and, in some instances, opposite responses are found, although there is some degree of overlap in the transcriptomes. Because of this, at times, it may be desirable for some individuals to consume genistein and not daidzein and thus there is a desire to produce functional foods with altered ratios of isoflavones, i.e., the ratio of daidzein to genistein. The most desirable way to do this is to engineer soybeans that do not produce daidzein. Thus, in addition to year-to-year and location-to-location consistency, both the total content and the composition or ratios of isoflavones are targets of metabolic engineering. It is difficult to define specific benchmarks for each of the targeted areas because different populations assign different values to the products. There are two approaches toward these engineering goals: traditional breeding and molecular metabolic engineering. Traditional breeding currently focuses on biochemical and genetic analysis, including quantitative trait locus (QTL) analysis, to determine the factors that contribute to isoflavone production and accumulation, as well as screening for extraordinary isoflavone phenotypes from different varieties and mutants. This review, however, is dedicated to the second approach, which utilizes recombinant DNA technology to modify isoflavone biosynthesis. As discussed

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later, the molecular metabolic engineering approach has been successful in changing isoflavone content and composition. One significant advantage of metabolic engineering over traditional breeding is the prospect of engineering nonlegume food crops to produce isoflavones. As part of the learned cultural differences toward food preferences, many soy foods currently on the market have an unpleasant taste to most mainstream consumers in North America and western Europe. To overcome this major obstacle, engineering isoflavone biosynthesis in nonlegume plants, such as maize (Zea mays) or rice (Oryza sativa), may provide an alternative source of dietary isoflavones that are more acceptable. At the same time, the enhanced nutritional value of the engineered crops will bring additional value to farmers and industries. In addition to modifying plants for enhanced nutritional value, it may also be desirable to modify plants to alter plant–microbe interactions. These efforts will likely be distinct from efforts to enhance nutritional value as they are likely to require the accumulation of isoflavones in novel spatial and temporal patterns, i.e., where and when the plant–microbe interactions occur. Previous research demonstrates that the production of foreign phytoalexins in transgenic plants can dramatically enhance pathogen resistance (Coutos-Thevenot et al., 2001; Hain et al., 1990, 1993; Hipskind and Paiva, 2000; Sparvoli et al., 1994). For example, heterologous expression of stilbene synthase results in accumulation of the phytoalexin resveratrol in both tobacco (Nicotiana tobaccum) and alfalfa (Medicago sativa) that improves disease resistance toward the fungal pathogens Botrytis cinerea and Phoma medicaginis (Hain et al., 1993; Hipskind and Paiva, 2000). These experiments indicate that native pathogens may have difficulty in detoxifying novel phytoalexins. While isoflavones are not typically potent phytoalexins, other simple flavonoids, such as maysin, provide a high level of protection against certain pathogens (Lee et al., 1998) and it remains possible that isoflavones expressed in certain tissues may be of significant value. For instance, the expression of isoflavones in maize silks may provide protection against silk-burrowing earworms. Additionally, engineering isoflavone production in nonlegume plants is a necessary precondition to engineering of more derived isoflavone phytoalexins with greater toxicity. In addition to providing plant protection to disease and herbivory, it is possible that isoflavones may also enhance symbiosis between roots and rhizobial bacteria. Engineering plants to have the ability to fix nitrogen has long been a desire of plant scientists, but given the large number of genes necessary for nodulation, it remains beyond our current technological ability. However, some rhizobia are able to fix nitrogen as free-living organisms. If these bacteria are associated with a plant root, the levels of nitrogen fixation are sufficient to be of value (Cocking et al., 1995). Previous work has shown that specific flavonoids, including daidzein, promote intercellular

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root colonization of Arabidopsis. It is an intriguing possibility that the accumulation of isoflavones in the root of nonlegume plants may lead to increased colonization by rhizobia, leading to nitrogen fixation. While engineering crops to produce isoflavones may not only enhance the nutritional value of the crop but also increase disease resistance, it should be noted that current attempts to engineer the isoflavone levels in soybean have all used seed-specific expression systems to limit the pleotropic effects of altering secondary metabolite biosynthesis.

IV. THE PATHWAY LEADING TO ISOFLAVONE BIOSYNTHESIS Isoflavonoids are synthesized from a branch of the phenylpropanoid pathway (Fig. 2). The phenylpropanoid pathway is ubiquitous throughout the plant kingdom and, in addition to isoflavonoids, produces a variety of phenolic compounds, such as lignans, lignins, flavones, flavonols, condensed tannins (also known as proanthocyanidins), and anthocyanins. Because flower color is such an intriguing attraction to humanity and colored compounds serve as visual markers for analysis, the phenylpropanoid pathway is by far the best-studied secondary metabolic pathway. For years, genetic and biochemical studies, particularly radioisotope-labeled precursor-feeding analyses, have revealed many steps and enzymes involved in flavonoid biosynthesis. Starting from the amino acid phenylalanine, the enzyme phenylalanine ammonia-lyase (PAL) removes the amine group from the amino acid and produces cinnamic acid. The first of several cytochrome P450 monooxygenases in this pathway, cinnamic acid 4-hydroxylase (C4H), adds a hydroxyl group to form p-coumarate. The enzyme 4-coumarate:coenzyme A ligase (4CL) further activates the p-coumarate by attaching a CoA at the three-carbon side chain. Next, chalcone synthase (CHS) carries out the condensation of p-coumaroyl-CoA with three molecules of malonyl-CoA to form the C15 flavonoid skeleton. In most species, this compound is naringenin-chalcone (4,2,4,6´-tetrahydroxychalcone). The chalcone synthesized by CHS can be converted to the flavanone naringenin (5,7,4´-trihydroxyflavanone) by the enzyme chalcone isomerase (CHI). Naringenin is one of the shared substrates between flavonoid and isoflavonoid pathways. Further modifications of naringenin lead to the production of various flavonoid compounds. The most common reaction using naringenin as a substrate is the addition of a hydroxyl group at the C3 position to form dihydrokaempferol as catalyzed by flavanone 3-hydroxylase (F3H), a 2-oxoglutartate-dependent dioxygenase (Deboo

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Figure 2 Outline of the phenylpropanoid pathway (including a list of enzymes and their abbreviations).

et al., 1995). The modification at the C3 position is essential for the production of anthocyanins and condensed tannins, which requires enzymes including dihydroflavonol reductase (DFR), leucoanthocyanidin dioxygenase (LDOX), UDPG-flavonoid glucosyl transferase (UFGT), and others. There are several other enzymes that utilize naringenin as a substrate. In maize, there are five known enzymes that use naringenin. In addition to F3H, maize flavone synthase (FNSII), a cytochrome P450 monooxygenase, uses naringenin to produce flavones. The flavonoid 3´-hydroxylase (F3´H) and flavonoid 3´5´-hydroxylase (F3´5´H) both modify naringenin with additional hydroxylations on the B ring, which are the precursors of the flavone maysin. DFR can also directly use naringenin as a substrate to initiate the tissue-specific production of phlobaphenes (Grotewold et al., 1994).

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Although the activity of all these enzymes has been previously observed, the exact nature of how these enzymes partition the common flavanone substrate is not clear. The flux of the substrate toward each pathway has not been measured. For metabolic engineering of isoflavone synthesis in nonlegume plants, naringenin is a critical metabolite because heterologously expressed IFS must directly compete with other endogenous enzymes for this substrate. Understanding the mechanism and regulation of pathway branching will be essential for metabolic engineering projects. In species that synthesize isoflavones, the enzyme isoflavone synthase (IFS), another cytochrome P450 monooxygenase, acts as the key metabolic entry point for the formation of all isoflavonoids. This enzyme plays two roles: it diverts naringenin formed by CHI into genistein production and, in conjunction with another legume-specific enzyme, chalcone reductase (CHR), forms daidzein. In this case, CHR, CHS, and CHI work in concert to produce isoliquiritigenin and then liquiritigenin, which is the precursor for daidzein. The IFS enzyme is discussed in detail later. Both daidzein and genistein can be conjugated sequentially with glucosyl and malonyl side chains and sequestered in vacuoles. The glycitein biosynthetic pathway is still largely unknown, although it has been suggested that the flavanone liquiritigenin is hydroxylated by flavanone 6-hydroxylase (F6H) to serve as a precursor (Latunde-Dada et al., 2001). It is not known whether methylation precedes or follows isoflavone production. Isoflavones can also be further metabolized to downstream isoflavonoids, such as pterocarpanoids, by a series of legume-specific enzymes. The pterocarpanoid pathway has been studied most extensively in legumes such as Medicago truncatula and alfalfa. In these plants, an isoflavone O-methyltransferase (IOMT) adds a methyl group to the 4´ position (Akashi et al., 2003). This modification occurs prior to isoflavone synthesis (Akashi et al., 2000). Similar pathways for the synthesis of pterocarpans exist in other legumes, including chickpea (Cicer arietinum), pea (Pisum sativum), licorice (Glycyrrhiza echinata), and soybean (Barz and Welle, 1992). In soybean, pterocarpans, known as glyceollins, are synthesized through a well-defined pathway for which many of the genes have been cloned. Daidzein is hydroxylated by isoflavone hydroxylase (I2´H) to form 2´-hydroxydaidzein. I2´H has been cloned from chickpea and alfalfa, and ESTs with high homology exist from other legumes, including soybean (Akashi et al., 1998; Liu et al., 2003). 2´-Hydroxydaidzein is then reduced by isoflavone reductase (IFR) to form 7,2´-dihydrodaidzein. A gene encoding IFR has also been cloned from alfalfa, and ESTs with high homology from other legumes have been found (Paiva et al., 1991). However, it is important to note that homologous enzymes must be characterized biochemically before reliable predictions of gene functions can be made.

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The dihydrofuran ring was originally thought to be formed by a pterocarpan synthase, but more recent work shows that this is in fact catalyzed by two enzymes that have been identified and characterized from alfalfa: vestitone reductase (VTR) and 7,2´-dihydroxy-4´-methoxyisoflavanol dehydratase (DMID) (Guo et al., 1994). This compound, 3,9-dihydroxypterocarpan, is then hydroxylated by pterocarpan 6a-hydroxylase to form 3,6a,9-trihydroxypterocarpan. This reaction is catalyzed by another cytochrome P450, and the gene encoding this protein was cloned from induced soybean (Schopfer et al., 1998). Finally, a prenyltransferase catalyzes the addition of a prenyl group and the resulting compound is cyclized by the enzyme glyceollidin cyclase to form the glyceollin isomers I, II, and III (Welle and Grisebach, 1988). Genes encoding the enzymes that catalyze the last two steps have yet to be characterized. Most of the extensively modified isoflavonoid phytoalexins, such as pterocarpans and coumestrols, are derived from 5-deoxyisoflavones (such as daidzein). Surprisingly, the exact function of genistein (5-hydroxyisoflavone) in soybean disease resistance and other plant–microbe interactions is not very clear, even if it makes up approximately 50% of isoflavone contents in seeds. Although kievetone, a prenylated genistein phytoalexin, exists in a few legumes, including garden bean (Phaseolus vulgaris) and lupines (Lupinus albus), it has not been discovered in soybean (Goossens et al., 1987). It is not clear to what extent the transport of phenylpropanoid compounds through different plants tissues affects their eventual accumulation. Previous reports suggest that the flavonoids that accumulate after UV-light irradiation and the furanocoumarin induced by fungal pathogens are produced by the specific cells exposed to the induction instead of being transported from other tissues (Asthana et al., 1993; Siegrist et al., 1998). However, more recent work suggests that while seeds are the site of much isoflavone synthesis, some of the accumulation of isoflavones is due to transport from other plant tissues, including maternal tissues (Dhaubhadel et al., 2004). These unknowns present an additional layer of complexity to metabolic engineering projects. In many other cases of metabolic engineering, controlling the degradation or catabolism of the targeted products is very important. As an example, free lysine is degraded by lysine-ketoglutarate reductase and saccharopine dehydrogenase, and the development of high-lysine maize was hindered until these enzymes were cloned and their activities understood (Epelbaum et al., 1997). However, several reasons argue against the necessity for this approach in isoflavone engineering: in soybean seeds, the majority of the isoflavonoids produced are isoflavones. The downstream products only accumulate to high levels under stress conditions. It may also significantly reduce the agronomic values if the conversion of isoflavones to other phytoalexins is blocked, thus weakening the disease resistance of the crop.

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However, a greater understanding of the biological fate of isoflavones may necessitate the reevaluation of this argument.

V. THE ENTRY POINT ENZYME: ISOFLAVONE SYNTHASE A. THE DISCOVERY OF ISOFLAVONE SYNTHASE IFS is the first committed enzyme in the isoflavone pathway and converts flavanone substrates to isoflavone products. In 1984, Grisebach’s group at the University of Freiburg in Germany first reported the enzyme activity in elicitor-treated soybean suspension cultures (Hagmann and Grisebach, 1984; Kochs and Grisebach, 1986). In an in vitro microsomal assay using the (radioisotope-labeled (2S)-naringenin substrate, the group was able to demonstrate that intramolecular aryl-migration is catalyzed by a NADPH- and oxygen-dependent enzyme located at the endoplasmic reticulum (ER) membranes. Because specific cytochrome P450 monooxygenase inhibitors such as carbon monoxide and ancymidol could inhibit this enzyme, IFS was thought to be a cytochrome P450 monooxygenase. Like many other cytochrome P450 monooxygenase enzymes, the lipophilic nature and relative low abundance of the protein hindered the isolation and identification of IFS. There was approximately 16 years between the identification of IFS as a cytochrome P450 monooxygenase and the eventual cloning of its DNA sequence. When the gene was finally cloned, it was reported by three independent groups, all of whom took a functional genomics approach to identifying the gene. Dixon’s group at the Noble Foundation in Oklahoma screened two cytochrome P450 monooxygenases, selected from soybean EST libraries, using microsomes purified from insect cells carrying a baculovirus expression vector (Steele et al., 1999). One of the gene products was able to convert liquiritigenin and naringenin to daidzein and genistein, respectively. The gene was named 2-hydroxyisoflavanone synthase (2-HIS). Based on sequence homology and cytochrome P450 monooxygenase nomenclature, it was placed in the CYP93C subfamily of cytochrome P450s. The sequence revealed all the features of a functional cytochrome P450 monooxygenases, including the oxygen binding “I” helix, the heme-binding motifs, and the conserved “PERF” domain. A Northern blot analysis suggested that the homologs of this gene in alfalfa were highly induced upon elicitor treatment in suspension cultures. Ayabe’s group at Nihon University in Japan reported a sequence, also a member of the CYP93C subfamily, that encoded 2-hydroxyisoflavanone synthase activity from licorice (Akashi et al., 1999). Using degenerate

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primers that targeted conserved cytochrome P450 monooxygenase domains, the group isolated eight cytochrome P450 monooxygenase genes from elicitor-induced licorice cultures (Akashi et al., 1999). When expressed in yeast carrying a cytochrome P450 reductase, one of the genes produced a protein that converted flavanone substrates to isoflavones. Radioisotope-labeled thin layer chromatography (TLC) and liquid chromatography-mass spectrometry (LC-MS) confirmed that this enzyme could synthesize 2-hydroxyisoflavanones and eventually isoflavones. An additional report of the discovery of IFS genes came from researchers at the DuPont Company (Jung et al., 2000). Starting from the DuPont EST database, the group focused on disease-induced cytochrome P450 monooxygenase genes. Using a similar yeast expression system as described earlier, they identified two highly homologous soybean EST sequences that encoded proteins that exhibited IFS activity as confirmed by gas chromatography-mass spectrometry (GC-MS). Subsequently, they cloned 11 IFS genes from nine different species using degenerate primers. These sequences included two sequences from Beta vulgaras (sugar beet), which is not a legume plant but had been previously reported to accumulate isoflavones (Geigert et al., 1973). Additionally, the genomic sequence of the two soybean IFS genes was cloned using polymerase chain reaction. One intron was found at the same location of both genes. The in vitro identification of IFS was further confirmed when the soybean IFS was expressed in Arabidopsis and the heterologously expressed IFS was able to utilize the endogenous naringenin accumulated during the Arabidopsis flavonoid biosynthesis and convert it to the isoflavone genistein. Currently, there are 30 IFS sequences in public databases, all of which belong to the CYP93C subfamily of cytochrome P450 monooxygenases (Table II).

B. THE MODE

OF

ACTION

OF ISOFLAVONE

SYNTHASE

IFS is an intriguing enzyme because it catalyzes at least two unusual reactions with one protein: a hydroxylation reaction and an intramolecular aryl migration reaction. Because crystallization of a membrane-bound protein is notoriously difficult, the extensive efforts to resolve the IFS structure have not yet been successful. Without a definitive structure, the exact mechanism of this enzyme reaction is still speculative. It has been proposed that the flavanone is first converted to 2-hydroxyisoflavanone and then to isoflavone by three steps (Hashim et al., 1990). First, a radical at the C3 is generated and then an intramolecular rearrangement moves the aryl group from C2 to C3 and leaves a hydroxyl group still attached to C2. Finally, another enzyme, named isoflavanone dehydratase, then converts 2-hydroxyisoflavanone to isoflavone (Fig. 3).

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Table II List of Cloned IFS Genes in GenBank (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi? db¼Nucleotide) and P450 Database (http://drnelson.utmem.edu/CytochromeP450.html) GenBank number

Species

P450 (CYP)

AF022462 AF195799

Glycine max (soybean) G. max (soybean)

93C1 93C1v1

AF135484, AB023636 AJ243804 AF089850a

G. max (soybean) Glycyrrhiza echinata (licorice) Cicer arietinum (chickpea) Glycine max (soybean)

93C1v2 93C2 93C3 93C4

AF195812 AF195806 AF195807 AF195808 AF195809 AF195801 AF195802 AF195800 AY253284a

G. max (soybean) Vigna radiata (mung bean) V. radiata (mung bean) V. radiata (mung bean) V. radiata (mung bean) Medicago sativa (alfalfa) M. sativa (alfalfa) M. sativa (alfalfa) Trifolium pratense (red clover)

93C5 93C6v1 93C6v3 93C6v3 93C6v4 93C7v1 93C7v2 93C8 93C9

AF195810 AF195811 AF195814 AF195815 AF195817 AF195816 AF195805 AF195804 AF195812 AF195803 AF195813 AB024931

T. pratense (red clover) T. pratense (red clover) T. repens (white clover) T. repens (white clover) Beta vulgaris (sugar beet) B. vulgaris (sugar beet) Lens culinaris (lentil) L. culinaris (lentil) Pisum sativum (pea) Vicia villosa (hairy vetch) Lupinus albus (white lupine) Lotus japonicus P. sativum (pea)

93C9v1 93C9v2 93C10v1 93C10v2 93C11v1 93C11v2 93C12 93C13 93C14 93C15 93C16 93C17 93C18b

AY167424a

Medicago truncatula

AF462633a

Pueraria montana var. lobata

Reference Siminszky et al. (1999) Akashi et al. (1999); Jung et al. (2000) Steele et al. (1999) Akashi et al. (1999) Overkamp et al. (2000) Wu and Verma, direct submission Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Kim et al. direct submission Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Jung et al. (2000) Shimada et al. (2000) Direct submission to P450 Butelli et al., direct submission Jeon and Kim, direct submission

a

Direct submission to GenBank. Direct submission to P450 database.

b

There is much experimental evidence supporting this hypothesis. It has been documented repeatedly that instead of isoflavone, the final product of the IFS enzyme is the 2-hydroxyisoflavanone, a compound not stable at

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Figure 3 IFS reaction scheme outline.

ambient conditions. Both liquiritigenin and naringenin were shown to become 2-hydroxyisoflavanones after incubating with IFS containing microsomes. For this reason, “2-hydroxyisoflavanone synthase” is a more accurate name for this enzyme than “isoflavone synthase.” An enzyme that catalyzes the dehydration of 2-hydroxyisoflavanone to isoflavone has been enriched to apparent homogeneity from Pueraria lobata (Hakamatsuka et al., 1998). The production of isoflavone from 2-hydroxyisoflavanone is most likely assisted by the homologs of this enzyme in other legumes. Based on the X-ray structure of the eukaryotic P450BM3 structure (Ravichandran et al., 1993) and the alignment of several CYP93 family cytochrome P450 monooxygenase proteins, including flavanone 2-hydroxylase (CYP93B1) and FNSII (CYP93B2), two amino acids in the IFS protein were identified that were thought to be involved in the aryl migration reaction (Sawada et al., 2002). When mutated, the resulting proteins produced largely (Ser310 to Thr) or only (Lys375 to Thr) 3-hydroxyflavanone instead of 2-hydroxyisoflavanone. When 3-hydroxyflavanone was fed to microsomes in vitro, IFS failed to convert it to 2-hydroxyisoflavanone. This suggests that 3-hydroxyflavanone is not a substrate for IFS. This further suggests that radical generation and aryl migration are catalyzed by different regions of the protein and that the reaction mechanism suggested by Hashim et al. (1990) is correct. Nonlegume plants accumulate isoflavone instead of 2-hydroxyisoflavanone when only the IFS gene is present even though the suggested reaction mechanism would suggest that 2-hydroxyisoflavanone should accumulate. It remains to be tested whether the autoconversion of 2-hydroxyisoflavanone to isoflavone occurs fast enough to prevent the former compound from accumulating in these plants or whether there is a general “flavonoid dehydratase” enzyme that carries out dehydration of multiple flavonoid/isoflavonoid compounds. Furthermore, there is no experimental evidence to exclude the possibility that IFS assists the conversion of 2-hydroxyisoflavone to isoflavone, perhaps at a much slower rate than the aryl migration reaction. A greater understanding of the IFS mechanism can lead to targeted enzyme engineering with enhanced IFS activities, which may be crucial for isoflavone pathway engineering across species. In the future, generating new

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cytochrome P450 monooxygenases may also produce unique phenolic compounds with special physiological and biological functions.

VI. OTHER KEY ENZYMES IN ISOFLAVONE BIOSYNTHESIS Many of the upstream phenylpropanoid pathway enzymes have been well characterized, including PAL, C4H, 4CL, CHS, and CHI. Two of the most important enzymes for any metabolic engineering attempts are CHI and CHR. CHI is important because it catalyzes a reaction that is a branch point between where the pathway diverts its substrates toward flavonoid and isoflavonoid production. CHR, which is not found in nonlegume species, is responsible for the synthesis of 6´-deoxychalcone, which is the precursor for daidzein and glycitein. Furthermore, the majority of the phytoalexins are derived from 6´-deoxychalcone instead of 6´-hydroxylchalcone, making CHR crucial for metabolic engineering directed toward improved disease resistance. Additional structural enzymes are important for pathway engineering but they are not covered in detail here.

A. CHALCONE ISOMERASE CHI (EC 5.5.1.6) catalyzes the stereospecific isomerization of chalcones into corresponding (2S)-flavanones (Fig. 4). Some chalcones in aqueous solution can be spontaneously isomerized into (2RS)-flavanones with a fairly high turnover rate (Jez et al., 2000b). The in vitro enzyme kinetic assay indicates that CHI operates at the upper limit of the turnover rate for all enzymes, approaching the diffusion limit. CHI ensures that the reaction produces only (2S)-flavanones, which are the biological substrates for downstream enzymes. The only functional CHI gene in Arabidopsis (tt5) is essential for the biosynthesis of anthocyanin and other flavonoid compounds (Shirley et al., 1992).

Figure 4

CHI reaction scheme.

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In all higher plants, isomerization of naringenin-chalcone into naringenin by CHI occurs rapidly. However, the conversion of 2´,4,4´-trihydroxychalcone (isoliquiritigenin) to 7,4´-dihydroxylflavanone (liquiritigenin), a reaction occurring mostly in legumes, has relatively slower kinetics because of the intramolecular hydrogen bond in the substrate molecule (Jez et al., 2002). CHI enzymes isolated from nonlegume plants are unable to use isoliquiritigenin as a substrate. Therefore, CHIs are classified into two types and their distribution is highly family specific. Type I CHIs are found in both legumes and nonlegumes and isomerize only naringenin-chalcone to naringenin. Type II CHIs are found exclusively in leguminous plants and have activities toward both naringenin-chalcone and isoliquiritigenin, yielding naringenin and liquiritigenin, respectively. The genes that encode both types of CHIs have been cloned from various plant species (Kimura et al., 2001; Shimada et al., 2003), and the deduced amino acid sequences within the same type of CHI shared high identity (>70%), while the identity between type I and II CHIs is only about 50% homologous. The antigenic cross-reactivity of the proteins and primary protein sequence suggests that the different substrate specificities of CHIs between leguminous and nonleguminous plants result from the different structures of CHI proteins. Furthermore, both type I and II CHIs are differentially regulated after elicitor treatment (Shimada et al., 2003). X-ray crystallography of an alfalfa type II CHI showed the stereo structure of the protein and revealed the dynamic reaction mechanism of the catalysis (Jez and Noel, 2002; Jez et al., 2000b, 2002): The substrate bound to the active site is forced to form a constrained configuration and is efficiently converted into the product by a general acid–base catalysis mechanism. The amino acid residues possibly affecting the accessibility of naringenin-chalcone and isoliquiritigenin at the active site cleft have been suggested, but the exact structural basis of substrate specificity of CHI is still unclear. The Arabidopsis CHI structure has been resolved and should help determine the structural constrains of the broad and narrow substrate specificity (Noel and Winkel-Shirley, personal communications). Considering potential enzyme interactions, e.g., the interaction of type I CHI with the flavonoid pathway and type II CHI with the isoflavonoid pathway, introducing specific CHIs may be one of the key factors for metabolic pathway engineering (see later).

B. CHALCONE REDUCTASE CHR belongs to the aldo-keto-reductase super family that catalyzes the NAD(P)H-dependent reduction of a variety of carbonyl compounds. All higher plants produce chalcones via the action of CHS, which synthesizes a

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tetraketide by condensing three molecules of malonyl-CoA sequentially to one molecule of the p-coumaroyl-CoA starter. CHR removes the hydroxyl group of the second malonyl-CoA, resulting in 6´-deoxychalcone. Earlier research demonstrated that CHR and CHS are transcriptionally coactivated. In an in vitro assay where purified CHR protein and CHS protein were added in a 2:1 ratio, 6´-deoxychalcone and 6-hydroxychalcone were produced in a 1:1 ratio (Welle and Schroder, 1992). It has been suspected that CHS and CHR form an enzyme complex that carries out the two reactions in tandem. However, colocalization and yeast two-hybrid assays so far have been negative, suggesting that the enzymatic association of the two proteins in vivo may be more complicated and may require additional protein factors. In addition, CHR and CHS proteins exist as multigene families in M. truncatula and soybean (Dixon et al., 2002). There are at least eight sequences from the M. truncatula EST database (TC78137, TC78138, TC82770, TC85519, TC85520, TC85521, BG586880, and AW774745; http://www.medicago.org/MtDB2/Queries/SimilarityDB2.html) that are homologous to CHR. These genes were determined to be homologs by querying the gene indices and selecting sequences with at least 50% similarity, on a DNA basis, to known genes. There are three sequences from the TIGR soybean gene index homologous to CHR (TC173540, TC180190, and TC192014; http://www.tigr.org/tigr-scripts/tgi/T_index.cgi? species¼soybean). There are also at least 13 CHS homologs in the M. truncatula database (TC76767, TC76768, TC76765, TC76884, TC79323, TC79835, TC83930, TC85138, TC85145, TC85146, TC85150, TC85169, and TC85174) and 10 CHS homologs in the soybean database (TC174579, TC175254, TC178994, TC179641, TC183485, TC189879, TC179880, TC190528, TC192493, and BI893708.). The large number of protein sequences would allow for a multitude of different combinations, making the prediction of specific interactions between CHS and CHR extremely difficult. The three-dimensional structure of Arabidopsis chalcone synthase is available (Jez et al., 2000a), but the structure of CHR has only recently been resolved (Noel, personal communications). This structural information will be useful in generating models for the putative CHS–CHR interaction. CHR is necessary for daidzein biosynthesis and, in soybean, for glycitein biosynthesis as well. Thus, engineering efforts targeted at CHR will be essential to control the ratio of isoflavone composition. In soybean, CHR expression needs to be silenced to produce low daidzein lines, and it may be necessary to overexpress CHR to produce larger amounts of daidzein either for nutritional purposes or as a precursor for phytoalexins. CHR is only found in legumes and thus to synthesize daidzein in nonlegume plants, the transformation of CHR genes is required. If the specific interaction between CHS and CHR is essential for producing 6´-deoxychalcone, additional

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“legume-specific” CHS may also need to be introduced for a high-level accumulation of daidzein in nonlegume plants.

VII. TRANSCRIPTIONAL AND POSTTRANSCRIPTIONAL REGULATION OF RELATED PATHWAYS The increased accumulation of flavonoids and isoflavonoids observed after fungal induction is mostly the result of transcriptional activation of biosynthetic genes (Weisshaar and Jenkins, 1998). Transcriptional regulation is therefore important for soybean and nonlegume plant metabolic engineering. As a general strategy, transcriptionally activating the upstream pathway may increase the flow of intermediates and provide more substrates. The transcriptional regulation of the phenylpropanoid and flavonoid pathways are among the most thoroughly analyzed regulatory pathways in plant systems (Fahrendorf et al., 1995; Ni et al., 1996; Weisshaar and Jenkins, 1998). In addition to tissue-specific expression, the phenylpropanoid pathway can be induced by various environmental factors, including both abiotic stress (such as high-intensity light, UV light, and nutrient deficiency) and biotic stress (such as pathogen attack and wounding). Thus various signal transduction pathways can eventually lead to phenylpropanoid pathway activation. The maize C1 gene regulates the tissue-specific biosynthesis of anthocyanin in the aleurone layers of the kernel by binding to a consensus cis element of the promoters of many phenylpropanoid pathway genes (Cone et al., 1986). Together with another transcription factor, R, C1 recognizes a conserved “CAACCACC” element and activates the transcription of the entire pathway (Grotewold et al., 2000; Sainz et al., 1997). A chimeric protein, CRC, consisting of the C1 DNA-binding domain, the complete R gene, and the C1 activation domain, is sufficient to drive anthocyanin production in maize and other plant species (Bruce et al., 2000). C1 belongs to the R2R3-Myb-like transcription family. In Arabidopsis, at least 145 R2R3-Mybs constitute the second largest transcription factor family (Kranz et al., 1998). Twenty-two subfamilies of Mybs have been identified. In animal systems, Mybs regulate essential cell functions such as cell cycle and cell differentiation; however, in plants the R2R3-Myb transcription factors have evolved to regulate diverse plant-specific processes, such as trichome development, ABA and GA hormone responses, and biotic/abiotic stress responses (Braun and Grotewold, 1999; Kranz et al., 1998; Meissner et al., 1999; Rabinowicz et al., 1999). Although most of these Myb-like transcription factors have not been functionally analyzed, the C1

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homologs form a distinct subfamily that specializes in regulating (activating or repressing) anthocyanin production in various species (Rabinowicz and Grotewold, 2000). For example, the C1 homolog in Arabidopsis, the PAP1 gene, activates anthocyanin synthesis in many tissues when it is overexpressed under a constitute promoter (Jin and Martin, 1999; Martin and Paz-Ares, 1997; Moyano et al., 1996). Some Myb-like transcription factors function as suppressors of the pathway. For example, Antirrhinum AmMyb308 and AmMyb330 not only inhibit the transcriptional activation of the phenylpropanoid pathway in Antirrhinum, but also inhibit the pathway activation in tobacco when introduced as transgenes (Tamagnone et al., 1998). Additionally, a group of defense-induced Myb-like transcription factors have been reported. They belong to a more diverse subfamily than the highly conserved C1 subfamily and play important roles in mediating the plant defense response (Lee et al., 2001; Sugimoto et al., 2000; Vailleau et al., 2002; Yang and Klessig, 1996). Because isoflavones are induced by plant defense mechanism, the prospect that this group of Myb-like genes may activate the isoflavonoid pathway in response to defense signals is intriguing. The promoters of many phenylpropanoid and flavonoid pathway genes have been cloned from various species. The common elicitor responsive cis elements, in addition to Myb-binding regions, have been identified (Hartmann et al., 1998; Lesnick and Chandler, 1998; Leyva et al., 1992; Loake et al., 1992; Terauchi and Kahl, 2000). For example, the H-box (CCTACC) and G-box (CACGTG) originally discovered on the bean CHS15 promoter are found in promoters of PAL and other defense-induced genes as well (Arias et al., 1993; Hatton et al., 1995). In addition to Myb-like proteins, other transcription factors also regulate this pathway in response to diverse signal transduction pathways. A basic helix–loop–helix transcription factor (tt8) was shown to activate the DFR and anthocyanidin reductase (BAN) gene in Arabidopsis (Nesi et al., 2000). The LIM protein family transcription factor Ntlim1 controls lignin biosynthesis in tobacco (Kaothien et al., 2002). A Ku-like transcription factor was shown to regulate the CHS genes in bean (Lindsay et al., 2002), and a bZIP family factor G/HBF1 activates CHS in soybean through phosphorylation of the transcription factor (Droge-Laser et al., 1997). Several breakthroughs have been made in the study of signal transduction pathways that lead to the activation of aforementioned transcription factors. Regulatory proteins containing WD40 repeats that are related to the b subunit of heterotrimeric G protein clearly play major roles in activating flavonoid-related Myb-like transcription factors. These proteins include AN11 from petunia (Sompornpailin et al., 2002) and TTG1 from Arabidopsis (Walker et al., 1999). AN11 is a cytoplasmic protein that regulates the Myblike transcription factor ANA, which in turn regulates flavonoid synthesis

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(Quattrocchio et al., 1999). TTG1 regulates flavonoid biosynthesis, trichome development, and root epidermal cell patterning through the Myb-like transcription factor glabrous1 (Walker et al., 1999). Another group of novel regulators of the flavonoid pathway is the WRKY family of transcription factors. The recently cloned Arabidopsis ttg2 gene, which contains two zincfinger domains typical of the WRKY family, shows a similar phenotype of ttg1 and regulates Myb-like transcription factors through transcriptional activation (Johnson et al., 2002). Therefore, it is possible that developmental regulation of the phenylpropanoid pathway is regulated via a WD40-like G-protein signal transduction pathway, whereas defense-induced activation is mediated by WRKY family transcription factors (Winkel-Shirley, 2001). In contrast to our understanding of the transcriptional regulation of anthocyanin biosynthesis, the transcriptional regulation of isoflavonoid biosynthesis is poorly understood. The fungal-induced transcriptional activation of key enzymes in isoflavonoid synthesis, such as IFS, IOMT, and IFR, has been reported, mainly in alfalfa (He et al., 1998; Ni et al., 1996; Paiva et al., 1991; Shimada et al., 2000). Constructs that contain an alfalfa IFR promoter fused to an expression reporter were transformed into both alfalfa and tobacco. Fungal-induced expression in both species and developmental expression in alfalfa appeared to be determined by sequences downstream of −436 bp, whereas sequences up to −765 bp conferred a complex pattern of ectopic expression in a heterologous system (Oommen et al., 1994). An IOMT promoter from M. truncatula was cloned and has also exhibited extensive ectopic expression in heterologous systems (Dixon, personal communication). The promoters of soybean IFS1 and IFS2 genes have been cloned and characterized (Subramanian et al., 2004). The promoters are root and seed specific and respond differently to defense and nodulation signals. A unique xylem-specific expression was induced upon Bradyrhizobium innoculation, suggesting novel roles of isoflavones during legume–rhizobium interactions (Subramanian et al., 2004). The transcription factors specific to the isoflavonoid pathway have yet to be reported. Posttranscriptional regulation involves enzyme activation and inactivation and appears to be present at various steps of the pathway, although its general importance is not well understood. One notable exception concerns a hydroxylase that converts coumaroyl CoA to caffeoyl CoA in parsley cells. This enzyme has a very narrow pH optimum and is presumed to be inactive at the normal cellular pH; exposure of cells to a fungal elicitor results in a rapid decrease in intracellular pH, leading to increased enzyme activity and to the production of caffeoyl and feruloyl esters (Kneusel et al., 1989). The entry point enzyme PAL can be regulated posttranscriptionally as well (Bolwell, 1992). The product of PAL, cinnamic acid, not only inhibits PAL transcription, but also induces a proteinaceous inactivation of PAL enzyme (Barz and Mackenbrock, 1994), probably through increased

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phosphorylation and turnover of the enzyme (Allwood et al., 1999). Few other enzymes have been investigated at the posttranscriptional level.

VIII.

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It has long been desired to enhance the nutritional value of the soybean by increasing the total isoflavone content in seeds while maintaining the quality and quantity of other output traits such as protein and oil. The most straightforward approach to metabolic engineering, the overexpression of a single rate-limiting enzyme, may result in a higher accumulation of the final product. For example, overexpression of stricotosidine synthase in Catharanthus roseus cell cultures leads to higher levels of alkaloids production (Hallard et al., 1997). There are not sufficient measurements of flux through the phenylpropanoid or isoflavone pathway to determine which enzyme catalyzes the rate-limiting reaction. PAL, CHS, and IFS are the entry-point enzymes of major branches of the phenylpropanoid pathway. However, overexpression of these three enzymes independently failed to alter the isoflavone content significantly (Zernova et al., 2002). PAL, CHS, and IFS were transformed into soybean via somatic embryo culture bombardment. Early results suggested that out of the three genes, only the lectin promoter-driven PAL gene showed up to a 30% increase in isoflavone contents in some of the transgenic seeds. Even that was not significantly different than natural variations of control lines (Zernova et al., 2002). These results agree with similar experiments carried out at DuPont (unpublished results). When PAL, CHS, and IFS were expressed in seed under the control of a storage protein b-conglycinin promoter, no significant alterations of the isoflavone level could be found, even when increased protein levels of these genes were detected by Western blots (unpublished results). There are several possibilities why this approach did not work. One is that even though the flux of substrates was increased by the overexpression of PAL and CHS, the substrates may not be targeted toward isoflavone biosynthesis. A second set of experiments further demonstrates that enhancing the flow of substrates through the metabolic pathway can cause a surprising outcome due to the complexity of metabolic networks. As mentioned earlier, the maize CRC chimeric gene encodes a chimeric transcription factor that transcriptionally activates the entire phenylpropanoid pathway in maize (Grotewold et al., 1998). When the CRC gene was transformed into soybean under a seed-specific phaseolin promoter, it activated the soybean phenylpropanoid and flavonoid pathway (Yu et al., 2003). In the phenylpropanoid pathway, RNA or protein levels of the four enzymes tested, PAL, C4H,

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CHS, and CHI, were increased by more than 10-fold. In the flavonoid pathway, expressions of the three tested genes, F3H, DFR, and FLS, were drastically increased as well (Yu et al., 2003). In contrast, transformation with CRC did not affect the expression of isoflavonoid branch enzymes, including IFS, IFR, and IOMT (Fig. 5). The heterologously expressed CRC is apparently binding to the consensus cis elements at the promoters of soybean phenylpropanoid and flavonoid pathway genes, interacting with the soybean transcription apparatus, which eventually leads to enhanced gene expression. However, the genes specific to the isoflavone pathway in soybean, and perhaps in other legumes, apparently do not share this particular mode of transcriptional activation. One exception is the CHR gene, which showed similar induction patterns as other phenylpropanoid pathway genes, even though CHR is legume specific and not present in maize. It is possible that the required coordinate expression of

Figure 5 Summary of phenotypes from CRC-transformed soybean seeds in a pathway background. CRC activated the phenylpropanoid and flavonoid pathway genes (broad arrows) and resulted in increased daidzein, isoliquiritigenin, and liquiritigenin levels (thin arrows). No changes in isoflavonoid pathway gene expression (dots) occurred, but genistein levels were reduced.

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CHS and CHR forced the genes to adopt similar transcriptional regulation patterns during evolution. Overexpression of CRC not only perturbed the gene expression of related pathways, but also caused a dramatic change in the phenotype of the seed (Yu et al., 2003). First, the daidzein and glycitein content, as measured by HPLC, were increased by up to fourfold in transgenic seeds. Second, the genistein content was significantly decreased, in some cases, to almost undetectable levels. As a result, the daidzein composition as a percentage of the total isoflavone increased from an average of 40% to about 90%, whereas the genistein composition decreased from approximately 50% to less than 10% or lower. Third, all the transgenic seeds carrying a CRC gene showed a brownish coloration on the seed coat. While this brownish coloration was not condensed tannin (i.e., it was not stained with vanillin), condensed tannins were increased in the seed coats as compared to wild-type seed. The gene expression pattern might explain some of the observed phenotypes (Fig. 5). Because CRC increased the flux of the phenylpropanoid and flavonoid pathways but not the isoflavonoid pathway, the increased pool of naringenin substrate was driven toward flavonoid biosynthesis, such as the condensed tannin synthesis. At the same time, the IFS transcript or protein was not increased; therefore genistein accumulation was significantly reduced. Similarly, because CHR and CHS were overexpressed while the downstream enzymes IFR and IOMT were not, the enhanced daidzein and glycitein accumulations were to be expected. However, the location of the brown color cannot be explained because the seed coat is a maternal tissue and its color should not segregate with the transgene, unless an active transportation system exists that transports some flavonoids from the cotyledon to the seed coat during embryo development. Another surprising and contradictory outcome is the discovery of a pool of daidzein precursors, isoliquiritigenin and liquiritigenin, in immature seeds containing CRC (Yu et al., 2003). These compounds have never been reported in wild-type seed. This implies that CHI, which is a diffusionlimited enzyme, is a rate-limiting factor in daidzein formation. Alternatively, CRC might only induce the expression of a type I CHI in soybean (which does have homologs in maize), but fails to activate the type II CHI that is necessary for daidzein biosynthesis, and does not have a counterpart in maize. Under these circumstances, the entire isoflavonoid pathway, including at least type II CHI, IFS, IOMT, and IFR genes, seems to be regulated by a different set of transcription factors than the CRC type. This set of genes may respond to defense or nodulation signals that specifically call for elevated isoflavonoid biosynthesis. The interaction and competition between flavonoid and isoflavonoid pathways are areas ripe for further exploration. The CRC transcription factor could be used to generate high daidzein/low genistein soybeans suitable to make soy foods that would be useful in

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studying the role daidzein contributes to the health benefits observed from the consumption of soy foods. However, to increase the total isoflavone content, the genistein concentration needs to be increased in CRC lines. Because F3H directly competes with IFS for the naringenin substrate, silencing of the F3H gene in CRC lines will block a major portion of the flavonoid pathway and redirect the flow of substrate toward isoflavone biosynthesis. Indeed, when the CRC and F3H cosuppression constructs were cotransformed into soybean, the genistein was restored to the wildtype level, and the total isoflavone level was increased by at least sixfold (Yu et al., 2003). The physiological features (such as defense and nodulation phenotypes) and molecular pathway analyses (such as gene expression and downstream metabolite quantification) of these transgenic soybeans have not been reported. It will be interesting to see if the increasing isoflavone levels in soybean seed lead to differences in plant–microbe interactions. In conclusion, the combination of transcription factor-driven gene activation and suppression of a competing pathway provided a successful method to enhance the accumulation of isoflavones in soybean seed. Compared to projects aimed at increasing isoflavone levels, strategies to develop soybeans with decreased levels of isoflavones are relatively straightforward. There are at least two approaches that should be suitable for producing isoflavone-null soybeans: (1) using a gene-silencing approach to decrease IFS expression in seeds and (2) the combination of overexpression of the CRC transcription factor and gene silencing of CHR to simultaneously reduce both genistein and daidzein production. This may be a case in which traditional breeding is particularly useful, as an alternative strategy it is an extensive mutant isolation screen to identify isoflavone-depleted lines. In addition to being of use for potential applications such as infant formula or protein isolate for bodybuilders, these lines will also be of use in studying the function of isoflavones during plant–microbe interactions and the role that isoflavones play in providing beneficial health benefits derived from the consumption of soy foods.

IX. METABOLIC ENGINEERING OF ISOFLAVONE ACCUMULATION IN NONLEGUMES The introduction of isoflavones into widely consumed crops such as corn may offer new sources of dietary isoflavone, which will increase the nutritional value of the crop and bring the health benefits of isoflavones to more consumers. Aside from the nutritional benefits, the accumulation of isoflavones as a novel phytoalexin in nonlegume plants could potentially

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enhance disease resistance and thus increase the agronomic value of the crop as well. To engineer the isoflavone pathway in nonlegume plants, heterologous expression of IFS is an essential step because it is required to convert the naringenin substrate (ubiquitous in higher plants) to isoflavone. Several experiments demonstrated that complex enzymatic interactions and pathway alterations occurred in nonlegume plants after expression of IFS. The soybean IFS1 cDNA was expressed under the control of a strong constitutive promoter in Arabidopsis, a nonlegume plant that does not synthesize isoflavonoids (Jung et al., 2000). Transgenic plants analyzed by HPLC showed that IFS diverted naringenin from the phenylpropanoid pathway to produce the isoflavone genistein. However, the level of genistein accumulated in Arabidopsis was low as compared to other flavonoids, even when the expression of IFS was high as confirmed by Northern and Western blot analyses. To increase naringenin levels, the expression of phenylpropanoid pathway genes was activated by a 12-h UV-light irradiation. This resulted in a threefold increase in genistein levels, but the portion of genistein in total flavonoid levels actually decreased, suggesting that the pool of naringenin substrate was not equally accessible to the flavonoid and isoflavonoid branch of the pathways. Similar experiments using transgenic tobacco also indicate differential partitioning of naringenin. When the aforementioned IFS construct was transformed into tobacco, the only tissue in which isoflavone accumulation could be detected was the flower, where the phenylpropanoid pathway was actively producing pink anthocyanin pigments (Yu et al., 2000). This was despite the fact that gene expression analysis and in vitro microsomal enzyme assays demonstrated a high level of functional expression of IFS gene in the leaf. The UV-light induction of isoflavone accumulation in Arabidopsis and the tissue-specific accumulation of isoflavone in tobacco indicate that isoflavone biosynthesis in nonlegume plants is dependent on phenylpropanoid path way activity. Additionally, unlike in Arabidopsis, UV-light treatment of tobacco leaves to increase naringenin levels resulted in elevated flavonol levels but failed to raise anthocyanin or isoflavone levels, suggesting that in this tissue, flux through the phenylpropanoid pathway was tightly channeled to flavonol production (unpublished results). Taken together, isoflavone biosynthesis is governed by both pathway activities and enzymatic interactions in heterologous systems. To delineate enzyme interactions between IFS and endogenous flavonoid pathway genes, a CHI from alfalfa, shown to be a type II by its ability to convert isoliquiritigenin into liquiritigenin, was transformed into Arabidopsis and then genetically crossed into a transgenic Arabidopsis carrying the IFS gene (Liu et al., 2002). The combination of genes enhanced genistein

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accumulation moderately. However, the flavonol accumulation was significantly reduced compared to transgenic plants carrying only the legumespecific CHI. The disproportionate reduction of flavonol biosynthesis caused by the presence of IFS further confirmed that the flux of substrate is preferentially channeled toward endogenous flavonoid biosynthesis. Using this information, the authors then went on to carry out experiments that led to significantly higher levels of isoflavone accumulation. Arabidopsis tt6/tt3 double mutant has structural defects in both F3H and DFR genes and is thus blocked in flavonol and anthocyanin production. When the IFS and type II CHI were introduced into a tt6/tt3 double mutant background, genistein accumulation was enhanced by up to 30-fold as compared to plants expressing IFS alone. Again, this suggests that the bottleneck for isoflavone production in Arabidopsis is competition for flavanone between IFS and endogenous flavonol synthesis. The levels of genistein measured approximately 50 mg per gram, the highest levels of isoflavone detected in an engineered nonlegume plant. It should be noted that is still 40- to 60-fold lower than the level of total isoflavones found in commodity soybean seeds grown under typical field conditions. For metabolic engineering of isoflavone production in a monocotyledonous plant, the IFS gene was cloned into monocot expression vectors and was transformed into Black Mexican Sweet (BMS) maize suspension cultures (Yu et al., 2000). Initially, no genistein could be detected in 32 independently transformed lines. To activate the phenylpropanoid pathway, the CRC gene was cotransformed with IFS into BMS. Activation of the phenylpropanoid pathway by the CRC transcription factor resulted in an intense red anthocyanin accumulation. In the IFS and CRC cotransformed lines, approximately half of the transgenic lines were red and the rest were colorless, probably caused by the lack of CRC expression, which was driven by a weak NOS promoter. Genistein accumulated to a detectable level only in the red lines where the phenylpropanoid pathway activity was visible by the pigments. Once again, isoflavone accumulation is correlated with phenylpropanoid pathway activity (Yu et al., 2003). CRC and IFS under the embryo-specific oleosin promoter were also introduced into corn callus cultures capable of regeneration into fertile plants. The regenerated plants had dark red kernels with genistein levels less than 0.1% of that found in soybean seeds. As observed in Arabidopsis and tobacco, the flavonoid branch of the pathway overwhelmed the engineered isoflavonoid branch in maize. One strategy for increasing genistein accumulation is to block anthocyanin production in isoflavone-producing maize. The a1 recessive mutant contains a transposon insertion at the DFR gene and blocks anthocyanin and 3-deoxyflavonoid accumulations throughout the plant. By genetic crossing, the a1 mutant was introduced to the CRC þ IFS maize, and F2 seeds containing CRC þ IFS and homozygous

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a1 alleles were tested for isoflavone accumulations (Yu, unpublished data). As mentioned earlier, there are at least five enzymes using naringenin as a substrate in maize. Blocking DFR may not have a significant impact on overall flux of the substrate. To engineer high levels of isoflavone in maize, further investigations into the enzyme organization and pathway interactions may need to be carried out. To produce daidzein (5-deoxyisoflavone) in nonlegume plants, CHR must be introduced in addition to IFS. Experiments in BMS that introduced IFS, CRC, CHR, and a transformation selection marker showed only a minute amount of daidzein, which was detected by GC-MS (Yu et al., 2000). The detailed gene expression and metabolite distribution analyses were not reported. The conversion of isoliquiritigenin to liquiritigenin may also be a limiting factor for the production of daidzein due to the lack of type II CHI in maize and other nonlegume species.

X. THE BOTTLENECK OF ISOFLAVONE PATHWAY ENGINEERING: “METABOLIC CHANNELING?” Previous experiments repeatedly demonstrated that protein–protein interactions between the key enzymes regulate isoflavone biosynthesis in legume and nonlegume plants. In general, sequential or related enzymes in metabolic pathways sometimes maintain specific interactions and are even colocalized to defined regions in the cell to form dynamic complexes called “metabolons” (Dixon and Steele, 1999; Ovadi and Srere, 2000). These multienzyme assemblies localize the accumulation of pathway intermediates and regulate competition for metabolites among branch pathways. Therefore, protein–protein interactions give rise to a higher level of complexity for controlling metabolic pathways beyond simple kinetic parameters and transcriptional control. The formation of metabolons has been well documented in many organelles, including chloroplasts, mitochondria, and peroxisomes (for reviews, see Dixon and Steele, 1999; Winkel-Shirley, 1999). For example, enzymes related to the Calvin cycle, which converts carbon dioxide into fixed carbon, are colocalized to chloroplast thylakoid membranes and have direct physical contact to ensure the channeling of substrates and products and to maintain efficient carbon fixation and conversion (Suss et al., 1993). In the cytoplasm, enzymes of secondary metabolism pathways may form similar metabolons. Multiple evidences support the existence of such metabolic channels in the phenylpropanoid pathway. When radioisotope-labeled substrates were fed to isolated buckwheat microsomes, the majority of p-coumaric acid (the product of C4H) came from phenylalanine, instead of cinnamic acid,

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suggesting a tight channeling of the first two enzymes of the phenylpropanoid pathway, PAL and C4H (Hrazdina and Wagner, 1985a). More direct evidence came from the colocalization of “soluble” enzymes to the ER membrane. It has been proposed that soluble enzymes form metabolons on a membrane surface, adjacent to the cytochrome P450 monooxygenase enzymes. The cytochrome P450 monooxygenases are integral membrane proteins that have been shown to be associated with the ER (Hrazdina and Wagner, 1985b). In the phenylpropanoid pathway, PAL and CHS were cofractionated with membrane-bound C4H and an ER marker protein (Wagner and Hrazdina, 1984). Additionally, the direct protein–protein interactions of CHS, CHI, F3H, and DFR in Arabidopsis were demonstrated by Burbulis and Winkel-Shirley (1999) with a yeast twohybrid assay, affinity purification, and immunocoprecipitation. In the isoflavonoid pathway, both IFS and I2’H are cytochrome P450 monooxygenases and have been shown to localize on ER (Liu and Dixon, 2001). Therefore, the type II CHI, together with other isoflavone biosynthesis enzymes, may form its own metabolic channels, independent of the flavonoid channels described in Arabidopsis. In fact, Liu and Dixon (2001) demonstrated that a key isoflavonoid phytoalexin synthesis enzyme, IOMT, is localized to the cortical ER surface only after elicitor induction, and this transient ER localization may be important for the function of IOMT. They provided a model suggesting that intermediates of the isoflavonoid pathway could flow rapidly from one enzyme center (IFS) to the next enzyme center (I2´H), which may eventually fuse with vacuoles. However, the prenyltransferases involved in the synthesis of prenylated pterocarpans and furanocoumarins are associated with plastids, not just the ER, thus requiring the shuttling of compounds between membranes and compartments (Dhillon and Brown, 1976). Although three-dimensional structures are available for many of the phenylpropanoid pathway enzymes, including alfalfa CHS and CHI, no structural model of this proposed macromolecular complex has been published. However, mechanistic studies of CHS and CHI support the need for metabolic channeling in this pathway. The nonenzymatic cyclization of chalcones into flavanones occurs in solution, but yields an enantiomeric mix of biologically inactive and active isomers. Channeling between CHS and CHI would prevent the formation of mixed isomers. Interestingly, the catalytic efficiency of CHI (kcat/Km ¼ 109 M−1 min−1) approaches the diffusion limit, so why would CHI need metabolites directed toward it? The moderate lipophilic nature of chalcones/flavanones may require close contact to limit potential sequestration in cellular membranes. Moreover, in legumes, the metabolon may “slow” CHI to protect the chalcone pool from complete conversion into naringenin (Jez et al., 2002). In many ways CHI is a paradoxical enzyme: it catalyzes a reaction that is thought to occur spontaneously yet its presence is necessary for flavonol

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production. In Arabidopsis, CHI is a single copy gene and mutations (tt5) have been isolated on the basis of their yellow seed color (Shirley et al., 1992). These mutants survive but are more sensitive to UV light (Li et al., 1992) and have been shown not to accumulate anthocyanidins or flavonols (Shirley et al., 1995). In tomato skins there is no CHI present and the naringenin-chalcone accumulates. Overexpression of CHI causes up to a 78-fold increase in flavonoid content (Muir et al., 2001; Verhoeyen et al., 2002), all of which suggests that although the reaction from chalcone to flavone should occur spontaneously, it is dependent on the presence of the enzyme CHI. Other recent evidence suggests that CHI may have functions other than those of a catalyst. The maize CHI is capable of complementing the Arabidopsis tt5 mutant (Dong et al., 2001). Interestingly, two mutant maize proteins with only approximately 20% or 3–5% of wild-type maize CHI activity, respectively, are able to complement the tt5 mutant as well (Irnai and Grotewold, 2003; personal communications). Either a small amount of CHI activity is sufficient to drive flux or the enzymatic activity is really not that relevant for CHI function. This is suggestive of a role for CHI extraneous to the catalytic activity, perhaps acting as a structural scaffold for the enzymes involved in the various branches of the pathway. Furthermore, a soybean CHI homolog (TC177628) with 81% similarity to L. japonicus CHI3 is expressed throughout the plants (based on EST distribution). Surprisingly, this “CHI” lacks a conserved serine residue at the reaction center and does

Figure 6 Proposed macromolecular complexes in the phenylpropanoid pathway. The isoflavonoid metabolon is shown on the left. The flavonoid metabolon after CHS is on the right. Arrows indicate metabolite flow.

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not have the enzyme activity in vitro (Yu, unpublished data), which may support the nonenzymatic function of CHI. Because metabolites flow through the phenylpropanoid pathway branches after CHI, this enzyme is likely a key component in interacting with downstream proteins in isoflavonoid (IFS) and flavonoid (F3H, FNS, DFR) biosynthesis (Fig. 6). Legumes contain both type I CHIs that are found in all plants and convert trihydroxy-chalcones into flavanones and type II CHIs, which convert both tetrahydroxy-chalcones and trihydroxy-chalcones into flavanones (Kimura et al., 2001; Shimada et al., 2003). Understanding the interactions between CHI and other pathway enzymes under the context of metabolic channeling may be crucial for achieving high levels of isoflavones in nonlegume plants. Taken together, the metabolic channeling in secondary metabolism presents additional challenges for metabolic engineering attempts.

XI. CONCLUSIONS Although there has been significant progress in metabolic engineering of isoflavone biosynthesis, the process remains a challenge. A better understanding of the health effects derived from consuming isoflavones would significantly increase the rewards for efficacious methods. To that end, some of the novel phenotypes produced by metabolic engineering will be useful in understanding the health benefits of consuming isoflavones. Separate from the goals to increase isoflavones for human consumption, it may be desirable to produce or increase the production of isoflavones in both legumes and nonlegume plants to alter plant–microbe interactions, which may lead to increased plant disease resistance or other desirable phenotypes. The temporal and spatial expression patterns, as well as the specific species of isoflavonoid(s) necessary for the desired phenotypes, still need to be determined. The individual reactions involved in the biosynthesis of isoflavones and the enzymes that catalyze the reactions are known. Genes that encode these enzymes have been cloned and the regulation of these genes is beginning to be understood. There are still gaps in our knowledge of how interactions of the various pathways are regulated, and an understanding of how the metabolon is formed and how specific members of protein families interact is only now developing. Clearly, understandings of these processes are necessary for more exquisite control of the modification of the isoflavone pathway. The phenylpropanoid and isoflavonoid pathways have long been studied and the knowledge gained has allowed a fairly deep understanding of

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secondary metabolism. This understanding will be important in allowing us to engineer other pathways that are less well understood.

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BIOLOGICAL CONTROL OF WEEDS WITH ANTAGONISTIC PLANT PATHOGENS Reza Ghorbani,1 Carlo Leifert1 and Wendy Seel2 1

Ecological Farming Group, School of Agriculture, Food and Rural Development, University of Newcastle, Nafferton Farm, Stocksfields, Newcastle upon Tyne, NE43 7XD, United Kingdom 2 Plant and Soil Science, School of Biological Sciences, University of Aberdeen, St. Machar Drive, Aberdeen, AB24 3UU, United Kingdom

I. II. III. IV.

V.

VI.

VII. VIII.

Introduction Biological Control of Weeds History of Biological Control Methods Strategies of Weed Biological Control A. Classical (Inoculative) Biological Control B. Bioherbicide (Inundative) Biological Control C. Conservation and Augmentation Biological Control Factors Affecting the Efficacy of Pathogens Used in Biological Weed Control A. Biotic Environment B. Physical Environment C. Soil Environment Formulation of Biological Control Agents A. Formulation for Foliar Application B. Formulation for Soil Application Limitations and Justifications of Biological Weed Control Overall Conclusion References

Many research programs have studied different aspects of the use of antagonistic plant pathogens in biological weed control strategies. The study of effects of individual environmental factors can be regarded as the first step in understanding limitations to the success of biological control methods. This review attempts to address the current advances of the basis and the progress of biocontrol methods, the link between environmental factors and plant infection development, and the use of formulation technol# 2005, Elsevier Inc. ogy in biological weed control.

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I. INTRODUCTION Agriculture is the process of managing plant communities to obtain useful materials from a limited number of species called crops. Since man first began to cultivate crops, undesirable plants, called weeds, have been a problem. Weeds reduce agricultural production in several ways: they compete with the crop for resources; increase general additional costs due to ploughing, harrowing, and disking; they may cause cultivating and harvesting problems; be hosts of diseases and parasites of crop plants; and cause toxicity, undesired color, taste, or odor in the final products (Klingman et al., 1982). Crop losses due to weeds are still very large and can result in significant financial burdens for farmers. It has been estimated that on a global basis, weeds are considered responsible for a 10% reduction of crop yield (Froud-Williams, 2002). The estimated average annual yield losses in America are valued at more than six billion dollars. In addition to this, about nine billion dollars are spent annually in America on weed control strategies (Aldrich and Kremer, 1997). Among all the petrochemical based pesticides, herbicides are used in the greatest volume, illustrating the relative importance of weeds. Herbicides accounted for 44% of the total, insecticides for 29%, fungicides for 21%, and others for 6% (Quimby et al., 2002). Much of the last half-century of weed science and weed management technology has been directed at total weed eradication, although this is not a realistic possibility in most arable fields, pastures, and rangelands (Liebman et al., 2001). Conventional efforts to eradicate weeds with herbicides have reduced weed competition and improved farm labor efficiency, but have also incurred substantial costs, including environmental pollution, threats to human health, and growing dependence on purchased input. New approaches are needed to manage weeds effectively while minimizing or eliminating such costs (Hoagland, 1990). Sustainable agricultural systems dictate that input currently provided by nonrenewable petrochemical resources should be replaced by biologically based renewable inputs, and therefore a need to develop sustainable weed management exists (Quimby et al., 2002). Moreover, the number of herbicide-tolerant/resistant weed species is growing more rapidly, as Zimdahl (1999) reported that more than 100 cases of herbicide resistance have been reported in 15 herbicide chemical families, and Quimby et al. (2002) stated that there are more than 300 examples of resistance for various weed species to different herbicides. Therefore, the need for assessing and implementing alternatives to chemical controls and the development of a more integrated approach to weed management are highlighted (Burki et al., 1997). Biological control of weeds using plant pathogens is accepted as a practical, safe, and environmentally beneficial weed management method

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applicable to agroecosystems (Charudattan, 2001). Biocontrol products can serve as an alternative to chemical pesticides (Elad, 2000). Moreover, the cost–benefit analysis is more favorable for bioherbicides than for chemical herbicides, as capital outlays needed for research, development, and registration of chemical herbicides versus bioherbicides considered are in the range of $50 million for chemical herbicides versus $2 million for bioherbicides (Charudattan, 2001). Research on the biological control of weeds has been practiced for many years and today is further driven by human communities and governments as a sustainable method with a reduced dependence on nonrenewable petrochemicals (Quimby et al., 2003).

II.

BIOLOGICAL CONTROL OF WEEDS

The concept of biological weed control is based on the premise that certain biotic factors differentially influence the distribution, abundance, and competitive abilities of different plant species (Kennedy and Kremer, 1996). Biological weed control is therefore an approach that uses living organisms to control or reduce the population of a selected, undesirable weed species, while leaving the crop unharmed (TeBeest, 1991). Since 1980, eight bioherbicides have been registered, at least 15 new biocontrol agents have been introduced, and more than 100 microorganisms have been identified as having the potential for weed biocontrol (Charudattan, 2001). However, a number of problems must be solved, such as a lack of consistency across various environments, before many of these organisms can be utilized on a commercial scale (Kennedy and Kremer, 1996). The purpose of this review is to assess the information available on these problems and indicate the extent to which they can be overcome.

III. HISTORY OF BIOLOGICAL CONTROL METHODS The earliest records of biological control refer to the use of cats to protect stored grain from damage by rodents, and indeed all the recorded early efforts employed general predators such as owls, toads, and ants (Waage and Greathead, 1988). During the 19th century, after microbes were discovered and insect life cycles began to be understood, some attempts were made by scientists to use other kinds of organisms. Observations of the effects of living organisms on weeds date from 1795 when an insect, Dactylopius ceylonicus, was introduced for drooping pricklypear (Opuntia vulgaris) control over a vast area in Australia (Tsukamoto et al., 1997). However, the

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successful and well-publicized introduction of the vedalia beetle (Rodolia cardinalis) into California from Australia in 1888 to control the cottony cushion scale (Icerya Purchasi) is usually taken as the formal beginning of biological control as a recognized discipline (Waage and Greathead, 1988). TeBeest (1996) considered that the idea of controlling weeds with plant pathogens dates back to between 1893 and 1894 when the New Jersey Experimental Station Bulletin reported a list of fungi injurious to weed seedlings. At the same time, a grower wrote in a letter to the New Jersey Experimental Station reporting that he had seen an acre of a farm overrun by Canada thistle (Cristium arvense), but by the time they were in full bloom, a rust stuck and hardly any of them produced seed. In the early 1980s, the first commercial nonchemical herbicides containing microorganisms (microbial herbicides/bioherbicides) were marketed. This bioherbicide, called DeVine, contains the fungus Phytophthora palmivora and is used to control Morrenia odorata in citrus plantations in Florida (Kenny, 1986).

IV. STRATEGIES OF WEED BIOLOGICAL CONTROL Based on the way in which natural enemies and antagonistic pathogens (biocontrol agents) are applied, three different approaches have been recognized in the biological control of weeds.

A. CLASSICAL (INOCULATIVE) BIOLOGICAL CONTROL The classical technique involves introducing organisms that act as biological control agents into a region where an exotic weed exists at noxious levels (Scher and Castagno, 1986). In this approach, weeds are controlled by one or several introductions of an exotic organism (Scheepens et al., 2001). Once successful releases have led to establishment, no further attempts, such as spraying or cultivation, are made to alter the population of the agent if a balance is maintained between the weed and its agent that keeps the weed below economic threshold levels (McWhorter and Chandler, 1982). This method has several advantages, such as self-perpetuation and self-dispersal of biocontrol agents; therefore, after initial establishment, no further costs are required over years and area. The main disadvantage is that once a biocontrol agent released, it cannot be recalled, and thus great care should be taken to consider potential conflicts of interest on nontarget plants (safety) before being released (Quimby et al., 2002). In classical biocontrol the necessary considerations are (1) safety (the biocontrol agent must not attack any cultivated or important living organism in the region),

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(2) adaptation (organisms highly adapted to the weed species or its close relatives), (3) virulence (biocontrol agents should have the ability to heavily infest an individual weed by overcoming its resistance to attack), and (4) effectiveness (ability to reach infection levels that cause reductions in populations of the weed to below economic threshold levels) (McWhorter and Chandler, 1982). There are successful examples of classical biological control of weeds: introduction of a rust fungus, Puccinia chondrillina, into Australia to control rush skeleton (Chondrilla juncea), which is a weed in Australian cereal crops (Charudattan and Dinoor, 2000); smut fungus, Entyloma ageratinae, imported from Jamaica to control Hamakua pamakani (Ageratina riparia) in Hawaiian forests and rangelands; Puccinia carduorum imported from Turkey and released into the northeastern United States to control musk thistle, Caduus thoermeri; the rust of Phragmidium violaceum to control weedy species of Rubus in Chile and Australia; and Uromycladium tepperianum to control invasive tree species of Acacia saligna in South Africa (Charudattan and Dinoor, 2000).

B. BIOHERBICIDE (INUNDATIVE) BIOLOGICAL CONTROL In this approach, large numbers of an organism are introduced into an environment in much the same way that herbicides are applied. A bioherbicide is defined as a plant pathogen used as a weed-control agent through inundative and repeated applications of its inoculum (Charudattan and Dinoor, 2000). Commercial biological control of weeds with plant pathogenic fungi is considered largely under the inundative category. Organisms used inundatively (1) must be safe, as they are released in the field at high population densities; (2) should have suitable life cycle characteristics that allow easy cultivation on a large scale; (3) should be easy to produce and store; and (4) should be highly virulent against the target (Charudattan et al., 1985). At least five species of fungi and one species of bacteria are registered as bioherbicides in Canada, Japan, South Africa, and the United States (Charudattan, 2000). These are (1) DeVine, composed of a Florida isolate of Phytophthora palmivora used for the control of Morrenia odorata in citrus in Florida; (2) Collego, based on Colletotrichum gloeosporioides f.sp. aeschynomene, is used to control Aeschynomene virginica, a leguminous weed in rice and soybean crops; (3) BioMal, containing Colletotrichum gloeosporioides f.sp. malvae, for control of Malva pusilla, presently unavailable for commercial use, but currently under development with a different formulation from Biomal and under a new commercial name of Mallet WP; (4) Dr. BioSedge, based on the rust fungus Puccinia canaliculata and

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registered for the control of Cyperus esculentus, presently unavailable for commercial use; (5) CAMPERICO, containing an isolate of Xanthomonas campestris pv. Poa,e which is a wilt-inducing bacterium, isolated in Japan from Poa annum, to control Poa annua in golf courses; and (6) Stumpout, based on the wood-infecting basidiomycete, Cylindrobasidium laeve registered in South Africa to control resprouting of cut trees in tree plantations and in natural areas (Charudattan, 2001; Charudattan and Dinoor, 2000). There are about five or six other unregistered bioherbicides used on small scales and also about 12 pathogens are under precommercial evaluations in different countries (Charudattan and Dinoor, 2000).

C. CONSERVATION AND AUGMENTATION BIOLOGICAL CONTROL Many authors define conservation biological control as actions that preserve or protect natural enemies and augmentation as actions that indirectly increase the populations of natural enemies. However, other researchers consider conservation to mean environmental modification to protect and enhance natural enemies. Conservation of natural enemies is probably the oldest form of biological control of insect pests. As early as 900 A.D., Chinese citrus growers placed nests of the predaceous ant (Oecophylla smaragdina) in mandarin orange trees to reduce populations of foliage feeding insects (Barbosa, 1998).

V. FACTORS AFFECTING THE EFFICACY OF PATHOGENS USED IN BIOLOGICAL WEED CONTROL A large number of potential biocontrol agents have been identified; however, only a few of them have reached the market as commercial products. The development of a successful biocontrol agent requires a thorough understanding of the ecology and physiology of the potential agent, especially its interactions with the physical environment. Understanding of these often complex relationships provides the basis for assessment of the potential biological control agent. In addition, the physical, chemical, and genetic characteristics of the target weed are likely to be key factors determining the success or failure of a candidate biocontrol agent. These all have to be considered along with any interactions between the potential bioherbicide and both nontarget hosts and associated microbes.

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A. BIOTIC ENVIRONMENT 1.

Virulence

Virulence or the ability of a biocontrol agent to infest a weed by overcoming its resistance to attack is one important factor determining the efficacy of biological control agents. The major pathogenicity or virulence factors that seem to be involved in degree of disease production, either directly or indirectly, are (1) enzymes that degrade plant cell walls (such as cutinises, pectinases or pectolytic enzymes, pectin lyases, cellulases, hemicellulases, ligninases) and other structures, such as proteins and lipid membranes (e.g., proteases, proteinases, peptidases, amylases, lipases, phospholipases), facilitating pathogen entry or dispersion through the host (Agrios, 1997; Keen and Staskawicz, 1988); (2) toxins that injure or kill plant cells, permitting the pathogen to colonize the disabled cells (Agrios, 1997; Keen and Staskawicz, 1988); (3) growth regulators (e.g., auxins, gibberellins, cytokinins, ethylene) (Agrios, 1997); and (4) polysaccharides (release a mucilaginous substance and cause a mechanical blockage of the vascular tissues) (Agrios, 1997). A detailed understanding of the virulence structure of the antagonist population should be essential in the development of a biological control agent. The pathogenicity or virulence of different species and isolates is variable; therefore, in order to find an effective biocontrol agent, screening for the most virulent isolate against specific weed species is necessary.

2.

Density of Biocontrol Agents

For disease development in target weed, enough active propagates (spores, conidia, mycelial fragments, etc.) of the biocontrol agent in the plant surface are needed. The leaf should also be in a good position and of sufficient size to keep the microorganism for the time needed for penetration in suitable environmental conditions. The most effective biocontrol agent density is different in various microorganisms, weed species, and environment conditions (Hoagland, 1990). Mabbayad and Watson (1995) reported that high inoculum concentrations (105 conidia ml−1 or higher) of Alternaria sp. are required for symptom development in Sphenoclea zeylanica. Mintz et al. (2002) found that seedlings of Amaranthus albus were killed within 2 days after inoculation with 106 conidia ml−1 of Aposphaeria amaranthi; however, at a spore concentration of 104 ml−1, plant death happened only when followed by a 24-h dew period. Pathogenicity of Alternaria alternata in Amaranthus retroflexus increased with increasing spore concentration. A spore concentration of 107 spores ml−1 in a rapeseed oil emulsion and

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Figure 1 Effect of fungal strain, inoculum density (spores ml−1), and formulation in oil seedrape on disease development in Amaranthus retroflexus at the four leaf stage 10 days after spraying with Alternaria alternata. Control plants (sprayed by distilled water) did not show symptoms (results not included). Linear regression analysis showed a significant difference for spore concentration (P < 0.001) and for formulation of spores (water or oil emulsion) (P < 0.001), but no significant difference between A. alternata strains (P ¼ 0.128, n ¼ 12).

given a 24-h dew period caused 100% mortality of A. retroflexus plants (Ghorbani, 2000; Fig. 1). Commonly, a high concentration of the active ingredient is required to achieve full disease expression by most antagonists. However, requirement of a high spore density is undesirable if an economically viable biocontrol agent is to be produced. More virulent isolates and appropriate formulation can reduce the high inoculum concentration requirement.

3.

Weed Growth Stage

The susceptibility of weeds to a specific dose of inoculum varies with the weed growth stage. For example, Alternaria cassiae infected and killed young Cassia obtusifolia seedlings, but equivalent spore densities applied to mature plants resulted in few infections, and plant death or growth reduction did not happen in mature plants (Charudattan et al., 1986). Echinochloa seedlings at the 1 and 2 leaf stages were more susceptible to Exserohilum monoceras than seedlings at 3 and 4 leaf stages (Zhang and Watson, 1997b; Zhang et al., 1996). The Alternaria sp. was virulent on all plants of Sphenoclea zeylanica at different developmental stages from seedlings to flowering stages (Mabbayad and Watson, 1995). Disease aggressiveness in Sclerotinia spp. decreased with an increasing plant age of Ranunculaus acris (Green et al., 1995). Plants of Ulex europaeus at all tested growth stages (up to 4 months old) were susceptible to the fungus Fusarium tumidum, but younger plants were killed more easily (Morin et al., 1998). Amaranthus albus seedlings were killed at the 4 leaf stage by Aposphaeria

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amaranthi and less than 30% death was achieved with plants having 8 leaves. Once plants began flowering (12–14 leaves), disease development decreased and symptoms were primarily restricted to stem and leaf lesions (Mintz, et al., 1992). Kadir et al. (2000) reported that 4–6 leaf stage plants of Cyprus rotundus were more susceptible to Dactylaria higginsii than older (8 leaf stage) plants. Therefore, plants change in their susceptibility to disease with age. In some plant–pathogen combinations, the hosts are susceptible only during the growth period and become resistant during the adult period (adult resistance). With several diseases such as rusts, plants are actually quite resistant to infection while still very young, become more susceptible later in their growth stage, and then become resistant again. In other diseases, plant parts are resistant during growth and the early adult period but become susceptible near ripening (Agrios, 1997). Susceptibility of the weed Epilobium angustifolium to the fungus Colletotrichum dematium decreased with increasing plant age up to 10-week-old plants (Leger et al., 2001). Wheat seedlings were more susceptible to Pyrenophora semeniperda than older plants and 3-week-old seedlings were slightly stunted, whereas older plants were unaffected (Campbell and Medd, 2003). Reaction of Amaranthus retroflexus to a single spray application of a suspension of Alternaria alternata containing 107 spores ml−1 was significantly greater at the 2- and 4-leaf stage compared to the cotyledon stage and older than 6-leaf stages (Ghorbani, 2000; Fig. 2). Mintz et al. (1992) observed similar results

Figure 2 Effect of Amaranthus retroflexus plant growth stage, inoculum density (spores ml−1), and formulation of Alternaria alternata spore suspension on disease development (5 ¼ dead plant, 0 ¼ health). Control plants (sprayed with distilled water) and plants sprayed with 106 spores ml−1 without emulsion did not develop disease symptoms. Regression analysis showed significant differences for growth stage (P < 0.001), spore concentration (P < 0.001, n ¼ 12), and application of emulsion (P < 0.001).

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and suggested that seedlings before the 2-leaf stage are too small to maintain sufficient inoculum on plant tissues for infection or seedlings may have more resistance at the cotyledon stage. The decrease in susceptibility of the older plants as compared to plants in the 4 leaf stage may be related to a change in plant epidermis structure, more surface wax, and/or production of specific metabolic products. In perennial weeds the susceptibility to antagonistic pathogens may be different depending on the age. For example, in the weed Plantago lanceolata there was a significant positive effect of plant age on Fusarium moniliforme pathogen frequency overall, but this was not consistent over all ages. Pathogen frequency was higher in 2-year-old plants than in 1-year-old plants, suggesting that age structure can influence the host–pathogen interaction. This pattern did not continue into 3-year-old plants. A possible explanation for this is that selective mortality allows only generally robust plants, and consequently the most resistant plants to survive to the oldest ages (Dudycha and Roach, 2003). Penetration and infection of a specific pathogen (microbial herbicide) are influenced by characteristics of both plant morphology and physiology and the delivery system in which the bioherbicide is applied (Hess and Flak, 1990). Leaf surface morphology and physical characteristics of biocontrol agents can influence the agent performance. Composition and concentration of resistance compounds/carbohydrates and enzyme activities in the host plant are important characteristics, which may cause incompatibility between plant species and antagonistic pathogens. Leaf surface topography and characteristics such as cuticle development, quality and composition of epicuticular wax as deposited on leaf surface, and the presence, type, and distribution of trichomes all influence the distribution of a given bioherbicide sprayed onto a leaf surface (Agrios, 1997). Clearly, further research is needed to optimize the positioning and processes such as spore germination, hyphal growth, and epidermal penetration by microorganism in the host plant.

B. PHYSICAL ENVIRONMENT The physical environment acts on both the microorganism and the host plant (Hoagland, 1990). It can variously act in favor of one, the other, or both depending on the suitability of conditions and the plasticity of the organisms involved. Some pathogens are highly plastic and are capable of tolerating a wide range of environmental conditions (Colhoun, 1973). Other pathogens may be less tolerant to environmental variations and are likely to be more restricted in their geographical and temporal distribution. For antagonists with the potential to become a bioherbicide, plasticity with respect to physical environment is an advantage. The following sections

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discuss some of the major physical factors affecting interactions between microorganisms and plant surfaces.

1. Temperature Temperature is one of the most important factors influencing the occurrence and development of many plant pathogenic diseases. Effects of temperature on infection may be attributed to effects on the pathogen, on the host, or on interactions between host and pathogen (Colhoun, 1973). Epidemics are sometimes favored by temperatures higher or lower than the optimum for the plant because they reduce the level of the horizontal resistance of the plant.1 At certain levels of infection, temperatures may even reduce or eliminate the vertical resistance2 of host plants (Agrios, 1997). Some spore collections of Peronospora tabacina germinate best at 2–10  C and others at 18–26  C (Colhoun, 1973). Therefore, a single optimum temperature for germination of spores in different isolates of this species does not exist. Similarly, a host may be susceptible to a pathogen at one temperature and resistant at another, but another cultivar of the same species may show quite different reactions (Colhoun, 1973). Walker (1981) showed temperature had highly significant effects on penetration and infection level of Alternaria macrospora in Anoda cristata. Most penetrations occurred at 25  C, fewer at 15, 20, and 29  C, and the least at 10  C. Disease development on Abutilon theophrasti by Colletotrichum coccodes was most severe at air temperatures of 24 or 30  C, which corresponded to the optimal range for spore germination and mycelial growth of this fungus (Hoagland, 1990). Infection of Pteridium aquilinum by Ascochyta pteridis occurred as low as 10  C but required at least 18 h of leaf wetness at this temperature. The infection frequency increased with increasing temperature up to 20  C, whereas the length of the leaf wetness period required for infection decreased over the temperature range of 10 to 20  C (TeBeest, 1991). Lesion development in inoculated plants of soybean with Rhizoctonia solani increased with increasing temperature from 21 to 29  C and decreased from 33 to 40  C (Kuruppu and Schneider, 2001). Fusarium tumidum infected Ulex europaeus over a wide range of temperatures (5–27  C), but more plants were killed as temperatures increased during the initial infection phase (Moirn et al., 1998). Optimum temperatures for disease development and dry weight reduction by Alternaria alternata on Amaranthus retroflexus plants were 20–30  C. Disease development was reduced at lower (15  C) and higher (35  C) temperatures (Ghorbani, 2000). Leaf necrosis in Xanthium occidentale 1 2

Partial resistance equally effective against all races of a pathogen. Complete resistance to some races of a pathogen but not to others.

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and Xanthium italicum inoculated by Alternaria zinniae was greatest when plants were subjected to temperatures of 15–20  C during the dew period and of 25  C after the dew period (Nehl and Brown, 2000). The effect of temperature on latent period and aeciospore production of Puccinia lagenophorae on Senecio vulgaris was determined by Kolnaar and Bosch (2001). The latent period decreased exponentially with increasing temperature. The present study suggests an increase in the exponential growth rate, with temperature. This increase in epidemic development was caused mainly by the effect of temperature on the latent period and on the net reproductive number. The effect of temperature on the sporulation curve appeared to be less important (Kolnaar and Bosch, 2001). In summary, weeds as well as biocontrol agents require certain optimum temperatures in order to grow and carry out their activities. For fungi and bacteria, temperature influences germination, infection, latent period, lesion development, sporulation, dispersal, survival, and the number of spores formed and released in a unit plant area (Agrios, 1997). Therefore, in order to achieve the best results in the biological control of weeds, the optimum temperature should be studied for specific weed–pathogen (control agent) interactions within the constraints of the local habitat conditions.

2.

Moisture

Availability and duration of moisture play a major role in microbial life stages (Colhoun, 1973; Hoagland, 1990). Moisture influences the initiation and development of plant diseases in many ways (Agrios, 1997). It plays a determining role in the distribution and spread of many pathogens; increases the succulence of host plants and thus their susceptibility to certain pathogens, has an activation effect on bacterial, fungal, and nematode pathogens before they can infect the plant; and has a direct effect on germination, infection, sporulation, dispersal, and survival of microbial propagules (Agrios, 1997). Most bacterial pathogens and also many fungal diseases are particularly favored by high moisture or high relative humidity. Abundant, prolonged, or repeated high moisture, whether in the form of rain, dew, or high humidity, is the dominant factor in the development of most epidemics caused by fungi, bacteria, and nematodes (Agrios, 1997). Mendi (2001) reported that leaf necrosis percentage caused by Ascochyta caulina in Chenopodium album plants increased with increasing relative humidity between 75 and 95%. The favored percentage of humidity may vary with the developmental stage of the microorganisms. For example, a moderate humidity and temperature favored hyphal growth, wheras a high humidity favored the germination of Uncinula necator (Rea and Gubler, 2001). In fungi, moisture affects fungal spore formation, longevity, and particularly

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the germination of spores, which requires a film of water covering plant tissues (Agrios, 1997).

3. Dew Period Spores or cells of most plant pathogens require a period in which there is a water film or free moisture (usually dew) over leaf tissues in order to germinate, penetrate, and infect the host (Boyette and Abbas, 1995). Free water in plant surfaces is naturally supplied by dew. Walker and Boyette (1986) reported that dew periods of 4 and 8 h enhanced the mortality of Cassia obtusifolia inoculated with Alternaria cassiae. TeBeest (1991) reported that optimal environmental conditions for the control of C. obtusifolia by A. cassiae included at least 8 h of free moisture at 20–30  C. Shabana et al. (1995) found that exposure of inoculated leaves of Eichhonia crassipes to at least 10 h of dew was conducive to a high level of disease caused by Alternaria eichhorniae. Mintz et al. (1991, 1992) showed that seedlings of Amaranthus albus were killed within 2 days after inoculation by Aposphaeria amaranthi with an 8-h dew period at 28  C. However, a 4-h dew period was not sufficient for plant mortality. Zhang and Watson (1997b) found that minimum dew periods to achieve 100% mortality of Echinochloa crus-galli, E. colona, and E. glabrescens caused by Exserohilum monoceras were 12, 16, and 8 h, respectively. Increasing the dew period length enlarged the range of temperature for maximum efficacy, and the use of an optimum dew period temperature decreased the dew period requirement. Morin et al. (1998) realized that long continuous dew periods (greater than or equal to 24 h) after inoculation of Ulex europaeus by Fusarium tumidum provided favorable conditions for infection. Ghorbani et al. (2000) reported that the most rapid and destructive development of disease caused by Alternaria alternata in Amaranthus retroflexus was achieved by a 24-h dew period at 20 and 25  C. High levels of disease in A. retroflexus were achieved as long as the dew period was longer than 12 h at 20 and 25  C. Leaf necrosis caused by Alternaria zinniae on Xanthium occidentale and X. italicum was 40% after 8 h of dew; however, the greatest necrosis percentage was observed with 18 h of dew (Nehl and Brown, 2000). A minimum dew period of 12 h was required for Dactylaria higginsii to produce severe disease on the weed of Cyperus rotundus (Kadir et al., 2000). Satisfactory levels of Epilobium angustifolium biocontrol by Colletotrichum dematium were achieved when the dew period was more than 20 h (Leger et al., 2001). The minimum dew period needed to achieve 100% mortality in Galium spurium caused by the fungus Plectosporium tabacinum was 16 h (Zhang et al., 2002). The disease development caused by Pyrenophora semeniperda in wheat leaves occurred in a logistic manner in response

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to the dew period, with maximum infection observed after 21 h compared with >48 h in wheat seeds (Campbell and Medd, 2003). Therefore, the dew period requirement varies in different plants and antagonists, and usually ranges from 6 h to more than 24 h depending on the pathogen and the weed host. In field situation, plants rarely sustain free water on the leaf surface for such long periods. Early application of the inoculum (i.e., just before dark) is suggested. Also, the formulation of spores in oil emulsions may decrease the absolute dew requirement by artificially extending the leaf wetness period.

4.

Delayed Dew Period

A delay in the occurrence of dew is another important factor affecting the activity of biocontrol agents in weeds. There is variation among pathogens in the extent to which they can withstand delay and interruptions in the dew period. Results of Walker and Boyette (1986) studies showed a delay of 1 or 2 days in the occurrence of dew tolerated without adversely affecting the efficacy of Alternaria cassiae in Cassia obtusifolia; however, the maximum rate of killing by this fungus was obtained with the shortest delay in the occurrence of dew after inoculation. In the weed Amaranthus albus, onset dew can be delayed for 2, 4, 8, 12, or 24 h without an apparent decrease in disease severity caused by Aposphaeria amaranthi (Mintz et al., 1992). Morin et al. (1998) reported that a delay of 24 h in dew did not affect the severity of Fusarium tumidum disease in Ulex europaeus. Mendi (2001) reported that leaf necrosis and plant death of Chenopodium album treated by Ascochyta caulina were only obtained when they were immediately transferred to high humidity conditions (>95%) (Fig. 3) and delayed dew significantly decreased disease severity. A single exposure to high humidity for 24 h imposed immediately after spore application gave significantly more disease than two 12h high humidity treatments separated by 12 h of incubation at low humidity. When exposure to high humidity after inoculation was delayed by 12 h, no disease development was observed (Mendi, 2001). Delaying the initiation of the dew period by 24 h significantly reduced disease development in Galium spurium caused by the fungus Plectosporium tabacinum (Zhang et al., 2002). A delay in the occurrence of dew may affect spore germination and viability of biocontrol agents on the plant surfaces. Will et al. (1987) and Morin et al. (1998) reported that hydrated spores are more metabolically active than nonhydrated spores. Also, hydrated spores may be more vulnerable to environmental stress (particularly low humidity). The latent period3 can also be affected by environmental factors, especially a delay in dew 3

Latent period: The time between infection and sporulation of the microorganism.

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Figure 3 Linear regression between periods of low humidity (<80%) after spraying and disease development in Chenopodium album plants 10 days after inoculation with Ascochyta caulina. Each point shows the mean of eight determinations (n ¼ 8) (Mendi, 2001).

(Jones, 1987). A delay in relative humidity and dew possibly changes the susceptibility of host plant tissues and its enzyme activities against growing microorganisms. However, research is needed to identify the mechanisms affecting individual weed–pathogen interactions in response to a delay in dew.

5.

Dew Temperature

Temperature during the wetness period influences the development of plant disease. TeBeest (1991) reported that the optimal dew temperature for infection of Anoda cristata by Alternaria macrospora was 15–25  C, with a maximum at 21.5  C. In Amaranthus albus, dew temperatures from 20 to 28  C were conducive for disease development of Aposphaeria amaranthi but disease sharply declined at 32  C with no mortality (Mintz et al., 1992). Maridha and Wheeler (1993) found that the disease severity of Sida spinosa by Colletotrichum malvarum was affected by dew temperature and was most severe at 24  C when given 16 h of dew. In this study, disease severity was significantly reduced at 20 and 28  C. The maximum disease incidence of oilseed rape inoculated with a spore suspension of Alternaria brassicae increased as the wetness period increased from 4 to 24 h after inoculation and as temperature increased to 20  C (Hong et al., 1996). When adequate dew was provided, 100% mortality occurred for all three Echinochloa spp. over a dew period temperature range of 20 to 30  C (Morin et al., 1998). Ghorbani et al. (2000) found that Alternaria alternata induced disease on Amaranthus retroflexus over a wide range of dew period durations and

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Figure 4 Effect of the length of dew period (hour) and dew temperature ( C) on disease development of Alternaria alternata in Amaranthus retroflexus plants treated at the four leaf stage. Linear regression analysis showed a significant difference for the length of dew period (P < 0.001), but no significant difference between dew temperatures (P ¼ 0.137).

temperatures. The most rapid and destructive development of disease was achieved by a 24-h dew period at 20 and 25  C. At longer dew periods (18 and 24 h), disease development was greater at high temperatures (20 and 25  C), whereas at a short dew period of 6 h, disease development was more severe at cooler temperatures (13  C) (Fig. 4). They also found that temperature after dew (postdew temperature) had a significant effect on disease development. The fungus of Dactylaria higginsii required a temperature of 25  C during the dew period to produce severe disease in the weed of Cyprus rotundus (Kadir et al., 2000). Satisfactory levels of Epilobium angustifolium biocontrol by Colletotrichum dematium were achieved when the temperature during the dew period was 30  C (Leger et al., 2001). The optimal dew temperature for disease development caused by the fungus Plectosporium tabacinum in Galium spurium was above 15  C (Zhang et al., 2002). The optimum dew period temperature for the conidial germination of Pyrenophora semeniperda in wheat was 23.6  C, 20.4  C for the production of infection structures on seedling leaves, and 23.7  C for floret infection. In this fungus, the temperature after the dew period significantly increased lesion development formed at 15  C compared to 30  C (Campbell and Medd, 2003). The effect of dew temperature on development of a particular disease after infection depends on the specific host–pathogen combination. Results of previous studies on different weed–pathogen combinations show that for most pathogens and weeds, the optimum temperature during dew and after

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inoculation ranges from 15 to 25  C. Since the duration of an infection cycle determines the number of infection cycles and, as a result, the number of new infections, it is clear that the effect of temperature on the efficacy of a biocontrol agent in a given season may be very great. The most rapid disease development usually occurs when the temperature is optimum for the development of pathogen and is above or below the optimum for the development of the host plant.

6.

Wind

Wind influences infectious plant diseases primarily by increasing the spread of plant pathogens and by increasing the number of wounds on host plants, which both increase infection (Agrios, 1997). The biological control agents, like most plant pathogens, are spread either directly by the wind or indirectly by insect vectors that can themselves be carried out over long distances by the wind. Wind is even more important in disease development when accompanied by rain. However, some spores such as basidiospores and some conidia and zoosporangia are quite delicate and do not survive long-distance transport in the wind. Wind speed has a strong influence on spore liberation and on the dissemination of fungal propagules (Hoagland, 1990). For example, Markell and Francle (2001) reported that wind speed had a significant effect on the spore dispersal of Fusarium head blight; therefore, it may spread the biological control agent in the area. However, wind accelerates drying surfaces of wet plants. If plant surfaces dry before penetration of the pathogen, any germinating spores or bacteria present on plant surface are likely to desiccate and die, and no infection will occur (Agrios, 1997). Therefore, biological control agents should be applied when there is the least possibility of wind.

7.

Light

The intensity and duration of light and darkness may increase or decrease the susceptibility of plants to infection and may also affect the severity of the disease (Agrios, 1997). Light intensity influences penetration of the host by the fungi. High light intensity is optimum for stomatal penetration (controlling opening by light receptors existing in the stomatal guard cells) of Septoria tritici in wheat (Colhoun, 1973). Etiolated plants are usually more susceptible to nonobligate parasites (e.g,. lettuce and tomato plants to Botrytis), but are less susceptible to obligate parasites (e.g,. wheat to Puccinia) (Agrios, 1997; this may be due to less reactions and metabolisms in etiolated plants. The daily light:dark cycle and seasonal variation in day

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length can also directly influence microbial activities, e.g., sporulation in numerous fungi. The intensity of light may directly affect the survival of propagules on the leaf surface and indirectly influence the probability of infection by pathogens by moderating host metabolism (Colhoun, 1973). Sun and Yang (2000) reported that increasing light intensity from 80–90 to 120–130 mmol m−2 s−1 increased the optimal temperature for production of the apothecium in Sclerotinia sclerotiorum. They found that apothecia were smaller at low light intensity than those produced at high light intensity at any temperature. The quality of light (wavelength) has an effect on disease development. In both greenhouse and field trials, the light quality and quantity could well affect the results of the experiment. Fortnum et al. (2000) reported that mulch color altered tomato plants resistance to root knot nematode infection by changing the distribution of mass in axillary shoots. In wheat, an initial dark phase during the dew period was necessary for Pyrenophora semeniperda infection (Campbell and Medd, 2003). These results emphasize the need to incorporate the interactive effects of light with other environmental factors on the weed and microbes to obtain better understanding and more predictable performance of the biocontrol agent.

C. SOIL ENVIRONMENT Physical, chemical, and biological soil characteristics can have both direct and indirect effects on the chances of success of the biocontrol agent applied as either foliar or soil treatment.

1. Soil Nutrients Successful colonization of plants by antagonistic pathogens requires efficient utilization of nutrient resources available in host tissues (Snoeijers et al., 2000). Researchers found various results regarding soil fertility and disease development in different plants and pathogens. This is regarding plant and pathogen species, plant age, soil characteristics, and environmental condition and their interactions. The most commonly studied element in relation to disease in plants is nitrogen. Separating direct and indirect effects of the nitrogen supply on the host–pathogen interaction is difficult because their influence on the dynamics of the pathogen via crop growth, crop physiology, and crop microclimate is confounded (Sasserville and Mills, 1979). Direct changes in host susceptibility to infection at a higher nitrogen supply have been postulated but are still controversial (Savary et al., 1995). It is known, for example, that fertilization with large amounts of nitrogen increases the susceptibility of pear to fire blight (Erwinia amylovora), wheat

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to rust (Puccinia) and powdery mildew (Erysiphe) (Agrios, 1997), rice to sheath blight (Rhizoctonia solani) (Cu et al., 1996), and winter wheat to Rhizoctonia blight (Colbach et al., 1996). Growth and disease responses to high levels of NH4-N have been documented with a range of plants and pathogens (Marti and Mills, 1991; Sasserville and Mills, 1979; Smiley and Cook, 1973). Ghorbani et al. (2002) found that disease development caused by Ascochyta caulina in Chenopodium album increased with increasing plant tissue nitrogen. Therefore, a supply of additional nitrogen can increase disease development. When nitrogen is not limited, pathogens can easily acquire nitrogen and will cause more disease on these plants than on host plants. In contrast, the reduced availability of nitrogen may increase the susceptibility of plants to microorganisms. For example, the susceptibility of tomato to Fusarium wilt, many solanaceous plants to Alternaria solani early blight and Pseudomonas solanacearum wilt, sugar beets to Sclerotium rolfsii, and most seedlings to Pythium damping off were increased with reducing nitrogen availability (Agrios, 1997). Rosen and Miller (2001) reported that nitrogen deficiency can increase the incidence of early blight (Alternaria solani) infestation in potato. Similarly, ammonium fertilizer decreased disease levels and infection cycles of take-all (Gaeumannomyces graminis var. tritici) in wheat (Colbach et al., 1996). A nitrogen-limiting environment may be one of the cues for disease symptom development during growth of the pathogens in some species of plants. Apart from possible effects of nitrogen supply on shoot architecture and the microclimate (humidity) affecting germination of the pathogen, an increased nitrogen supply may have potentially affected cuticular properties, cell wall structure, and metabolic activity (Argios, 1997). Biocontrol agent performance may be affected by other macro- and micronutrient availability. Increasing soil phosphorus has shown to reduce the severity of take-all disease (Gaeumannomyces graminis) of barley and potato scab (Steptomyces scabies), but to increase the severity of cucumber mosaic virus on spinach and of leaf and glume blotch of wheat caused by Septoria (Argios, 1997). Increasing potassium has also been shown to reduce the severity of numerous diseases, including stem rust of wheat, early blight of tomato, and stalk rot of corn, although high amounts of potassium seem to increase the severity of rice blast (Magnaporthe grisea) and root knot nematode (Meloidogyne incognita) (Argios, 1997). A high level of calcium reduces the severity of several diseases such as Fusarium oxysporum, but increases Streptomyces scabies in potato (Argios, 1997). Results of studies conducted by Duffy et al. (1997) showed that the biocontrol activity of Trichoderma koningii for controlling take-all disease in wheat was positively correlated with iron, nitrate-nitrogen, boron, copper, soluble magnesium availability, and percentage clay and was negatively correlated with soil pH and available phosphorus.

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2.

Soil Reaction

The occurrence of some diseases is greatly influenced by pH. An antagonistic pathogen of Pythium oligandrum was able to control pre- and postemergence damping off (Pythium ultimum) of sugar beet at pH 7.0 and 7.5 only (tested range of pH was from 4–8) (Holmes et al., 1998). Yoshida and Kobayashi (1997) found that root tumors of melon occurred at a soil temperature of 20–35  C and a soil pH of 5.5–7.5. There was no disease at a soil temperature below 20  C and a soil pH level below 5.5. Blank and Murray (1998) reported that soil pH from 4.7–7.5 did not have a significant influence on germination of Cephalosporium gramineum conidia in the soil. Also, the interaction between soil pH and matric potential on germination of this particular pathogen was not significant. Sclerotial germination of Sclerotium rolfsii was greater in acidic soil than alkaline soil. The percentage of infected peanut stems by S. rolfsii was greater at a soil pH of 5.6 than in more alkaline soil; however, disease did develop at a soil pH of 8.7 and 9.8. (Shim and Starr, 1997). Studies on the effect of soil characteristics on Fusarium wilts in banana indicated that a relationship exists between the disease incidence and the values of pH, cation exchange capacity (CEC), sodium (Na) in solution, and iron (Fe) (Dominguez et al., 1996). It is therefore clear that when the soil reaction influences disease, it may not be attributable only to direct effects on the pathogen. Moreover, soil acidity may influence the availability of soil nutrients and so affect plant growth and vigor, which in turn, through affecting a change in the microclimate within a crop, indirectly affect infection and disease development (Agrios, 1997). In these and many other diseases, the effect of soil acidity seems to be principally on the pathogen, presumably by the effect on the enzyme controlling the metabolic processes inside the pathogen. However, weakening of the host through altered nutrition that is included by soil acidity may affect the incidence and severity of some diseases.

3.

Soil Microorganisms

Soil microbial communities are fundamental to the development of agricultural systems that are less dependent on nonrenewable resources (Kremer and Li, 2003). Agricultural practices (e.g., increasing organic matter) that enhance soil microbial populations and soil enzyme activities increase the potentiality for the development of weed-suppressive biocontrol agent communities. Growth of Chenopodium album in a potato crop was only 25% in soils receiving annual inputs of green manure, composted plant residues, and beef manure compared to nonamended soils (Gallandt et al.,

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1999). Hoitink and Boehm (1999) suggested that high levels of soil hydrolytic enzymes associated with soils with both high organic matter and microbial biomass were correlated to the pest suppressive characteristics in a soil. Soil and crop management systems that increase organic matter in the soil surface provide a source of readily available carbon substrates that can support increased microbial activity (Kremer and Li, 2003). Therefore, several farming practices that maintain or increase soil organic matter can be used to manage soil microorganisms and microbial activity to optimize potential weed suppression. Other soil-related factors, such as soil moisture and temperature, may influence the epidemiology and soil microorganism communities. Pathak and Srivastava (2001) reported that soil moisture and soil temperature both had cumulative effects on the development of Rhizoctonia bataticola in a sunflower crop. In this study, with increasing the soil moisture and also with decreasing soil temperature, disease development decreased. Soil organic matter status, such as plant residues, microorganisms, and pesticides affects the growth and development of plant pathogens by supplying more nutrient sources or a favorable/ unfavorable environment for the pathogen (Newman, 1985). In conclusion, the study and identification of potential soil-related factors affecting biocontrol activity of the agent are necessary to optimize biocontrol treatments for recommended sites. Agricultural practices, especially crop rotation and tillage systems that apply locally, also must be carefully engineered to suit for soil quality and crop growth while stimulating activities of beneficial microorganisms and biocontrol agents.

VI. FORMULATION OF BIOLOGICAL CONTROL AGENTS For increasing the efficacy of a biocontrol agent against environmental constraints, it should be formulated appropriately. However, it is not easy to formulate biological control agents into effective products because, as living organisms, their viability must be preserved throughout processing and storage (Auld et al., 2003; Hoagland, 1990; Scher and Castagno, 1986). In other words, the “active ingredient” of bioherbicides is a living organism; therefore, extra care is required in shipping, storage, and handling. Perhaps the biggest single constraint for the commercial development and marketing of bioherbicides is development of an appropriate formulation (Greaves et al., 1999). Shelf life is very important for a commercial bioherbicide; the longer the shelf life of the product, the greater the chance that it will be developed, registered, and commercialized.

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Wound inoculation to plants overcomes several limitations to infection and provides a moist environment for disease development (Auld et al., 2003). In this method, the antagonistic agent is applied to the wounded weed surface caused by mowing, harrowing, or other mechanical equipment. Wounding improves the performance of some potential bioherbicides; however, it probably has its greatest role in the control of large woody plants (Auld et al., 2003). It is not always possible to cause damage and wound the weeds; therefore, formulation of biocontrol agents is a critical component to help the antagonistic pathogen for germination and infection in a weed (Zhang et al., 2003). In formulation of biocontrol agents, various adjuvants may be involved. The term adjuvant includes a wide range of compounds, such as surfactants, antievaporation agents, inert carriers, antifreezing compounds, humectants, stickers, and micronutrients (Zhang et al., 2003). Some materials have received much attention, including various kind of emulsions, organosilicone surfactants such as Silwet L-77, hydrophilic polymers, and alginate-, starch-, cellulose-, or gluten-based encapsulation systems (Charudattan, 2001). Materials and components (adjuvants) used in the formulation must be carefully screened for compatibility and toxicity or inhibitory properties toward the biocontrol agent (Zhang et al., 2003). The formulation type will also affect the choice of application tools and methods, e.g., certain emulsions cannot be applied by conventional sprayers (Charudattan, 2001). Moreover, a satisfactory formulation of any product ideally has a long shelf life, relative ease of application, efficacy, and low cost (Auld et al., 2003). Therefore, identifying the appropriate formulation of a biocontrol agent for a wider range of environmental conditions is a critical step of its commercial product development. Formulation development has followed two main procedures, either as liquid sprays or solid materials. Liquid formulations of mycoherbicides are usually the best suited for use as postemergence sprays and are used primarily to incite leaf and stem disease. Compared to fungal bioherbicides, bacterial pathogens such as Xanthomonas campestries pv. poae and Pseudomonas syringae pv. tagetis are very easy and quick to produce in liquid cultures and to store as frozen or freeze-dried pellets. Even simpler to produce, store, and use are mechanically transmitted viruses such as Araujia mosaic virus and tobacco mild green mosaic virus U2, which can be multiplied on tolerant (nonlethal) hosts, freeze dried, and stored for several years without loss of infectivity (Charudattan, 2001). Conversely, pathogens that infect at or below the soil surface are probably best delivered in a solid or granular formulation (Boyette and Abbas, 1995).

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A requirement for extended periods of free water retention for infection continues to limit the development of many potential bioherbicides. It is necessary to maintain the deposit on the leaf surface for some time after application of an antagonistic pathogen to germinate and penetrate in plant tissues. Many crop protection agents are applied by deposition on the foliar surface and a number of techniques have been devised for this purpose (e.g., use of hydrophilic polymers such as gums and polyacrylamides, surfactants, stickers, emulsions, and electrostatically charged droplets and sometime dusts) (Chittick and Auld, 2001). The simplest liquid formulation used most frequently in the early stages of a bioherbicide evaluation is a suspension of spores (conidia) in water (Greaves et al., 1999), which often contains a small amount of wetting agent [such as 0.1% (v/v) of Tween 20] (Auld et al., 2003). These formulations are generally used as standards against which to compare more complex formulations. Wetting agents such as the Tweens facilitate spread on foliar surfaces, and silicone-polyester copolymers such as Silwet L-77 will aid penetration of stomata and lenticels by bacterial spores. However, by decreasing the surface tension of the applied suspensions, wetting agents will tend to increase the rate of water evaporation (Auld et al., 2003). In order to decrease the water loss rate, a range of other materials (for example, humectants such as glycerol and sorbitol) (Greaves et al., 1999) might be used in formulation. Complex polysaccharides have appealed as stickers in formulations; however, they are rather humectants properties as polymers than stickers (Auld et al., 2003). Simple oil emulsions (e.g., 10% oil and 1% of an emulsifying agent) showed promise in reducing dew dependence and improving the efficacy of biocontrol agents with various modifications of this type of simple emulsion (Auld et al., 2003; Lawrie et al., 1997; Shabana, 1997). Ghorbani (2000) confirmed the effectiveness of a rapeseed oil emulsion applied with Alternaria alternate against the weed Amaranthus retroflexus. This oil emulsion increased disease development and decreased the length of dew period requirements. In this study, A. alternata conidia are thought to be supplied with water at the critical germination and infection stages. The mechanism by which simple emulsions may reduce dew dependence and improve efficacy is not always clear. It is thought that emulsion capture added water or moisture from the atmosphere or from the plant surfaces and enveloped it in the oil matrix (Greaves et al., 1999). The oil from emulsion may also permeate the intracellular and intercellular spaces (Greaves et al., 1999), which may assist the infection process. One study found that both corn oil

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emulsion and a surfactant (Silwet) stimulated the germination of Alternaria helianthi on common cocklebur leaves (Abbas and Egley, 1996). Therefore, the oil could act as a germination stimulator for fungal spores or may damage the plant cuticle, thereby assisting the entry of the pathogen (Lawrie et al., 2000). Invert emulsions consist of a continuous oil phase that contains water droplets (Auld et al., 2003). They are effective carriers for the application of fungal plant pathogens to weeds, primarily because they retard evaporation of the dispersed water droplets during and after application (Connick et al., 1991). Application of herbicides in invert emulsions at low volume may also retard drift and prolong available moisture in the spray droplet, thus allowing more time for the bioherbicide to penetrate into the leaf surface (Bryson et al., 1990). Where inverts are used the pathogen is more likely to have access to free water over an extended period of time, promoting germination and infection of the target weed. For example, greenhouse results using Alternaria cassiae against Cassia obtusifolia with an application of invert emulsions showed that the quantity of paraffin wax and droplet deposit size determined the rate of water evaporation; therefore, invert emulsion could be both a successful delivery system and a water source for A. cassiae (Hoagland, 1990). Although these formulations have been shown to overcome dew requirements, they have two main disadvantages: (1) they contain a high percentage of oil (>30%), which makes them expensive and very viscous, requiring special spraying equipment such as air-assist nozzles; and (2) the high oil content may cause phytotoxic effects on nontarget plants (Auld et al., 2003). In order to overcome the aforementioned disadvantages in the invert emulsions, scientists recommend novel bioherbicide formulations such as using a complex emulsion, which is a water–oil–water (WOW) emulsion (Auld et al., 2003). In WOW emulsions, microscopic oil droplets containing water are dispersed in a continuous phase of water. This is made by emulsifying an invert emulsion of water in oil into water; therefore, it contains at least one lypophilic surfactant, at least one hydrophilic surfactant, oil, and water. The oil content can be varied but is typically only from 1 to 5% and the complex emulsion can be sprayed with conventional equipment (Auld et al., 2003). The use of hydrophilic polymers in bioherbicides is also recommended by many scientists. Shabana et al. (1997) evaluated eight hydrophilic polymers including alginates, gums, a polyacrylamide, a cellulose derivative and a mucilloid. They found that Gellan gum, alginates and the polyacrylamide all improved pathogenicity of Alternaria eichhorneae. A range of three natural and four artificial polymers, including gums and polyacrylamides, were tested by Chittick and Auld (2001) in Colletotricum orbiculare and weed Xanthium spinosum, and results showed that all polymers were nontoxic to

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fungal spores and thus suitable for use in bioherbicide formulations. Loss of water from deposits of liquid formulations may be considered by adding a water-retaining coformulant. Netland et al. (2001) examined the waterretaining properties of polyvinyl alcohol (PVA) and polyvinylpyrrolidine (PVP) (compounds polymerized by oxygen in the air to form a protective film across the leaf), water-lock (a water-absorbent starch), carrageenan (a plant gum from Eucheuma spinosa), xanthan gum (a microbial polysaccharide), sodium alginate (a polysaccharide from seaweed), and Psyllium-Metamucil (a plant-derived polysaccharide) alone and in combinations. They found that all those polymers reduced the evaporation of water; however, Carageenan in combination with PVA had the best water retention properties with only a 30% loss during 1 h. In conclusion, application of adjuvants in formulation may enhance the activity of the biocontrol agent by (1) prolonging water retention to overcome the dew period requirement, (2) adding nutrients to maintain fungal viability and to stimulate spore germination, penetration, and infection, (3) modifying leaf wettability to improve spore deposition and retention on sprayed leaves, and (4) mixing with proper filler for an extended shelf life.

B. FORMULATION FOR SOIL APPLICATION Soil texture, nutrients, microbial communities, and moisture contents vary considerably between sites and affect the competition and performance of the biocontrol agent as an introduced microorganism to the area. Therefore, a proper formulation should be able to improve the predictability of the biocontrol agent activity in different areas. There are various products that might be used for solid formulations. Several types of grain (rice, barley, millet, and wheat) have been used as growing media for biocontrol agents. After a period of incubation the colonized grain is dried and usually milled finely for application (Auld et al., 2003). The first reproducibly uniform and reliable solid carrier was an alginate-based granular formulation of fungal spores (Greaves et al., 1999). Walker and Connick (1983) developed an elegant method of encapsulating bioherbicide fungi in calcium alginate. Fungal propagules were placed in a sodium alginate solution and this suspension was added dropwise to a calcium chloride solution and dried. This technique has been widely used and modified by many researchers. Connick et al. (1991) developed an encapsulation process that they termed “Pesta. ” The fungal suspension was mixed with wheat flour and kaolin clay to form a dough, which was kneaded and rolled into thin sheets. The dried sheets were then ground into granules. A pasta-like process was used by Boyette and Abbas (1995) to produce granules by mixing semolina wheat flour and kaolin clay with fungal

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propagules contained in a liquid component (either water or residual liquid growth medium). The mixture was kneaded into dough, rolled into thin sheets with a pasta press, and air dried for 48 h. The sheets were then milled and sieved to obtain uniformly sized granules. An alginate formulation of Alternaria eichhorniae to control Eichhornia crassipes was used, and results suggested that 4 weeks after applying this mycoherbicide the treated leaves became diseased and died and the biomass of treated plants decreased by 29% from the initial weight (Zhang and Watson, 1997c). A wheat brankaolin granular formulation of Trichoderma harzianum used in the control of seed rot and damping off in chickpea incited by Rhizoctonia solani was used successfully by Prasad and Rangeshwaran (2000). Ghorbani (2000) applied Alternaria alternata granules, made by mixing kaolin, semolina, and Alternaria spores (as described by Greaves et al., 1999), and results showed that the application of granules caused disease development in Amaranthus retroflexus seedlings, but considering the high amount of granule requirement for that pathogen and weed, this formulation was not economically practicable and needed to be improved. For the biological control of Chenopodium album, Netland et al. (2001) incorporated Ascochyta caulina spores into granules made of strong white bread flour, kaolin, and a suspension of 5.6 106 conidia ml−1 in 0.1% (v/v) Sylgard 309 solution. Isolates of Rhizoctonia spp. in Pesta and rice flour formulations were used, and results showed that storage of this formulation at 4  C significantly improved spore survival compared to storage at 25  C (Honeycutt and Benson, 2001).Various modifications of this technique, using different flours, additives such as vegetable oil, starch, pyrophyllite, and vermiculite, as well as extrusion and fluid bed drying processes, have been reported by Daigle and Connick (2002). Granular formulations are often better suited for use as preplant or preemergence mycoherbicides than spray formulations because the granules provide a buffer from environmental extremes; the granules can serve as a food base for the fungus and are less likely to be washed away from treated areas than spores in a liquid media (Boyette and Abbas, 1995). Although it is possible to use granular formulations to inoculate plant foliage, especially if the granules have a sticky surface and the plant has a rosette of leaves at or near the soil surface, this approach has been limited to soil inoculation (Greaves et al., 1999). Microbial herbicide granules are generally 0.3–2.0 mm in diameter, however, the soil inoculant can be prepared as a dust, with particles of 3–50 m diameter (Greaves et al., 1999). For example, pasta granules of Alternaria spp. or Colletotrichum sp. with 0.6–1.4 mm diameter killed more weeds (68 to 100%) than smaller granules (Greaves et al., 1999). The granule size is important in viability of biocontrol agent in solid formulations. Shabana et al. (2003) also found that propagules viability in smaller sizes of Pesta granules of Fusarium oxysporum were less than larger size granules.

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Grinding may cause damage in spores or propagules of fine particles in granule formulations (Connick et al., 1991). However, this effect of grinding might be different in various spore types and microorganism species. Encapsulation methods offer possibilities to apply bioherbicides as dry material to soil, water, and aerial plant surfaces (Charudattan, 2001). The delayed release of the agent until suitable environmental conditions occur or when contact with the host is achieved is also beneficial (Shabana et al., 2003). However, because a moist condition is needed for fungal growth and infection, the main limitation in the use of solid forms of bioherbicides is moisture availability in the field, especially in dry and semidry climates. Moreover, the living active ingredient in the solid bioherbicide must survive during that dry period in the field. The viability of living organisms in granular formulations during storage may be influenced by the nutritional amendments added to the formulation. For example, sucrose can enhance spore germination, protect microorganisms during drying, and extend the survival of the microorganism during storage (Caesar and Burr, 1991; Shabana et al., 2003). Optimizing water activity during granule production and storage, incorporation of suitable adjuvants, and storage at cool temperatures all contribute significantly to preservation of the viability of the biocontrol agent (Shabana et al., 2003).

VII. LIMITATIONS AND JUSTIFICATIONS OF BIOLOGICAL WEED CONTROL The development of biological control can be faced with serious limitations: 1. In classical biological weed control, there is the possibility that after introduction a biocontrol agent organism from other continents moves to nontarget species and becomes another problematic pest. Risk assessment studies are an important and integrated issue in weed biocontrol projects (Scheepens et al., 2001). 2. The market for bioherbicides is not big enough to earn back the registration costs in a reasonable period of time, and therefore registration can be a limitation to development (Scheepens et al., 2001). 3. Most biocontrol agents have too narrow a host range, whereas many applications demand effectiveness over a broad range of weed species (Quimby et al., 2002); also, once a weed species is removed by a highly selective agent, it may simply be replaced by other weed species that are more difficult to control (Scheepens et al., 2001).

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4. There is a limited commercial interest in this approach to weed control due to the development of herbicide-resistant crops through genetic engineering, which is currently advocating the use of chemical herbicides (e.g., Roundup) (Quimby et al., 2002) and the fact that markets for biocontrol agents are typically small, fragmented, highly specialized, and consequently the financial returns from biocontrol agents are too small to be of interest to big industries (Charudattan and Dinoor, 2000). 5. The complexities in production, formulations, and assurance of efficacy and shelf life of the inoculum can further limit bioherbicide development (Charudattan and Dinoor, 2000; Quimby et al., 2002). Typically, each bioherbicide is used in a highly specific way to control a single weed species. From an economic point of view, it would be attractive to develop a bioherbicide that can control several weed species. This might stimulate commercial interest in this technology. In a “multiple-pathogen strategy,” three or more pathogens are combined at optimum inoculum levels and sprayed onto the weeds in post- or preemergent applications (Charudattan and Dinoor, 2000). A few experimental attempts have been made to combine more than one pathogen to control one or more weeds (Charudattan, 2001). The feasibility of controlling several weeds with three pathogens (Drechslera gigantea, Exserohilum longirostratum, and Exserohilum rostratum) has been demonstrated in the field. Results showed that applying these three pathogens caused severe foliar blighting and killed 4-week-old plants of Digitaria sanguinalis, Dactyloctenium aegyptium, Panicum maximum, Sorghum halopense Cenchrus echinatus, Panicum texanum, and Setaria gluaca (Chandramohan, 1999; Chandramohan et al., 2000). In another study, four host-specific fungal plant pathogens (Phomopsis amaranthicola, Alternaria cassiae, Colletotrichum dematium, and Fusarium udum) were applied in a single postemergent spray and the mixture was able to control 100% of three different weed species, including Senna obtusifolia, Crotalaria spectabilis, and Amaranthus retroflexus (Chandramohan and Charudattan, 2003). Results demonstrated the feasibility to control three weeds simultaneously with different fungi without a loss of efficacy or alterations in the host specificity of each fungus in the given mixture. Therefore, application of several host-specific fungal pathogens in a bioherbicide mixture as a multicomponent bioherbicide system may be advantageous for the further development of simultaneous, broad-spectrum weed control. However, as Dorn et al. (2003) concluded, mixed species infestations can have different effects on host plants depending on the antagonistic species involved and the presence of other nonhost plant/weed species in the field.

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Another novel approach is the use of broad-spectrum pathogens. For example, Pseudomonas syringae pv. tagetis as a broad-spectrum bacterial pathogen causes apical chloresis on several species of Asteraceae family with the aid of an organosilicone surfactant such as Silwet L-77 or Silwet 408 (Charudattan, 2001). Use of a wide host range pathogen such as Sclerotinia sclerotiorum in a host-restricted manner with the help of genetic and nutritional engineering is another novel approach (Charudattan, 2001). S. sclerotiorum is a fungal pathogen reported to attack an excess of 400 different plant species (Charudattan, 2001). Risk assessment in the wide host range biocontrol agent has much more importance. Microorganisms can potentially be modified to increase pathogenicity by genetic transformations with genes for virulence from other species, by increasing the endogenous expression of genes, or by transferring from other organisms by protoplast fusion (Gressel, 2002). An improvement in the efficacy of plant pathogens used for weed control is possible by recombinant DNA methods (practical use of genetically engineered pathogens may be difficult due to regulatory restrictions, e.g., organic farming) (Charudattan and Dinoor, 2000). For example, an attempt was made to modify the host range and to improve the virulence of Xanthomonas campestris by using genes encoding bialaphos production. However, more work is needed to characterize genes that may be useful for improving the efficacy of bioherbicidal pathogens (e.g., pathogenicity, virulence, host range, and production of enzymes, toxins, and hormonal compounds) (Charudattan and Dinoor, 2000). Increasing virulence, especially by gene transfer, requires extreme care due to environmental impact, i.e., the possibility of increasing the host range to include other crops (Gressel, 2002). In this regard, future research should consider the identification and cloning of genes for virulence, host susceptibility, and host–parasite recognition (Charudattan, 2001). Plant pathogens hold enormous potential as weed biocontrol agents. In conclusion, in addition to the use of plant pathogens as biocontrol agents, it is likely that pathogen-drived genes, gene products, and genetic mechanisms will be exploited in the near future to provide novel weed management systems (Charudattan and Dinoor, 2000).

VIII. OVERALL CONCLUSION Huge advances are being made in the discovery and development of biological control products, but various factors have limited the application of biological control methods in crop production systems. Many of the limitations to bioherbicide advancement have been suggested with low pathogen virulence and fastidious environmental conditions identified as the key

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restraints to overcome. Many research programs have studied different aspects of the use of plant pathogens for biological weed control. The study of the effects of individual environmental factors can be regarded as the first step in understanding limitations to the success of a biological control agent. Biological weed control methods are more dependent on specific environmental conditions than on chemical methods (Charudattan, 2001). Knowledge of these factors allows the timing of application of biological control agents to be optimized. The challenge is made more difficult by the fact that the environment in the field consists of a multitude of factors that not only interact with each other, but also rarely remain constant for any substantial length of time. The aforementioned literature review attempted to address the importance of environmental factors and also the interaction of those factors in the activity of biocontrol agents, but more work, perhaps with the inclusion of modeling and molecular biology, would be profitable in respect to many biocontrol agents. In order to break or at least weaken the link between disease and natural environment, it is necessary to provide the potential biocontrol agent with a microenvironment tailored to its needs. This entails the use of formulation technology (Greaves et al., 1999), molecular biology, and novel approaches in biological weed control (Charudattan, 2001). Improvements in strain selection, formulation, awareness of interaction of local soil and environmental conditions with weed and biocontrol agent, and integrated biological control methods with other nonchemical weed control strategies to provide effective more sustainable weed control are recommended.

REFERENCES Abbas, H. K., and Egley, G. H. (1996). Influence of unrefined corn oil and surface active agents on the germination and infectivity of Alternaria hellanthi. Biocontrol Sci. Technol. 6, 531–538. Agrios, G. N. (1997). “Plant Pathology”. Academic Press, San Diego. Aldrich, R. J., and Kremer, R. J. (1997). “Principles in Weed Management”. Iowa State University Press/Ames. Auld, B. A., Hetherington, S. D., and Smith, H. E. (2003). Advances in bioherbicide formulation. Weed Biol. Manag. 3, 61–67. Barbosa, P. (1998). “Conservation Biological Control”. Academic Press, San Diego. Blank, C. A., and Murray, T. D. (1998). Influence of pH and matric potential on germination of Cephalosporium gramineum conidia. Plant Dis. 82, 975–978. Boyette, C. D., and Abbas, H. K. (1995). Weed control with mycoherbicides and phytotoxins. In “ACS Symposium Series; Allelopathy Organisms Process, and Application”, pp. 280–299. American Chemical Society. Bryson, C. T., Wills, G. D., and Quimby, P. C. (1990). Low volume invert emulsions for purple nutsedge (Cyperus rotundus) control. Weed Technol. 4, 907–909. Burge, M. N. (1988). “Fungi in Biological Control Systems”. Manchester University Press, UK.

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NUTRIENT STOCKS, NUTRIENT CYCLING, AND SOIL CHANGES IN COCOA ECOSYSTEMS: A REVIEW Alfred E. Hartemink ISRI–World Soil Information, 6700 AJ, Wageningen, The Netherlands

I. II. III. IV.

V. VI. VII. VIII.

Introduction Climatic and Soil Conditions of Study Areas Nutrient Stocks Nutrient Cycling A. Nutrient Removal: Yield B. Nutrient Removal: Leaching C. Nutrient Removal: Soil Erosion D. Addition of Nutrients E. Transfer of Nutrients Nutrient Balances Soil Changes Under Cocoa Discussion Concluding Remarks Acknowledgments References

It is generally assumed that agricultural systems with perennial crops are more sustainable than systems with annual crops. Soil erosion is negligible and perennial crops have more closed nutrient cycling. Moreover, inorganic fertilizers are used more commonly in cash crops such as perennial crops so that soil fertility decline and nutrient mining are less likely to occur. In the past decades, considerable research has been devoted to the quantification of nutrient stocks and nutrient cycling in agro-ecosystems. This article reviews the main stocks and flows of nutrients in cocoa ecosystems for several cocoagrowing regions in the tropics. Most of the nitrogen is found in the topsoils, and less than 10% of the total N stock is in the cocoa and shade trees. Nitrogen in the annual litter fall is about 20 to 45% of the total N in the vegetation and 2 to 3% of the total N in the soil. The accumulation of potassium is low in cocoa ecosystems, and in most systems the total amount in the biomass is equivalent to the available P content in the topsoil. Phosphorus in the annual litter fall is about 10 to 30% of the total P in the vegetation and 10 to 40% of the available P in the soil. Potassium is a major nutrient in mature cocoa. Stocks of exchangeable K in the topsoil 227 Advances in Agronomy, Volume 86 Copyright 2005, Elsevier Inc. All rights reserved. 0065-2113/05 $35.00

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A. E. HARTEMINK vary from 100 to 550 kg ha
1, and high K levels in the soil correspond to high K levels in the vegetation and litter. Partial nutrient balances were calculated that compares the losses, addition, and transfer of N, P, and K. The nutrient balance is negative in the absence of inorganic fertilizers, especially for K. Rainwash and litter fall are key components in the cycling of nutrients of cocoa ecosystems. The amount of nutrients transferred by rainwash is less than 8 kg ha
1 for N and P but varies from 38 to more than 100 kg ha
1 year
1 for K. Most soils under cocoa had a lower fertility when compared to primary forest, although soil chemical properties seem to settle at equilibrium levels. This review shows that large amounts of nutrients in cocoa ecosystems are transferred each year and that such nutrient cycling is # 2005, Elsevier Inc. essential for maintaining cocoa production.

I. INTRODUCTION Nutrient cycling is a relatively new concept in ecological research that has made considerable progress since the seminal work of Nye and Greenland (1960) on nutrients flows and pools in shifting cultivation systems. It has been used in many areas of ecological research, and in the last decade the developments have been especially large in research on agroforestry systems (Sanchez, 1995) and in the quantification of stocks and flows in nutrient balance studies of smallholder agriculture. It is often mentioned that the quantification of nutrient flows and stocks is an important step in the development of sustainable land use systems, especially on low-fertility soils of the humid tropics (Schroth et al., 2001; Smaling et al., 1999). Nonetheless, the number of studies on nutrient cycling and balances on perennial plantation crops is limited, despite the importance of plantation cropping for the economies of many developing countries (Hartemink, 2003). For example, it was not until the early 1980s that a N balance was available for coVee and cocoa, as available data for N cycling in coVee and cocoa plantations were scarce (Robertson, 1982). Cocoa—food of the gods (Theobroma cacao L.)—is a major cash crop in many tropical countries. Cocoa is produced within 10  N and 10  S of the equator where the climate is suitable for growing cocoa trees (Fig. 1). West Africa has been the center of cocoa cultivation for many decades, as twothirds of the world’s cocoa is produced in West Africa. However, in 1900 Africa’s share of the total world cocoa production was a mere 17% (Duguma et al., 2001). Currently, the main producers are the Ivory Coast, Ghana, and Indonesia. The Ivory Coast is the largest cocoa producer with a 95% increase in output over the 1980s and it now holds more than 40% of the world market. In Ghana, cocoa export accounts for about 60% of the country’s

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229

Figure 1 Main cocoa-producing countries in the world (map from the International Cocoa Organization).

foreign earnings, whereas in Indonesia, the revenue of cocoa is over $600 million per year. Yields in 2001 were about 540 kg ha
1 in the Ivory Coast and 280 kg ha
1 in Ghana and Nigeria. A considerable part of the cocoa in the world is produced by smallholders, and the International Cocoa Organization (ICCO) estimates that approximately 14 million people are directly involved in cocoa production. The most significant contribution to the rise in global output is expected from Africa where production is forecast to rise by close to 9%, followed by the Americas, whereas production in the Asia and Oceania region is likely to remain static. Africa remains the main cocoa-producing region, accounting for 69% of world cocoa production in 2002 and 2003, followed by Asia and Oceania (18%) and the Americas (13%) according to ICCO (2003). Compared to other agricultural activities, cocoa has been a leading subsector in the economic growth and development of several West African countries (Duguma et al., 2001). The first systematic research on nutrient cycling in cocoa was started in Cameroon by Boyer in the early 1970s (Boyer, 1973). In Malaysia, where the area under cocoa rapidly expanded in the 1980s, data related to cocoa growth and nutrition were insuYciently available and studies were undertaken to formulate more precise and eYcient fertilizer programs to reduce

230

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manuring costs (Ling, 1986; Thong and Ng, 1978). In the 1980s several studies were conducted in South America. Aranguren and co-workers (1982a) conducted nutrient cycling research in Venezuela and assessed the role of cocoa and shade tree litter in the N cycle of a cocoa plantation. A series of experiments on nutrient cycling in cocoa ecosystems was conducted at the CATIE research station, Turrialba, Costa Rica (Alpizar et al., 1986; Beer et al., 1990; Fassbender et al., 1988, 1991; Heuveldop et al., 1988) and although the research was somewhat hampered by the size of the experimental plots (Somarriba et al., 2001), it yielded much insight in the nutrient cycling pattern of shaded cocoa. Overall, research on nutrient cycling in cocoa ecosystems was undertaken to increase understanding of the systems and served for a more accurate assessment of inorganic fertilizer requirements. This article reviews the results of research on nutrient cycling in cocoa ecosystems, including data on soil changes under permanent cocoa cultivation. The objectives are to calculate and compare nutrient stocks of cocoa ecosystems and to compose nutrient balances for some of the world’s cocoa growing areas. Hereto, the cocoa ecosystem is divided into two pools (soil and vegetation) and one flow (litter fall). This review is restricted to pools and flows of N, P, and K. Although Ca and Mg are quantitatively important as well, they are not included due to insuYcient data for comparison.

II. CLIMATIC AND SOIL CONDITIONS OF STUDY AREAS Nutrient stocks and balances could be calculated from experimental data from Malaysia, Venezuela, Costa Rica, Brazil, and Cameroon. A brief description of the environmental conditions of the areas where the studies were conducted is given. The experimental site in Malaysia was located in a flat to undulating area with deep red, highly weathered soils derived from granite. The soils were classified as Oxisols and Ultisols. Average annual rainfall is about 1850 mm with a dry spell of 6 to 8 weeks. The cocoa was of the upper Amazon hybrid type and was planted with a density of 1074 plants ha
1. The cocoa was 8 to 10 years when the nutrient studies were made. Yield levels were high at about 1400 kg ha
1 (dry beans), and shade trees are Gliricidia maculata. The soils of the study site in Venezuela were well drained and located in a flat area at sea level. They are of recent alluvial origin and are classified as Psammentic Entisol (Psamment). The soil reaction is slightly alkaline (pH 7.4), and organic C levels are below 1.5% in the topsoil. Mean annual rainfall is 740 mm, and average temperatures are around 25  C. Cocoa was planted at a density of 947 plants ha
1 and was about 30 years when the

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nutrient studies were conducted. The cocoa is of the Criollo type and yields are 640 kg ha
1 (dry beans). The soils under cocoa in Costa Rica are poorly drained and the soil reactions are extremely acid (pH-H2O 3.8). The soils are derived from fluvial-lacustrine deposits and are classified as Typic Dystropepts. Average annual rainfall is 2648 mm, and mean temperatures are 22  C. Cocoa was 10 years old and planted at a density of 1111 plants ha
1. Annual yield levels were around 650 kg ha
1. Shade trees planted at 278 ha
1 were Cordia alliodora and Erythrina poeppigiana. The soils of the study site in Brazil were classified Alfisols and have a high fertility. Total annual rainfall is 1862 mm, and the average temperature is about 23  C. There is no information available on the cocoa but shade trees were Erythrina fusca and Ficus spp. at a density of 278 ha
1. Not much data are available for the experimental site in Cameroon. The site was formerly a tropical rain forest and the soils were red and clay-like. Total annual rainfall is 1700 mm. The cocoa was planted under natural shade with a population of about 1000 plants ha
1. Table I summarizes the environmental growing conditions and information on the cocoa and shade trees of the study areas.

III. NUTRIENT STOCKS Nutrient stocks of cocoa ecosystems comprise above and belowground biomass and the nutrients in the soil. Stock size depends on the amount of biomass and fertility status of the soils. The aboveground biomass is subdivided into the biomass of the cocoa and the shade tree. The total biomass of cocoa ecosystems is variable, and in Malaysia, 7.5-year-old cocoa had a biomass of about 60 tons dry matter (DM) ha
1 (Thong and Ng, 1978), whereas a 10-year-old cocoa plantation in Costa Rica had 8.5 to 11 tons DM ha
1 (Alpizar et al., 1986). Shade trees in Costa Rica accumulated about 23 to 35 tons DM ha
1. Biomass includes roots, as they are an important component of primary production in perennial cropping systems and consist of about 25 to 43% of the aboveground biomass (Young, 1997). Research at CATIE (Costa Rica) showed that the fine root biomass of cocoa shaded with Erythrina poeppigiana or Cordia alliodora was around 1 ton ha
1, but higher values were found at the end of the rainy season (Munoz and Beer, 2001). In most papers on cocoa ecosystems, soil nutrient stocks were given in kg ha
1 and these stocks were calculated from soil chemical analysis: total N, available P, and exchangeable K. These nutrients were generally given as % (N), mg kg
1 (P), and mmolc kg
1 (K) and were multiplied with the soil bulk density values to obtain nutrient stocks in kg ha
1. Nutrient stocks

232

Table I Summary of Soil, Climate, Cocoa, and Shade Tree of Cocoa Ecosystems Soil

Typea

Malaysia Venezuela

Oxisol, Ultisol Entisol

Costa Rica

Inceptisol

Brazil

n.d.b

Cameroon

n.d.

a

Poor fertility Very sandy Poorly drained High fertility

1850

n.d.

USDA soil taxonomy classification. No data.

b

Annual rainfall (mm)

Dry periods

Cocoa Mean annual temperature ( C)

Shade

Age (years)

Trees (ha
1)

Yield (kg ha
1)

1074

1400 636

21

8–10

740

6–8 weeks 3 months

25

30

947

2648

1 month

22

10

1111

ca. 700

1862

n.d.

23

n.d.

n.d.

n.d.

1700

n.d.

n.d.

30

1000

700

Species Gliricidia maculata Mixture

Trees (ha
1)

Reference

268

Ling (1986)

566

Aranguren et al. (1982a) Alpizar et al. (1986) de Oliveira Leite and Valle (1990) Boyer (1973)

Cordia/ Erythrina Erythrina fusca

278

Natural

n.d.

278

A. E. HARTEMINK

Country

Diagnostic property

Climate

COCOA ECOSYSTEMS

233

have been restricted to the upper 30 cm, as most feeding roots of cocoa are concentrated to that depth. The root system of a cocoa tree consists of a thick tap root and a mat of lateral roots that lies in the top 20 cm of the soil; these lateral roots are the main channel for moisture and nutrients (Wood and Lass, 1985). De Oliveira Leite and Valle (1990) found that 85% of the roots are concentrated in the first 30 cm of the column, and Thong and Ng (1978) also found that cocoa is a surface-root feeder with most lateral roots found in the surface soil layer (0–30 cm). Also, de Geus (1973) mentioned that 80% of the roots are found within 15 cm of the soil surface. In most soils in the tropics the major part of the nutrients are also found in the top 25 cm. Nitrogen accumulation in the above- and belowground biomass of cocoa ranges from 100 to over 400 kg ha
1. This variation is explained by the age of planting, diVerence in cultivar, and environmental conditions. In Costa Rica and Brazil, more than twice the amount of N was present in the shade tree than in the cocoa, and it is not uncommon that shade trees contain more N than the cocoa (Stephenson and Raison, 1987). Total N contents in the shade tree does not vary much and is around 260 kg N ha
1. As total biomass of the shade trees diVers between the cocoa ecosystems, nutrient content per unit biomass largely varies. Most of the N is found in the topsoils and less than 10% in the cocoa and shade trees. The total N content in the upper 30 cm varies from about 4800 to 18,750 kg ha
1. The N content of the soils in Costa Rica with a leguminous shade tree (Erythrina poeppigiana) is about 1000 kg ha
1 higher compared to soils under a nonleguminous shade tree (Cordia alliodora). As the age of the plantation is 10 years, average yearly N fixation could be 100 kg ha
1, which is very high. It has been reported that Erythrina may fix about 60 kg ha
1 per year (Young, 1997). The extremely acid soil reactions (pH 3.8) with high Al concentrations favoring P fixation (Giller, 2001) seem to have little adverse eVects on nodulation (Alpizar et al., 1986). The accumulation of P is low in cocoa ecosystems. In most systems the total amount in the biomass is equivalent to the available P content of the soil. The content of phosphorus in the cocoa is about 55 kg ha
1 for Malaysia and around 12 kg ha
1 for Costa Rica and Brazil. The P stocks in the cocoa of Cameroon is extremely low but concerns the aboveground biomass only. The P content of the shade trees is typically around 25 kg ha
1. Cocoa and shade trees in Costa Rica contain more P under nonleguminous shade trees, possibly as Rhizobium sp. is high P demanding, which restricts uptake by the vegetation. The P content in the litter varies from 7 to 14 kg ha
1. In Brazil and Costa Rica, the same amount of P is found in the cocoa biomass as in the annual litter fall, but for Malaysia, about 8 times more P is found in the cocoa biomass than in the annual litter fall. Potassium is a major nutrient in mature cocoa. Stocks of exchangeable K in the topsoil vary from 100 to 550 kg ha
1. The K content of mature

234

A. E. HARTEMINK

cocoa in Malaysia is over 600 kg ha
1 whereas in other studies the K contents of soils under cocoa were found to be only 10 to 15% of these values. High K levels in the soil correspond to high K levels in the vegetation and annual litter fall (Table II).

IV. NUTRIENT CYCLING For nutrient cycling in cocoa ecosystems, a simple balance is used that was first presented by Boyer (1973) and later adjusted by Wessel (1985) and Ling (1986). The cocoa ecosystem is divided into a soil and vegetation pool (Fig. 2). Nutrients can be removed or added from the soil and vegetation pool or transferred between the soil and the vegetation pool. Pathways for nutrient losses include nutrient removal by the yield and leaching, and soil erosion. Denitrification under cocoa is small, as the crop is mostly grown on well-drained soils.

A.

NUTRIENT REMOVAL: YIELD

Removal of nutrients from cocoa ecosystems includes yield (beans and husks), immobilization in stem and branches, and leaching of nutrients below the rooting zone. Most nutrients in cocoa ecosystems are lost by the harvest of beans and husks. Table III shows the nutrients removed in a crop with a yield of 1000 kg dry beans per ha. If data of Venezuela are disregarded, about 20 kg N, 4 kg P, and 10 kg K are removed with 1000 kg dry beans. When the husks are also removed, the amount is increased to about 35 kg N, 6 kg P, and 60 kg per 1000 kg beans, which indicates that K removal by the husks is high. Nutrient removal in beans shows little variation, whereas large diVerences can be noticed for husks. According to Wessel (1985), this is caused by the fact that husks are aVected more strongly by the environment and the type of fruits than beans. Nutrients immobilized in the stem and branches of cocoa and shade trees are also considered lost for the system as they are excluded from nutrient cycling. Immobilization of nutrients is particularly important for young cocoa, but is unimportant for mature cocoa (Wessel, 1985).

B. NUTRIENT REMOVAL: LEACHING Leaching is an important pathway for nutrient losses in soils of the humid tropics (Buresh and Tian, 1997; Grimme and Juo, 1985; Sollins, 1989). Despite the diVerences in crop phenology and soil management, very few

Table II Nutrient Stocks of the Soil and Vegetation (kg ha
1) Pool and in the Litterfall (kg ha
1 year
1) of Cocoa Ecosystems Vegetation

Country Nitrogen

Potassium

Cocoa

Shade tree

Total

Litterfall cocoa

Shade tree

Total

Malaysia Malaysia Venezuela Costa Ricab

6699 n.d.a 18750 5327

423 438 302 110

245 n.d. n.d. 260

668 n.d. n.d. 370

84 n.d. 115 n.d.

48 n.d. 205 n.d.

132 n.d. 320 115

Costa Ricac

6370

109

249

388

n.d.

n.d.

175

Brazil Cameroon

4805 4782

103 39d

263 n.d.

366 n.d.

n.d. 52

n.d. n.d.

128 n.d.

Mean  1 SDe

7789  5429

248  161

254  9

448  147

84  32

127  111

174  85

Malaysia Malaysia Costa Ricab Costa Ricac Brazil Cameroon

59 n.d. n.d. n.d. 30 79

57 48 14 10 12 1d

20 n.d. 32 29 26 n.d.

77 n.d. 46 39 38 n.d.

5 n.d. n.d. n.d. n.d. 4

2 n.d. n.d. n.d. n.d. n.d.

7 n.d. 14 9 12 n.d.

Mean  1 SD

56  25

28  22

27  5

50  18

51

n.d.

11  3

Malaysia Malaysia Costa Ricab

557 n.d. 385

607 633 105

140 n.d. 258

747 n.d. 363

91 n.d. n.d.

33 n.d. n.d.

124 n.d. 66

Costa Ricac

475

52

252

304

n.d.

n.d.

54

Brazil Cameroon

113 103

67 51d

237 n.d.

304 n.d.

n.d. 38

n.d. n.d.

25 n.d.

Mean

327  209

253  285

222  55

430  213

65  37

n.d.

67  42

Calculated from Ling (1986) Thong and Ng (1978) Aranguren et al. (1986) Alpizar et al. (1986); Heuveldop et al. (1988) Alpizar et al. (1986); Heuveldop et al. (1988) De Oliveira Leite and Valle (1990) Boyer (1973)

Ling (1986) Thong and Ng (1978) Heuveldop et al. (1988) Heuveldop et al. (1988) De Oliveira Leite and Valle (1990) Boyer (1973)

COCOA ECOSYSTEMS

Phosphorus

Soil (0–30 cm)

Ling (1986) Thong and Ng (1978) Alpizar et al. (1986); Heuveldop et al. (1988) Alpizar et al. (1986); Heuveldop et al. (1988) De Oliveira Leite and Valle (1990) Boyer (1973)

a

235

No data. Cocoa with Cordia alliodora as shade tree. c Cocoa with Erythrina poeppigiana as shade tree. d Excluding roots; figure not included for the calculations of mean and CV%. e Standard deviation. b

236

A. E. HARTEMINK

Figure 2

Simplified nutrient cycling diagram for cocoa ecosystems.

studies have compared leaching losses under perennial and annual crops in the tropics (Seyfried and Rao, 1991). A leaching experiment was conducted at CATIE with two contrasting cropping systems: (i) a mixed perennial cropping system composed of Cordia alliodora (a timber species), cocoa, and plantain and (ii) an annual monocropping system with maize (Seyfried and Rao, 1991). Losses of Ca, Mg, and K were significantly greater by 2 to 15 times in the maize system, and NO3 losses from the maize plots were 56 kg ha
1 compared to 1 kg NO3 ha
1 in the mixed perennial plots. The diVerence was explained by the much larger nutrient retention and uptake capabilities of the perennial crops (Seyfried and Rao, 1991). Research conducted in West Africa also concluded that leaching losses under annual crops are likely higher than under oil palm (Omoti et al., 1983), whereas Imbach et al. (1989) concluded that leaching losses in cocoa ecosystems are much lower than under annual crops. These studies provide evidence for the “safety net” theory of tree crops whereby nutrients leached to a deeper soil horizon can be taken up by tree roots at great depths (Sanchez, 1995; van Noordwijk, 1989). In the cocoa-growing regions of south Bahia, Brazil, a lysimeter study was conducted on a 30- to 40-year-old cocoa plantation with Tropudalfs as the dominant soil orders (Santana and Cabala-Rosand, 1982). Leaching losses in unfertilized and fertilized plots (40 kg N, 40 kg P, and 50 kg K ha
1) were compared. The amount of NH4-N and NO3-N losses was proportional to the amount of rainfall. Less N was leached from the fertilized plots than from the unfertilized plots. This was possibly because the

Table III Nutrients (kg) Removed by 1000 kg Dry Cocoa Beans Beans

Total

N

P

K

N

P

K

N

P

K

Calculated from

20.4 39.3 19.3 21.3 22.0 19.2 22.8 22.9 22.1 n.d. n.d.

3.6 n.d.a 4.6 4.2 n.d. 4.4 4.0 3.9 3.0 n.d. n.d.

10.5 n.d. 10.9 10.5 n.d. 10.6 8.4 8.5 7.5 n.d. n.d.

10.6 31.4 11.5 14.8 12.0 15.0 17.0 15.4 13.2 n.d. n.d.

1.3 n.d. 1.8 1.8 n.d. 1.9 2.3 1.8 1.8 n.d. n.d.

43.3 n.d. 34.5 27.2 n.d. 62.0 77.2 68.4 43.0 n.d. n.d.

31.0 70.7 30.8 36.1 34.0 34.2 39.8 38.3 35.3 44.0 26.6

4.9 n.d. 6.4 6.0 n.d. 6.3 6.3 5.7 4.8 3.5 4.5

53.8 n.d. 45.4 37.7 n.d. 72.6 85.6 76.9 50.5 53.1 37.4

Thong and Ng (1978) Aranguren et al. (1982a) Heuveldop et al. (1988) Heuveldop et al. (1988) Santana et al. (1982) Boyer (1973) Wessel (1985) Wessel (1985) Snoeck and Jadin (1992) van Dierendonck (1959) van Dierendonck (1959)

COCOA ECOSYSTEMS

Malaysia Venezuela Costa Ricab Costa Ricac Brazil Cameroon Nigeria Nigeria Ivory Coast Trinidad Trinidad

Husks

a

No data. Cocoa with Cordia alliodora as shade tree. c Cocoa with Erythrina poeppigiana as shade tree. b

237

238

A. E. HARTEMINK Table IV Annual Leaching Losses (kg ha
1 ± 1 SD), Inorganic Fertilizer Inputs (kg ha
1), and Soil Nutrient Reserves (kg ha
1 for 0–45 cm) Under Cocoa with DiVerent Shade Trees at Turrialba, Costa Ricaa

N P K

Cocoa with Erythrina poeppigiana as shade tree

Cocoa with Cordia alliodora as shade tree

Inorganic fertilizer inputs

Soil nutrient reservesb

5.3  0.2 0.5  0.1 1.5  0.1

5.2  0.3 0.5  0.1 1.2  0.1

120 29 33

8800 3400 650

a

Modified from Imbach et al. (1989) and Alpizar et al. (1986). Averaged and rounded data from soils under cocoa with E. poeppigiana or C. alliodora as shade tree. b

application of P and K increased the development of cocoa roots, thus increasing nutrient-absorbing surfaces and decreasing the amounts of N available for leaching. No data were given in kg ha
1 or as a percentage of applied nutrients, but it was concluded that N leaching losses were small and do not seriously aVect N availability to the cocoa (Santana and CabalaRosand, 1982). Another study with cocoa on Alfisols in Bahia showed mean annual losses of 22 kg N, 0.9 kg P, and 17 kg K ha
1 (de Oliveira Leite, 1985). These are fairly high losses, particularly when it is considered that the cocoa was unfertilized. At the cocoa experiment at CATIE, inorganic fertilizer input was 120 kg N, 29 kg P, and 33 kg K ha
1 year
1. Leaching losses were calculated from nutrient concentrations in lysimeter capsules at 1 m depth and the volume of percolated water (Table IV). Losses of N, P, and K were very small and seem to have no management significance when compared to inorganic fertilizer inputs or to the total soil reserves on the experimental site. Reports from cocoa on Psamments in the lowlands of Venezuela showed that leaching losses under traditional shaded cocoa were low, although leaching may be large when inorganic fertilizers are applied in such light-textured soils (Aranguren et al., 1982b).

C. NUTRIENT REMOVAL: SOIL EROSION In perennial crop systems, soil erosion can be considerable with inappropriate land-clearing methods and with insuYcient soil cover immediately after forest clearance (Lal, 1979, 1986). Most annual crops provide adequate cover within 30 to 45 days after planting and pastures within 2 to 6 months, but tree crops may require 2 to 5 years to close their canopy (Sanchez et al.,

COCOA ECOSYSTEMS

239

1985). Erosion is greater during the initial stages of tree establishment than when the tree canopy is fully developed and a much-used solution to the problem of soil exposure during plantation establishment is to use a managed cover crop (Sanchez et al., 1985). Erosion losses are thought to be low except in cocoa grown on steep slopes without shade and when the cocoa is young (Roskoski et al., 1982). Under monocropping cocoa in Malaysia, soil erosion losses were 11 mg ha
1 year
1, but losses were very low when cover crops such as Indigofera spicata were planted (Hashim et al., 1995). When the cocoa was intercropped with banana and clean weeding with herbicide was practiced, soil losses up to 70 mg soil ha
1 year
1 were measured, which are high losses based on a general rating of tolerable soil erosion losses (Hudson, 1986). Overall, soil erosion is negligible in mature cocoa and losses of nutrients with soil erosion are insignificant.

D. ADDITION

OF

NUTRIENTS

Nutrients are added to cocoa ecosystems by inorganic fertilizers, atmospheric deposition, and symbiotic and asymbiotic N fixation. Weathering of parent material resulting in a release of P and K is not considered an input to the ecosystem. Inorganic fertilizers add directly to the soil pool, although a significant portion may be lost through volatilization or leaching directly after application. Nutrients supplied by rainfall (i.e., wet and dry deposition) vary from 5 to 12 kg N ha
1, 0.2 to 3.0 kg P ha
1, and 2.5 to 12 kg K ha
1 in the study areas (Table VII). Nitrogen in the rainfall in Venezuela (11 kg ha
1) and Cameroon (12 kg ha
1) is particularly high. Sanchez (1976) mentioned that about 4 to 8 kg N ha
1 must be considered as a low and high estimate of annual contribution by rain and dust in tropical areas. Fixation of N by leguminous shade trees may be a considerable source of N for the cocoa as was shown in the total N content of the soils under cocoa with and without a leguminous shade tree (Table II).

E. TRANSFER

OF

NUTRIENTS

In cocoa ecosystems, nutrients are transferred through litter, rainwash, and fine-root turnover. Litter fall is subdivided into the litter from the cocoa and shade tree and includes branches, twigs, leaves, fruits, and flowers. In many parts of the world, cocoa is produced under natural or planted shade trees. Shade trees compete for growth resources but may also ameliorate adverse climate conditions; reduce soil erosion, pests, and diseases; and increase nutrient use eYciency in cocoa (Beer et al., 1998; Johns, 1999).

240

A. E. HARTEMINK Table V Annual Litterfall of Cocoa Ecosystems in kg DM ha
1 Annual litter fall Age cocoa (years)

Cocoa

Shade tree

Total

Reference

Malaysia Venezuela

8–10 30

5460 7630

2660 13,571

8120 21,201

Costa Ricaa

10

n.d.b

n.d.

7071

Costa Ricac

10

n.d.

n.d.

8906

Brazil

n.d.

n.d.

n.d.

9000–14,000

Cameroon Ghana

30 n.d.

5092 n.d.

3408 n.d.

8500 5000

Ling (1986) Aranguren et al. (1982a) Heuveldop et al. (1988) Heuveldop et al. (1988) De Oliveira Leite and Valle (1990) Boyer (1973) Wessel (1985)

Country

a

Cocoa with Cordia alliodora as shade tree. No data. c Cocoa with Erythrina poeppigiana as shade tree. b

Generally, cocoa yield increases dramatically when high levels of inputs are made, but under low levels of inputs, cocoa yields are substantially higher with shade trees (Wood and Lass, 1985). Litter fall ranges from 5 to more than 21 tons DM ha
1 year
1 (Table V). The average annual litter fall of cocoa and the shade tree is 10 tons ha
1, which resembles the litter production of other plantation crops under shade trees, such as coVee with Inga spp. (Young, 1997). High litter fall in the cocoa of Venezuela may be due to the low rainfall of the experimental site (Table I). Maximum leaf fall coincides with low rainfall or drought (Ling, 1986), and leaf fall is further related to shade (cocoa under light-shaded conditions defoliates more rapidly than under light shade) and the age of planting (the older the plant, the more leaf fall), according to Wood and Lass (1985). Climate has more influence on the amount of litter fall than the age of the cocoa, and it seems that shade trees drop their leaves under dry conditions. Large amounts of nutrients are returned to the soil with the litter fall. Nutrient concentrations in the leaf fall are lower than in the fresh leaves as nutrients are resorbed before the leaves fall. The amount of nutrients annually transferred depends on the amount of litter fall and the nutrient concentration. The N concentration varies from 11 to 20 g kg
1 with a mean of all data of 15 g kg
1 (Table VI). Phosphorus is only present in very low concentration, typically around 0.1%, and the concentration of K shows large variation. The high values of K in the cocoa litter in Malaysia and

COCOA ECOSYSTEMS

241

Table VI Nutrient Concentration (g kg
1) in Cocoa and Shade Tree Litterfall Nutrient concentration (g kg
1) Country

N

P

K

Calculated from

Malaysia Venezuela Costa Ricaa

16.3 15.1 16.3

0.8 n.d. 2.0

15.3 n.d. 9.3

Costa Ricab

19.6

1.0

6.1

Brazil

11.2

1.0

2.1

11.1

1.2

11.7

Ling (1986) Aranguren et al. (1982a) Alpizar et al. (1986); Heuveldop et al. (1988) Alpizar et al. (1986); Heuveldop et al. (1988) De Oliveira Leite and Valle (1990) Boyer (1973)

14.9  3.3

1.2  0.5

Cameroon Mean  1 SD

c

8.9  5.1

a

Cocoa with Cordia alliodora as shade tree. Cocoa with Erythrina poeppigiana as shade tree. c Standard deviation. b

Cameroon may be due to a high K content in the soil and the luxury consumption of K by the cocoa and shade tree. Apparently less K is resorbed before the leaves fall. The NP ratio varies from 21 for Malaysia to 9 for Cameroon. Decomposition is most rapid if the ratio is around 10, which is the case for the litter in Cameroon, Brazil, and in Costa Rica under leguminous shade. With decomposition, N and P concentrations tend to increase, but K concentrations decline rapidly, as K is mobile and leached rapidly from the litter (Giller, 2001). Nitrogen in the annual litter fall is about 20 to 45% of the total N in the vegetation and 2 to 3% of the total N in the soil. Phosphorus in the annual litter fall is about 10 to 30% of the total P in the vegetation and 10 to 40% of the available P in the soil. About 10 to 20% of the exchangeable K in the soil is yearly transferred by the litter fall, and K in the litter is about 15% of the total K in the biomass. Large amounts of nutrients are transferred by rainwash (through fall) in cocoa ecosystems. Rainwash is a transfer of nutrients but can also become an addition if the leaves were covered with dust that has been transported from elsewhere (Asner et al., 2001; Parker, 1983). The major part of the nutrients supplied with the rainwash had been taken up from that same soil. The amount of nutrients transferred by rainwash is less than 8 kg ha
1 for N and P. For K this varies from 38 to more than 100 kg ha
1 per year, which demonstrates the importance of rainwash for the K nutrition of the cocoa. Few data were available for the nutrient cycling of roots and although an appreciable store of nutrients and roots constitutes a substantial element in

242

A. E. HARTEMINK

nutrient cycling, they are almost invariably turned to the soil (Young, 1997). Munoz and Beer (2001) showed that fine root turnover was close to 1.0 in cocoa shaded with Erythrina poeppigiana or Cordia alliodora in Costa Rica. Nutrient inputs from fine root turnover were estimated as 23–24 kg N, 2 kg P, and 14–16 kg K per ha year
1. Such amounts equaled about 6–13% of the total nutrient input in the cocoa shaded with C. alliodora and 3–6% in the cocoa shaded with E. poeppigiana (Munoz and Beer, 2001).

V.

NUTRIENT BALANCES

Partial balances were calculated in which losses, additions, and transfer of nutrients were calculated for the cocoa ecosystems in Malaysia, Venezuela, Costa Rica, and Cameroon. In all cocoa ecosystems, it was found that N removed by cocoa beans (yield) is lower than in the litter fall (Table VII). For Cameroon, N in the litter is about twice the amount removed by the yield, whereas for Malaysia, this ratio is nearly 5. If about 6000 kg N ha
1 is present in the topsoil, N removed by the yield is, on average, less than 0.5%. Addition of N by wet and dry deposition is fairly high and ranges from onesixth to almost half of the yearly N removal. The turnover of N is large compared to the additions and losses, particularly when the cocoa is not fertilized. In Costa Rica where fertilizer N is applied at a rate of 120 kg N ha
1, the total transfer is lower than the yearly addition. The beans remove only 16 to 21% of the applied N. Data of Malaysia and Costa Rica suggest that inorganic fertilizer has no eVect on the transfer of N with the litter. A major part of the N requirement is supplied with litter decomposition, which may explain the absence of a significant yield response after inorganic fertilizer applications. It is well known that inorganic fertilizers have little or no eVect under shaded cocoa (de Geus, 1973; Wessel, 1985). A large part of the P in a cocoa ecosystem is found in the vegetation and in the litter, whereas the amount of P in the soil is low. Both the quantity and the distribution within the ecosystem diVer from those of N and K, which aVect the nutrient balance. Phosphorus losses are equal to half of the transfer of P by rainwash and litter. Addition of P in dry and wet deposition, although variable, may contribute substantially to the P requirements, and in Malaysia, more than half of the removal by the yield is supplied by atmospheric deposition. A relatively large amount (6 to 8%) of the available P in the soil is removed by the cocoa beans. The ratio among losses, additions, and transfer is similar under fertilized conditions as under unfertilized conditions. Inorganic P fertilizers at rates of less than 30 kg ha
1 change the balance, but P fertilizers seem to have little influence on the P transfer with litter.

COCOA ECOSYSTEMS

243

Table VII Partial Nutrient Balance and Transfer (kg ha
1 year
1) of Cocoa Ecosystems

Nitrogen

Phosphorus

Potassium

Process

Malaysia

Venezuela

Costa Ricaa

Costa Ricab

Cameroon

Losses

Yield Immobilization Leaching Total

29.0 4.0 n.d. 33.0

25.0 n.d.c n.d. 25.0

19.3 n.d. 5.5 24.8

25.7 n.d. 5.5 31.2

24.0 3.5 n.d. 27.5

Additions

Deposition N2 fixation N fertilizers Total

8.0 n.d. 0 8.0

11.0 n.d. n.d. 11.0

5.0 n.d. 120.0 125.0

5.0 n.d. 120.0 125.0

12.0 n.d. n.d. 12.0

Transfer

Rainwash Litter fall Total

8.0 132.0 140.0

n.d. n.d. 329.0

n.d. 115.0 115.0

n.d. 175.0 175.0

6.3 52.5 58.8

Losses

Yield Immobilization Leaching Total

5.0 2.0 n.d. 7.0

4.0 n.d. 0.5 4.5

4.3 n.d. 0.5 4.8

n.d. n.d. n.d. n.d.

4.4 0.1 n.d. 4.5

Additions

Deposition P fertilizers Total

3.0 n.d. 3.0

0.2 29.0 29.2

0.2 29.0 29.2

1.0 n.d. 1.0

1.7 n.d. 1.7

Transfer

Rainwash Litter fall Total

<1.0 8.0 <8.0

n.d. 14.0 14.0

n.d. 9.0 9.0

8.0 12.0 20.0

1.3 1.8 5.1

Losses

Yield Immobilization Leaching Total

15.0 8.0 n.d. 23.0

28.4 n.d. 1.5 29.9

26.9 n.d. 1.5 28.4

n.d. n.d. n.d. n.d.

51.0 5.0

Additions

Deposition K fertilizers Total

8.0 n.d. 8.0

2.5 33.0 35.5

2.5 33.0 35.5

8.0 n.d. 8.0

12.0 n.d. 12.0

Transfer

Rainwash Litter fall Total

38.0 133.0 171.0

n.d. 66.0 66.0

n.d. 54.0 54.0

47.0 25.0 72.0

101.0 38.0 139.0

56.0

a

Cocoa with Cordia alliodora as shade tree. Cocoa with Erythrina poeppigiana as shade tree. c No data. b

Potassium is quantitatively the second nutrient in cocoa ecosystems. The K removed by the yield is about 5 to 10% of the total exchangeable K in the soils of Malaysia and Costa Rica, whereas in Cameroon, half of the exchangeable soil K reserve is removed in the cocoa beans. In Costa Rica, about two times more K is present in the litter than removed by the yield; in the other cocoa ecosystems, K in the litter is three to five times larger than

244

A. E. HARTEMINK

the amount removed by the beans. Rainwash and litter fall are the most important K recycling process in a cocoa ecosystems.

VI. SOIL CHANGES UNDER COCOA Tree crops such as cocoa remain in the same field for many years and require an initial high investment. Long-term returns of such investments can only be expected if production is sustained, which requires, among others, that the soil remains in good condition. However, permanent cropping will aVect the soil conditions and in order to sustain productivity, it is needed to investigate the long-term changes brought about by the crop and management practices (Hartemink, 2003). The previous section reviewed nutrient stocks and nutrient balances. Although there was a considerable diVerence between systems and between the three major nutrients, it was shown that the total amount of nutrients in cocoa ecosystems is large and that a considerable part is removed and transferred each year. The eVects of cocoa growing on the soils are reviewed here, and several studies have focused on the eVects of cocoa on soil organic C, as in many soils of the tropics, maintenance of soil organic C is the key to sustainable crop production (Greenland, 1994; Woomer et al., 1994). Beer et al. (1990) measured soil organic C in cocoa ecosystems on a Typic Humitropept at CATIE, Turrialba (Costa Rica). When the cocoa was shaded with Erythrina poeppigiana topsoil (0–15 cm), organic C levels increased from 28 to 32 g kg
1 in 9 years. Levels in the 15- to 30-cm soil horizon changed from 23 to 25 g C kg
1 over the same period. Similar changes were noted in the top- and subsoil when the cocoa was shaded with Cordia alliodora (Beer et al., 1990). None of the changes were statistically significant, which indicates that cocoa ecosystems were able to maintain soil organic C contents. Several studies have been conducted in Nigeria, which is the fourth largest cocoa producer in the world. Near Ibadan, Ekanade et al. (1991) found soil organic C contents under forest of 29 g kg
1, whereas this was 19 g C kg
1 under cocoa. Available P was much higher under cocoa than under forest, but exchangeable K was lower. In Oyo State (Nigeria), Adejuwon and Ekanade (1987) found topsoil organic C levels of 26 g kg
1 under forest and 19 g C kg
1 in the topsoils under cocoa (Table VIII). All major nutrients and the pH were lower under cocoa compared to soils under forest. In another study in the Oyo state of Nigeria, Adejuwon and Ekanade (1988) sampled a large number of soils under forest, and soils that had been under cocoa for 10 to 15 years. Soils were classified as Alfisols, and mean annual rainfall at the sites was about 1300 mm. The soil pH under forest was 6.8,

COCOA ECOSYSTEMS

245

whereas the pH under cocoa had decreased to 5.5. Soil organic C levels were 27 g kg
1 under forest but only 13 g C kg
1 under cocoa. Also, total N and levels of exchangeable cations were much reduced when the soils under forest were compared to those under cocoa (Adejuwon and Ekanade, 1988). In southern Nigeria it was found that soil organic C under a secondary forest was about 35 g kg
1; under 10-year-old cocoa, levels were 25 g C kg
1 (Ogunkunle and Eghaghara, 1992). Total N and most other soil properties were about the same under cocoa and secondary forest. Ekanade (1988) sampled 60 cocoa plots of ages from 1 to 55 years and collected 30 soil samples under forest on Alfisols in southwestern Nigeria (Table IX). Soil organic C was, on average, 26 g kg
1 under forest and 19 g kg
1 under cocoa, and the soil reaction was 6.8 under forest and 5.9 under cocoa. All soil chemical properties were significantly lower under cocoa.

Table VIII Mean Values (Range in Parentheses) of Soil Chemical Properties Under Forest and Cocoa on Alfisols in Nigeriaa Sampling depth: Land use: pH Organic C (g kg
1) Available P (mg kg
1) CEC (mmolc kg
1) Exchangeable Ca (mmolc kg
1) Exchangeable Mg (mmolc kg
1) Exchangeable K (mmolc kg
1) a

0–15 cm

15–45 cm

Forest

Cocoa

Forest

Cocoa

6.8 (5.4–7.6) 26 (13–37) 14 (8–23) 144 (90–191) 90 (54–112) 38 (21–53) 7 (4–15)

5.9 (4.6–7.4) 19 (12–30) 12 (6–20) 95 (52–174) 53 (20–118) 20 (14–38) 4 (2–14)

4.7 (3.1–6.0) 13 (6–23) 13 (4–28) 78 (31–200) 47 (14–113) 29 (9–63) 5 (2–8)

5.0 (4.0–6.0) 12 (6–20) 9 (5–16) 62 (27–129) 41 (15–73) 20 (6–47) 3 (2–5)

Modified from Adejuwon and Ekanade (1987).

Table IX Mean Values of Soil Chemical Properties Under Forest and Cocoa on Alfisols in Nigeriaa

pH (CaCl2) Organic C (g kg
1) Available P (mg kg
1) CEC (mmolc kg
1) Exchangeable Ca (mmolc kg
1) Exchangeable Mg (mmolc kg
1) Exchangeable K (mmolc kg
1) a

Modified from Ekanade (1988).

Forest (n ¼ 30)

Cocoa (n ¼ 60)

6.8 25.2 16 196 122 57 9

5.9 18.5 12 125 83 28 4

Difference P P P P P P P

< 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.05

246

A. E. HARTEMINK

These studies from West Africa provide insight into the diVerences and changes that may be expected when the natural forest is converted to perennial cropping. The studies consistently show that soil organic C equilibrium data under cocoa settle below those of the soils under natural forest. Carbon storage under cocoa is, however, often higher than in comparable soils under annual cropping (Duguma et al., 2001; Kotto-Same et al., 1997). Studies have shown that nutrient and metal pollution levels on cocoa farms are generally very low (Okuneye et al., 2003) due to the relatively low use of agrochemicals such as inorganic fertilizers. The soil chemical fertility was significantly lower under cocoa compared to soils under forest, and this is often found under perennial crops (Hartemink, 2003). However, in Cameroon, soil pH, organic C, and exchangeable actions were generally higher in home gardens dominated by cocoa than in secondary forest (Table X). The secondary forest was developed after fields that were used for food crop production were left fallow.

VII. DISCUSSION Several sources of variation were identified when comparing nutrient stocks and balances in cocoa ecosystems: climatic and soil conditions, cocoa and shade tree (age, cultivar, or species, plant density), and research approach and methods (sampling techniques, analytical methods). DiVerences in the research approach and methods also resulted in some variations in the studies reviewed here, and despite the temporal and spatial variation, several trends emerged. They are discussed here. Nitrogen is the main nutrient in cocoa ecosystems and about 90% of the total N is found in the topsoil. More P and K are found in the cocoa and shade tree than in the soil. High K levels in the soil result in high concentrations in the vegetation and litter fall, which is likely aVected by the luxury consumption of K by the cocoa. No clear relation was found between N and P concentrations in the soil, vegetation, and annual litter fall. The calculations on the nutrient stocks have some limitations. Total N is determined by total analysis, whereas P is available (bicarbonate extraction) and K is exchangeable (NH4-acetate); P and K are therefore a fraction of the total content in the soil. As much of the P and K are locked up in insoluble compounds or in minerals that weather very slowly, data give a fair estimate of the amounts of P and K that are potentially available for crop production. Nitrogen is based on total analysis and thus equals the total amount present in the topsoil. As most cocoa roots are found in the top 30 cm, deep capture of nutrients, which is important in many perennial cropping systems, is not

Exchangeable cations (mmolc kg
1) Organic C (g kg
1)

pH (H2O)

Ca

Mg

K

Study site

Cocoa

Forest

Cocoa

Forest

Cocoa

Forest

Cocoa

Forest

Cocoa

Forest

Yaounde Mbalmayo Ebolowa

6.9 6.8 6.5

5.2 6.5 4.8

26.4 24.6 28.2

15.0 28.8 19.2

108 114 118

26 52 30

21 20 25

10 18 9

4 6 14

1 2 2

a

COCOA ECOSYSTEMS

Table X Soil Chemical Properties (0–20 cm) in Cocoa-Dominated Home Gardens and Secondary Forest in Southern Cameroona

Modified after Duguma et al. (2001).

247

248

A. E. HARTEMINK

so relevant. The nutrient stocks reported for the topsoil are more or less equal to the amount of nutrients available. Transfer of nutrients takes place with the litter fall and rainwash, and the rate of litter fall and nutrient concentration determines the amount of nutrients transferred. Rate of litter fall depends on climate (dry spells), age and type of the plantings, and shading density. The nutrient concentration of litter depends on the availability in the soil and/or the uptake capacity of the plants. This review has shown that K is transferred via rainwash in large amounts (up to 100 kg ha
1 year
1) as K is mobile in the plant, whereas N and P are more fixed in organic compounds. Total transfer via litter fall and rainwash covers the removal with the beans in all nutrient balances. For N the ratio transfer to losses is 2 to 13, whereas for P this ratio is 1 to 3. Although more nutrients are transferred than lost annually, this does not necessarily imply that cocoa ecosystems are self-suYcient in terms of N, P, and K nutrition, as the transfer does not compensate for losses. The size of the total nutrient transfer is, however, important in relation to the sustainability of a cocoa ecosystem, and a large annual transfer of nutrients may indicate that the system is more self-suYcient. Under unfertilized conditions (Malaysia, Cameroon), yearly losses of N are about two to four times higher than the nutrient addition. For P, losses are about two to three times higher, and about three to five times more K is lost annually when no inorganic fertilizer is applied. Under fertilized conditions (Costa Rica), the balance changes and even at moderate fertilizer applications, annual losses are lower than additions. However, as part of the nutrients applied in inorganic fertilizers are lost after application, the nutrient balance is less positive. Because fertilizer use eYciency diVers among nutrients, fertilizer types, time and method of application, soil types, and cropping systems, no standard fraction can be deducted from the application rate. Most cropping systems in the tropical regions have negative nutrient balances (Henao and Baanante, 1999; Pieri, 1989; Smaling, 1993). This is caused by the low use of inorganic fertilizers, which has severe environmental implications, as it results in soil mining and soil fertility depletion (Dudal and Byrnes, 1993). The low use of inorganic fertilizers in the cocoa ecosystems results in a negative nutrient balance, but leaching and erosion losses are much lower than in systems with annual crops. Moreover, cocoa ecosystems have relatively large nutrient stocks of which only a fraction is removed with the bean yield. As such it can be argued that cocoa ecosystems have a much higher degree of resilience than annual cropping systems. Changes in soil chemical properties were found to be different as soils, climates, and cropping systems differed. Nevertheless, a decline was found in most soil chemical properties and in most soils. Various studies indicated that the original C and N levels under natural forest are not attained again in perennial cropping systems, although levels of P and exchangeable cations,

COCOA ECOSYSTEMS

249

particularly K, may be higher in soils under perennial crops due to the use of inorganic fertilizers. Changes in soil chemical properties reflect the decrease in nutrient stocks of the soil, but it also reflects immobilization of nutrients in the biomass. Therefore, it is more diYcult to assess soil fertility decline and its causes in cocoa ecosystems than, for example, in annual cropping systems. The studies discussed here have shown that leaching losses under cocoa can be considerable, although the losses are consistently smaller than under annual crops (Hartemink, 2003; Seyfried and Rao, 1991). This is related to the fact that tree crops grow the whole year through in the humid tropics, whereas in annual cropping there may be periods when there is no crop or the crop is either too young or old to take up nutrients from the soil solution. The absence of a crop in combination with the onset of the seasonal rainfall inducing the N priming eVect (Birch, 1958) may result in leaching losses: no crop, no uptake. Tree crops generally provide a “safety net,” but an adequate supply of all nutrients for a dense root mat is essential to reduce nutrient leaching and to enable a deep uptake of leached nutrients (van Noordwijk and Cadisch, 2002).

VIII.

CONCLUDING REMARKS

It is generally assumed that perennial crops are a more sustainable form of land use than systems with annual crops. A perennial plant cover protects the soil better against erosion than an annual crop (Jacks and Whyte, 1939; Lal, 1990; Ruthenberg, 1972), although much depends on the soil, site factors (slope, rainfall, etc.), and management practices. Perennials can also provide a “safety net” whereby nutrients leached to a deeper soil horizon are taken up by tree roots at great depths (Sanchez, 1995; van Noordwijk, 1989), and as perennial crops are often cash crops that receive inorganic fertilizers, nutrient depletion is often lower than under annual crops (Hartemink, 2003). Although the data set was limited, this review showed that large amounts of nutrients in cocoa ecosystems are transferred each year. Such nutrient cycling is important for maintaining cocoa production. Although no attempts were made to compare the cocoa ecosystem with annual cropping systems, this review provided evidence that that cocoa ecosystems are more environmentally sound. Nonetheless, little specific research has been carried out on the macroenvironmental service impact, such as biodiversity conservation, C sequestration, and water quality (Somarriba et al., 2001), which are research priority areas in cocoa ecosystems.

250

A. E. HARTEMINK

ACKNOWLEDGMENTS I am grateful to Professor Dr. Marius Wessel and Wouter Gerritsma of Wageningen University for their comments on an earlier draft of this paper. Wouter Bomer of ISRIC–World Soil Information is thanked for the drawing of Fig. 1.

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RICE–WHEAT CROPPING SYSTEMS Rajendra Prasad Division of Agronomy, Indian Agricultural Research Institute, New Delhi, India

I. Introduction A. Global Population and Food Demand B . Rice–Wheat Cropping Systems C . Contribution to Food Security II. Climate and Soils III. Agronomic Management A. Tillage and Transplanting/Seeding B . Crop Residue Management C . Nutrient Management D. Irrigation and Water Management E . Weed Management IV. Genetic Manipulation A. High Yielding Ability B . Early Duration C . Multiple Resistance to Diseases and Pests D. Grain Quality E . Breeding for Special Soil Problems V. Sustainability of Rice–Wheat Cropping Systems A. Declining Yields B . Factor Productivity C . Soil Health D. Pest Problems VI. Socioeconomic and Policy Factors VII. Future Research Needs Acknowledgments References

I. INTRODUCTION A. GLOBAL POPULATION

AND

FOOD DEMAND

Global population was 1 billion in 1800 A.D. and it took a whole century and 30 years to double itself by 1930 A.D. However, it took only 30 years to add another billion to reach 3 billion in 1960 A.D. and again in the next 255 Advances in Agronomy, Volume 86 Copyright 2005, Elsevier Inc. All rights reserved. 0065-2113/05 $35.00

256

R. PRASAD Table I Demand for Meat and Eggs, Milk, Fish, and Feed in India at 5% GDPa

Item

1995

2000

2010

2020

Meat and eggs Milk Fish Feed

3.1 64.0 4.7 14.2

Million tonsb 3.7 75.3 5.7 16.8

5.4 103.7 8.2 23.7

7.8 142.7 11.8 38.1

a

From Kumar (1998). All data in this paper are in metric ton, which is 1000 kg.

b

39 years it doubled itself to 6 billion in 1999. It is predicted that it will continue to increase and will double itself by 2100 A.D. to reach 12 billion (TOI, 2001). Most of this increase in population has been and will be in lesser developed countries in Asia, Africa, and South America, with Asia contributing the most. Some short-term projections are available from the World Bank and, according to their 1994–1995 population projections, the world population will increase from 5.7 billion in 1995 to 7 billion in 2020; the increase in China is likely to be from 1.2 to 1.5 billion, in south Asia from 1.3 to 1.9 billion, and in Africa from 0.7 to 1.3 billion (IFA, 1978). Obviously, this large increase in the world population will result in increased demand for food. According to the International Food Policy Research Institute (Pinstrup-Anderson et al., 1997), between 1993 and 2020 A.D. the global demand for cereals is expected to increase by 41%. It has been projected (IRRI, 1998) that annual rice production must increase from 556 million tons in 2000 A.D. to 758 million tons by 2020 A.D., a 36% increase (1.8% year
1). Major rice-growing and rice-eating nations in south and southeast Asia must achieve a higher production growth rate. In addition to direct human consumption, the developing countries’ demand for cereals for feeding livestock is expected to double during 1993–2000 A.D. due to increased demand for meat and other animal products, such as milk, butter, and cheese. Some of the factors contributing to the increased demand for animal products are economic growth, rising income, and urbanization. For example, China’s per capita annual consumption of grains, meat, and edible vegetable oil was only 97.4, 4, and 1.7 kg, respectively, in 1949 and increased to 377, 42.8, and 21.2 kg, respectively, in 1998 (Jiaguo, 2000). Table I shows that the demand for meat, eggs, milk. and fish in India will almost double by 2020 A.D. from the present (2000). The situation is further complicated by the fact that the increase in the production of cereals and other foods has to be made from the same or even lesser land due to an increased demand for land for housing, industry,

RICE–WHEAT CROPPING SYSTEMS

257

Table II Available Arable Land (ha capita
1) in RWCSa Countries Country

1961

1990

2000

2020

Bangladesh China India Nepal Pakistan

0.168 0.159 0.456 0.191 0.330

0.079 0.087 0.199 0.121 0.169

0.059 0.077 0.161 0.095 0.126

0.035 0.060 0.105 0.059 0.069

a

From Gill (1994).

railways, roadways, and so on; the pressure of this will be more in populous and predominantly rice–wheat cropping system (RCWS) countries such as China, India, Pakistan, and Bangladesh. Trends in per capita available arable land are shown in Table II. During the period 1961–2000 the per capita arable land in China declined from 0.159 to 0.077 ha and is predicted to decline further to 0.060 ha by 2020; thus it will be only 37.7% of that in 1961. Similarly, in India and Pakistan available arable land per capita by 2020 will be 23 and 21% of that in 1961, respectively. Other RWCS countries are not better off.

B.

RICE–WHEAT CROPPING SYSTEMS

RWCS is a long-established grain production system in China; it was reported during the Tang dynasty (617–907 A.D.) and was widely adopted during the Song dynasty (960–1279 A.D.) and spread throughout the Yangtze River Valley in the Ming and Quig dynasties (1368–1911 A.D.) (Lianzheng and Yixian, 1994). However, the wheat yield following rice was only 0.7 to 1.0 tons ha
1 until the 1940s and it increased progressively after the 1950s as a result of improved varieties, better agronomic management, and pest control. Thus, in the Jiangou province, the average yield of wheat after rice was 1.6 tons ha
1 in 1970, 3.3 tons ha
1,in 1980, and 4.0 tons ha
1 in 1988 (Lianzheng and Yixian, 1994). The average wheat yield after rice in the Sichuan province in 1997 was 3.76 tons ha
1, with the highest recorded as 6 tons ha
1 (Jiaguo, 2000). RWCS in the Indian subcontinent is quite new and started only in the late 1960s with the introduction of dwarf wheat from CIMMYT, Mexico, which required a lower temperature (mean below 23  C) for good germination than that required for traditional tall Indian wheat. Thus, wheat sowings were shifted from mid-October to mid-November, providing a full extra month

258

R. PRASAD

for the preceding rainy season crop. This provided enough time for rice to mature; high-yielding varieties (HYV) of which such as IR-8 were already available. This set in the RWCS in the Indo-Gangetic plains (IGP) of the Indian subcontinent and the northwestern states of India [Punjab, Haryana, western Uttar Pradesh (UP)] and the Punjab and Sind province of Pakistan, which were traditionally wheat regions, were transformed into rice–wheat regions. The reverse of this happened in Bihar and West Bengal states of India and parts of Bangladesh, which changed from traditional rice regions to rice–wheat regions. In RWCS two to three crops are grown during a span of 12 months or a crop year (July–June), as it is termed in India. In RWCS belt Indian subcontinent rice is grown during rainy season (July to November) when 700–1000 mm rainfall is received, while wheat is grown during the winter season (November to May) on stored soil moisture with supportive irrigation. In China, almost the same months are occupied by rice and wheat, although the rainfall pattern differs and, in some parts, quite a bit of rain is received during the wheat-growing season. Many farmers in India take a third crop of potato or toria in between rice and wheat or rice/mungbean/ cowpea/green manure (GM)/sunflower in between wheat and rice. Some of the rice–wheat cropping systems are listed. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

Rice (Oryza sativa L.)–wheat (Triticum aestivum) Rice–potato (Solanum tuberosum)–wheat Rice–toria (Brassica campestris)–wheat Rice–wheat–mungbean (Vigna radiata) Rice–wheat–cowpea (Vigna unguiculata) Rice–wheat–green manure (Sesbania spp., Crotolaria spp.) Rice–potato–wheat–green manure Rice–wheat–sunflower (Helianthus annuus) Rice–wheat–rice Rice–vegetable peas (Pisum sativum)–wheat Rice–vegetable peas–wheat–green manure Rice–wheat–maize (Zea mays)

There could be many more variants involving vegetables and other shortduration crops. Most rice in RWCS is transplanted and rice varieties grown are of 90–140 days duration (seed to seed) of which 25–45 days may be spent in nursery; more aged seedlings (50 to 60 days old) are transplanted in some parts of China (Gupta et al., 2000). Wheat in the cropping system takes 120 to 160 days; its maturity is determined by temperatures above 35  C, bright sunshine, and high wind velocity. Thus sown in mid-November (optimum for India), wheat matures by the end of March in eastern India, by the end of April in western Uttar Pradesh and Haryana, and by the first fortnight of May in Punjab and Himachal Pradesh. In China, wheat matures in June/July

RICE–WHEAT CROPPING SYSTEMS

Figure 1

259

Crop calendar for RWCS in China. From Jiaguo (2000).

and thus receives quite a bit of rainfall asking for adequate drainage. It also delays rice transplanting, which is why the tradition of using older rice seedlings is used in some parts of China. A calender of RWCS in China for different regions is given in Fig. 1. The estimates of area under RWCS in the world vary considerably. Paroda et al. (1994) reported 22.4 million ha (m.ha), whereas Ladha et al. (2000) reported 24 m.ha under RWCS. However, adding up the estimates available for different countries, it totals 28.8 m.ha: 13 m.ha in China (Jiaguo, 2000), 12.3 m.ha in India (Kumar et al., 1998), 2.2 m.ha in Pakistan, 0.5 m.ha in Nepal (Paroda et al. 1994), and 0.8 m.ha in Bangladesh (Ladha et al., 2000). These 5 RWCS countries are not just any 5 of the more than 200 countries of the world, they represent 43% of the world’s population on 20% of the world’s arable land (Singh and Paroda, 1994). Also, more than half of the world’s malnourished people are in these countries. In the Indian subcontinent, RWCS is predominant in the Indo-Gangetic Plains (Fig. 2) (Woodhead et al., 1994), although there are pockets of this cropping system in several other states of India. The IGP are spread from 67 to 96 E longitude and from 20 to 33 E latitude (Schwartzberg, 1978). It extends from Assam and the Bay of Bengal on the east to the Afghan border and Arabian sea in the west and covers India, Bangladesh, and Pakistan. It has Himalayas in the north and minor hills or plateau in the south and covers about 2400 km from east to west and about 160 km wide in the east and 500 km in the west. In China, RWCS is predominantly in the Yangtze River Valley (Fig. 3). In India, as well as in China, areas under RWCS have spread over time. Data on the spread of the area under RWCS in India in 1983 and a decade later in 1993 under RWCS are given in Table III. In the states of

260

R. PRASAD

Figure 2 RWCS belt of the Indo-Gangetic Plains of the Indian subcontinent. From RWCS Int. Workshop, New Delhi, India, September 25–27, 2000. Ministry of Agriculture, Gurtiy India, Indian Council of Agricultural Research, and the World Bank.

Punjab, Haryana, and UP, which are predominantly wheat-growing states, almost all rice is under RWCS. However, in West Bengal, which is a predominantly rice-growing state, only 4% of the area under rice is under RWCS. The reverse is true when the area under RWCS is expressed as the percentage of total wheat area in these states. In Bihar and West Bengal, the wheat area under RWCS is 96–98% of the total wheat area; in Punjab and UP, the values are 63 and 61%, respectively, whereas in Haryana it is only 36%. This is because wheat also follows rainy season fallows, sorghum (Sorghum bicolor), maize (Zea mays), pearl millet (Pennisetum typhoides), cowpea, mungbean, pigeonpea (Cajanus cajan), and so on, in UP, Punjab,

RICE–WHEAT CROPPING SYSTEMS

261

Figure 3 RWCS belt (filled area) of China (mainly in the Yangtze river valley). From Jiaguo (2000).

Table III Estimated Area under Rice–Wheat Cropping System in the Indo-Gangetic Plains in Indiaa,b

Area (m ha) of rice–wheat system

Rice–wheat rotations area as percentage of total rice area

Rice–wheat rotations area as percentage of total rice area

States

1983

1993

1983

1993

1983

Punjab Haryana Uttar Pradesh Bihar West Bengal Indo-Gangetic plain India

1.35 0.51 5.14 1.70 0.11 8.82 11.46

2.02 0.67 5.25 1.90 0.26 9.96 12.33

100 100 94 37 2 72 29

100 100 96 40 4 75 30

44 30 61 96 41 58 49

1993 63 36 61 96 98 63 52

a

Average of triennium ending 1983 and 1993. From Kumar et al. (1998).

b

and Haryana. Yadav et al. (1998a) showed that RWCS in India is prevalent in about 120 out of a total of 502 districts, whereas rice–rice is practiced in only about 50 districts. Other cropping systems, such as maize–wheat, sorghum–wheat, rice–rape (Brassica spp.), and sugarcane–wheat, are practiced in still fewer districts.

262

R. PRASAD

In China, RWCS accounts for 41.5% of the total area of 31.3 m.ha under rice (Jiaguo, 2000). Taking all the five countries (China, India, Pakistan, Bangladesh, and Nepal) together, RWCS covers 28% of the total rice area and 35% of the total wheat area in these countries.

C. CONTRIBUTION

TO

FOOD SECURITY

RWCS covers about 32% of the total rice area and 42% of the total wheat area in four countries of south Asia (India, Pakistan, Bangladesh, and Nepal) and accounts for one-quarter to one-third of the total rice and wheat production (Ladha et al., 2000). More detailed information on this is available from India where it is the backbone of the country’s food security. In 1983, the total production from RWCS was 35.6 million metric tons, which was 28.3% of the total cereal production in India (Table IV); the production increased to 50.4 million metric tons in 1993, accounting for 31.4% of the total cereal production in that year. In India, rice and wheat are procured by the government for distribution through the public distribution system (PDS). In 1994–1995, RWCS in the IGP of India contributed 94.9% of the total wheat procurement and 59.6% of the total rice procurement by the government of India for distribution through the PDS (Kumar et al., 1998). This share of RWCS to PDS in India is continuing even today. Thus, RWCS is the key for India’s food self-sufficiency.

Table IV Contribution of Rice–Wheat-Based Cropping System (RWCS) in Total Cereal Production in Indo-Gangetic Plains of Indiaa Production from RWCS (mt)b

Total cereal production (mt)

Contribution of RWCS in total production (%)

States

1983

1993

1983

1993

1983

1993

Punjab Haryana Uttar Pradesh Bihar West Bengal Indo-Gangetic plain India

8.2 2.6 14.8 3.9 0.9 29.9 35.6

14.1 4.3 20.5 5.5 1.1 44.7 50.4

13.9 6.2 24.0 7.7 6.9 58.7 125.6

19.7 9.4 33.2 8.9 12.4 83.6 160.7

59.0 41.9 61.7 58.6 13.0 50.9 28.3

74.6 45.7 61.7 61.8 8.9 53.5 31.4

a

From Kumar et al. (1998). Million metric tons.

b

RICE–WHEAT CROPPING SYSTEMS

263

In China, the contribution of RWCS toward total cereal production from rice-based cropping systems was about 50%, which was roughly about one-fourth of the total cereal production in the country (Lianzheng and Yixian, 1994).

II. CLIMATE AND SOILS RWCS is generally practiced in subtropical to subtemperate regions with warm humid summers and dry cold winters. There is a west-to-east zoning in the IGP of the Indian subcontinent. Rainfall ranging from 700 to 1000 mm year
1 is mostly received during June to September, with rainfall increasing eastward. Some rains (5–10% of the annual total) are received during winters (November–March) in some areas. As already mentioned, rice in the Indian subcontinent is grown during the rainy season (June–September) and fall (September–October), whereas wheat is grown during the winter (November to February) and spring (March–May). Growing seasons of wheat are longer in the west (195 days, mid-November to the end of May) and shorter in the east (135 days, mid-November to the end of March). Wheat in the RWCS belt in the Indian subcontinent is grown under irrigation. In China there is a north-to-south zoning in RWCS regions. The growing season of wheat is longer in the north (220 days, early October to mid-June) and shorter in the south (160 days, early November to mid-May). In northern China, as in Beijing, wheat season rainfall may be only 150 mm (35 mm month
1 during February–April), which is not sufficient for wheat, and irrigation is a must. However, in the middle and lower reaches of the Yangtze River, wheat season rainfall is 500–700 mm, which, in the absence of adequate drainage, results in fatal water logging of wheat. A good drainage system is a prerequisite for wheat in this zone (Lianzheng and Yixian, 1994). Both in the IGP and in the Yangtze river valley in China, the soils are formed from the river alluvium. In the IGP, soils could be Alfisols (Haplustalfs, Ochroqualfs), Inceptisols (Ustochrepts), Entisols (Aquents, Fluvents, Psamments), and Mollisols (Hapludoll) with soil textures ranging from loamy sands to clay loams. In India, RCWS is also practiced in pockets outside IGP in the states of Madhya Pradesh (Chromosterts), Rajasthan, Maharashtra, and Gujarat (Torrifluvents, Haplargid, Ustochrepts, Dustochrepts, Chromostarts). Large areas under RWCS in IGP and elsewhere are saline-sodic, which is one reason why rice is quite popular as a rainy season crop. In China, soils of RWCS regions are more weathered and are referred to as red soils, yellow earths, purple soil, and limestone soil (Zitong, 1986).

264

R. PRASAD

Red and yellow soils could be Alfisols or Entisols, whereas dark/purple colored soils are vertisols such as Shajiang black soils in Jingsu and other provinces. The clay content in black soils could vary from 40 to 70%, making soil management very difficult, particularly for wheat after rice.

III. AGRONOMIC MANAGEMENT A. TILLAGE

AND

TRANSPLANTING/SEEDING

1.

Rice

In the RWCS belt of the Indian subcontinent, most rice is transplanted. Unless a third crop is taken between wheat and rice, there is plenty of time (about 2 months) for preparing fields for rice, which is generally done 1 to 2 weeks before transplanting (first week of July). Where mechanization is practiced, the dry field is disked twice with an offside disk and is then harvested or cultivated twice and leveled. Where animal power is used, the land is prepared after giving one light irrigation. Generally two to three harrowings are done with a country plough and the land is leveled. The field is then ponded with water and is puddled with a puddler and leveled again. Two to three 21- to 25-day-old rice seedlings per hill are then transplanted at a spacing of 20  10 cm or 15  15 cm. Rice seedlings are raised separately on a site near the tube well so that the nursery can be irrigated frequently. For each hectare of land, a nursery area of 1000 m2 and 25–30 kg seed is required. Nurseries are well manured with farmyard manure and chemical fertilizers. Also, one or two hand weedings are given. There have been some studies in India on direct seeding on a dry seed bed (Chatterjee and Mukherjee, 1970; Sudhakara and Prasad, 1986) or sowing sprouted seeds on a puddle seedbed (Narhari and Pawar, 1961; Nayak and Garnayak, 1999). These techniques, although time and energy saving, have not yet found favor in the RWCS belt due to serious weed problems. Farmers, particularly those in a less favorable environment (LFB), who are not economically well off do not have enough funds to spend on herbicides. The land preparation is similar in China but many farmers broadcast rather than transplant rice. For this purpose, seedlings are raised in special 60  30-cm PVC trays that contain shallow depression or cones with a 2-cm-diameter top and a 1-cm-diameter bottom. These cones are 1–1.5 cm deep with a hole at the bottom for drainage. Two to three seeds are placed and grown in each cone. The 20- to 25-day-old seedlings are broadcast manually or with the help of a blower in a puddled rice field. Some gap filling is done manually (Gupta et al., 2000). This technique reduces the labor

RICE–WHEAT CROPPING SYSTEMS

265

requirement for transplanting considerably. In regions when rice transplanting is delayed due to delayed wheat harvest, about 60-day-old seedlings are used for transplanting (Jiaguo, 2000). Some farmers practice twice culture for raising a rice nursery. First, young seedlings are raised for 7–10 days in a greenhouse using 500 seeds m
2. These young seedlings are then transferred to a nursery at a spacing of 5  5 cm and are raised there for 40–45 days before transplanting in the rice field. In this case, because rice grows in the field for fewer days (60–70 days), the irrigation requirement is reduced considerably.

2.

Wheat

In RWCS there is very little turn-around time between rice harvest and wheat sowing. Depending on the variety and date of transplanting, rice is harvested between the end of October and the end of November, whereas the optimum time of sowing wheat in India is mid-November and in China it is the last week of October to the first week of November. Depending on the time of harvest of the rice crop, conventional tillage requires presowing irrigation on well-drained soils or draining or drying of soil in lowlands followed by one or two diskings, two harrowings, and leveling. All these operations require time and delay sowing of wheat, which results in a reduced yield (Figs. 4 and 5). Zero-till techniques are therefore being tested and adopted where suitable and advantageous. In the Sichuan province of China, surface seeding of wheat and rice straw mulching is practiced (Yonglu et al., 2000). This practice saves 22% in costs and 23% in labor and increases rice yield by 10% and farmers income by 35%. Some farmers in India also do surface broadcasting of wheat immediately after rice harvest and without preparatory tillage, but most wheat in the Indian subcontinent is sown after conventional tillage. Available data from Pantnagar (Rath et al., 2000), New Delhi (Singh et al., 2001), Ludhiana (Samra and Dhillon, 2000), and Modipuram (Prasad and Yadav, 2000) also show its advantage (Table V). Kumar (2000) from Pantnagar recommended a minimum of two passes of a harrow followed by two passes of a cultivator and one leveling for seed bed preparation for wheat after rice. In a study at Pantnagar (Singh and Gangwar, 2000), although the grain yield and benefit cost ratio was higher under conventional tillage, zero tillage was recommended due to savings in cost, time, labor, fuel, and energy consumption (Table VI). However, in 132 trials conducted on the farmers’ fields in Haryana, Mehla et al. (2000) found a 7.1% increase in the grain yield of wheat with zero tillage (ZT) over conventional tillage (CT) sowings on the same date (Table VII) and 16.7% when conventional tillage was done and sowings were delayed by about 2 weeks (CTD), as is the traditional farming practice,

266

R. PRASAD

Figure 4 EVect of planting dates and tillage options on the productivity of wheat Cultivar PBW 343, From Mehla et al. (2000).

Figure 5 EVect of sowing date on the yield of wheat in China in 1997 (left) and 1998 (right). From Yonglu et al. (2000).

RICE–WHEAT CROPPING SYSTEMS

267

Table V Grain Yield (t ha
1) of Wheat as AVected by Tillage New Delhia

Pantnagarb

Modipuramc

Ludhianad

Tillage

1994

1995

1996

1998

1999

1997

1998

1996 and 1997 mean

Zero tillage Conventional tillage LSD (0.05)

4.2 4.6 0.17

3.6 4.1 0.09

3.2 3.3 NS

3.6 4.6 0.07

3.8 5.2 0.10

3.4 4.4 NA

1.6 2.3 NA

4.8 5.0 NS

a

From Singh and Prasad (2000). From Rath et al. (2000). c From Prasad and Yadav (2000). d From Samra and Dhillon (2000). b

Table VI Comparative Performance of Conventional and Zero Tillage in Wheat After Ricea

Factors

Conventional

Time (h/ha) Labour (h/ha) Diesel (l/ha) Energy (K cal/ha) Cost of sowing (Rs/ha) Grain yield (t/ha) Benefit:cost ratio a

5 12 30.2 480,567 895 4.2 2.5

Zero till 2 6 10 146,042 400 3.0 2.3

Savings over conventional (%) 60.0 55.3 50.0 66.9 69.6

From Singh and Gangwar (2000).

where sowings are delayed because a presowing irrigation is given and it takes time for the soil to come to condition for preparatory tillage. Similarly, in 338 frontline demonstrations on the farmers fields during 1998–2001 carried out throughout India under the All India Coordinated Wheat Improvement Project (AICWIP), zero tillage gave 8.1 to 35.5% higher yields (Table VIII). The increase in returns over variable cost was 1882 Indian Rupees ha
1 (Table IX). Similarly, in a village adopted by the Banaras Hindu University in eastern UP (Village Karhat, District Mirzapur), the farmers harvested an average of 4.8 tons ha
1 of wheat using zero-till technology; it was claimed to be the best crop in the entire district (Joshi et al., 2001). In the Haryana state of India, zero-till technology spread from a few hectares in 1997–1998 to more than 8000 ha in 1999–2000 (Mehla et al.,

268

R. PRASAD Table VII Relative Performance of Zero Tillage (ZT) and Conventional Tillage (CT) on the Grain Yield of Wheat on Farmers’ Field in this Haryana State of Indiaa Grain (t ha
1)

District

Year

Trials (number)

ZT

CT

CTD

Kaithal

1997–1998 1998–1999 1997–1998 1998–1999 1998–1999 1998–1999 1998–1999 1998–1999

04 32 17 32 07 06 02 32

4.4 4.9 4.4 4.6 3.5 3.8 3.8 4.6 4.2

3.8 4.6 3.8 4.5 3.3 4.0 3.6 4.4 3.9

3.6 4.3 3.5 4.3 2.0 3.6 3.0 4.0 3.5

Karnal Sonepat Panipat Ambala Kurukshetra Mean a

Phalaris minor plant m
2 ZT

CT/CTD

129 114 103 110 75 89 73 97

560 550 438 473 333 440 379 442

From Mehla et al. (2000).

Table VIII Performance of Zero Tillage over Conventional Tillage in Seeding Wheat in 338 Frontline Demonstrations on Fields in India (Average over 3 Years of Data from 1998–1999 to 2000–2001)a Wheat grain (t ha
1) Zone Northwest plains (states of Punjab, Haryana, western UP, Delhi, and Rajasthan) Northeast plains zone (states of Bihar, West Bengal, Orissa, Assam, and eastern UP) Central zone (states of MP, Gujarat, and parts of Rajasthan) a

Zero tillage

Conventional tillage

Yield gain (%)

4.95

4.58

8.1

3.69

2.72

35.5

5.05

4.52

11.8

From Singh and Kharub (2000).

2000). Similarly, in the Sichuan province of China, the area under zero till increased by about 146,000 ha annually during the 1990s (Yonglu et al., 2000). This has been possible due to the development of zero-till machines in both China and India. Thus, over time, zero-tillage is likely to spread in the RWCS belt in most countries. Another new wheat-seeding technology in RWCS in India is the furrow irrigated raised bed (FIRB). This was introduced from Sonora, Mexico,

RICE–WHEAT CROPPING SYSTEMS

269

Table IX Comparative Economics (Indian Rupees (Rs) ha
1) of Zero Tillage (ZT) and Conventional Tillage (CT) in Frontline Demonstrations on the Farmers’ Fields in Northwest Plains Zonea

Working cost ZT 9338 (485.3)b

Returns over variable cost

Gross output

CT

ZT

CT

ZT

CT

DiVerence

9612 (392.6)

36550 (592.9)

34958 (671.4)

26652 (524.5)

24770 (529.4)

1882c

a

From Singh and Kharub (2001). Standard error. c Significant at 1%. b

Table X EVect of Tillage Practices on Soil Physical Properties, Soil Moisture Conservation, and Soil Fertility at Changdu (China)a Porosity at tillering

Tillage Zero till Conventional a

Soil moisture (%)

Soil fertility

Soil layer depth (cm)

Total (%)

Capillary (%)

Tillering

Jointing

Organic matter (%)

Total N (%)

0–7 7–15 0–7 7–15

49.4 50.1 54.7 54.3

46.7 44.4 41.2 41.6

20.1 19.5 19.9 20.5

24.3 24.4 20.8 24.7

1.62 1.68 1.67 1.55

0.154 0.131 0.108 0.105

From Yonglu (2000).

where about 1 million acres of wheat are grown under FIRB. A specially designed raised bed planter is required for this purpose and is now locally made in India. The planter makes 70-cm-wide beds (for two to three rows of wheat) with an irrigation furrow in between. The FIRB system gives a 5–10% higher yield over conventional sowing and brings considerable savings in irrigation water and also facilitates manual weeding (Kumar et al., 2001). The advantages of zero-till technology are many. Some of these are as follows. 1. 2. 3. 4. 5. 6. 7.

Less time required for sowing Less labor requirement Lower costs Less diesel requirement Less energy requirement Avoidance of delay in wheat sowing Improved soil physical and chemical properties (Table X)

270

R. PRASAD

8. Soil moisture conservation 9. Reduction in the population of Phalaris minor (Table VII) 10. Higher yield and income. However, adequate weed control measures with the help of herbicides and fertilizer nitrogen are required for a successful wheat crop with zero-till after rice.

B.

CROP RESIDUE MANAGEMENT

Due to a short turn-around period between two crops in RWCS, crop residue management is a serious problem. In the Indian subcontinent the major problem is the management of rice residue, as rice is harvested during the end of October to the end of November, whereas the optimum sowing period of wheat is mid-November. As a contrast, there is a gap of 2 months between wheat harvest and rice planting and the wheat residue can be removed easily, However, wheat residue management becomes a problem if a third crop (rice/mungbean/cowpea/greengram) is taken during summer. The problem of crop residue management has become more serious due to combine harvesting of the crops, which leaves 15- to 25-cm-tall stubbles and spreads the rest of the straw on the field. Most farmers therefore burn the rice/wheat residue in the field. In China, crop residue management is a problem for both rice and wheat. Rice is harvested in October/November and wheat is sown in November/ December, leaving a small turn-around period as in the Indian subcontinent. Again, wheat is harvested in June/July, while rice is transplanted in July, which leaves very little time for land preparation. Burning of crop residue is therefore the most common practice. Due to increasing concerns about depleting soil fertility in RWCS, which is being held responsible for a declining rice/wheat yield (Duxbury et al., 2000; Nambiar, 1995; Yadav, 1998), and with the availability of zero-till seed drill for seeding wheat after rice, a number of studies have been made in India in the 1990s on the effect of residue incorporation vis-a`-vis its burning or removal on rice/wheat yields and on soil fertility. At New Delhi (Prasad et al., 1999a), Karnal (DWR, 2000–2001), and Kaul (Dhiman et al., 2000), incorporation of rice and/or wheat residues showed beneficial effects on the yield of rice. Data from Kaul are given in Table XI. In the case of wheat in the initial year there was poor growth in residue incorporated plots, but no such effects were seen in later years. There was an increase in grain yield of 0.6 tons ha
1 in the rice–wheat cropping system. These results show that crop residues can be incorporated without any detrimental effects on crops in RWCS. The little disadvantage seen in wheat due to cool winter temperatures, slowing decomposition of rice

RICE–WHEAT CROPPING SYSTEMS

271

Table XI EVect of Rice (R) and Wheat (W) Residue Management on Grain Yield (t ha
1) of Rice and Wheat in RWCS at Kaula 1994–1995 Treatment b

Residue removed Residue burnt Residue incorporated LSD (P¼0.05) a b

1995–1996

1996–1997

Mean

R

W

R

W

R

W

R

W

Total

7.0 7.0 7.7 0.30

3.8 4.3 3.6 NS

6.2 6.1 6.7 0.26

3.9 3.4 3.7 0.29

7.3 7.2 7.7 0.31

4.3 4.5 4.9 0.28

6.8 6.8 7.4

4.0 4.1 4.1

10.8 10.9 11.5

From Dhiman et al. (2000). Both rice and Wheat Residues in Respective Years.

Table XII EVect of Crop Residue Management on Soil Fertility after Five Cycles of RWCS at Pantnagara Total nutrients (g kg
1) Treatment

Organic C (g kg
1)

N

P

K

N

P

K

7.8 5.4 5.3 0.2

0.73 0.68 0.65 0.03

0.59 0.58 0.51 0.05

16.0 15.3 14.5 0.2

118 119 110 3.6

11.4 11.1 9.3 1.1

85.4 81.8 72.3 2.7

Residue incorporation Residue burning Residue removal LSD (P¼0.05) a

Available nutrients (mg kg
1)

From Sharma et al. (2000).

residue and immobilization of soil and fertilizer nitrogen, can be overcome by applying some additional fertilizer N by 40 kg ha
1 (Brar et al., 2000) or by intercropping legume-enriched cereal residues (Sharma and Prasad, 2001). Chauhan et al. (2001) also recommended 25% higher nitrogen for zero-till seeding of wheat. The major advantage of incorporation of rice/wheat residue is the increase in soil organic C (Dhiman et al., 2000; Prasad et al., 1999). In a study at Pantnagar (Sharma et al., 2000) after five cycles of RWCS, organic C, total N, total K, and available K were significantly higher in plots receiving crop residues as compared to plots where residue was burned or removed (Table XII). Sharma et al. (2000) from Delhi reported that an incorporation of crop residue also reduced the bulk density of soil. These results are similar to those reported from the United States, European countries, and Australia on residue incorporation in other cropping systems (Prasad and Power, 1991).

272

R. PRASAD

C. NUTRIENT MANAGEMENT Nutrient management is crucial for high yields in RWCS. Work at New Delhi showed that for each metric ton of grain produced in RWCS, 20–22 kg N, 2–3 kg P, and 25–29 kg K are removed from the soil (Aipe and Prasad, 2001; Gangiah and Prasad, 1999); the total grain production (rice þ wheat) in these studies varied from 5 to 8 tons ha
1 and total NPK removal from 257 to 406 kg ha
1. At Pantnagar where a grain yield of 9.8 tons ha
1 (rice þ wheat) was recorded, NPK removal was 522 kg ha
1 (Nambiar, 1994). In addition to NPK, large amounts of micronutrients are also removed, although the information available on this is limited. At Pantnagar, RWCS removed 7162 g Fe, 1325 g Mn, 1145 g Zn, and 636 g Cu ha
1 (Nambiar, 1994). Many farmers in the RWCS belt in the Indian subcontinent harvest 7–8 tons ha
1 of rice and 5.6 tons ha
1 of wheat, leading to a heavy removal of plant nutrients. The general recommendation in the RWCS belt in the Indian subcontinent is 120 kg N and 13 kg P ha
1 for rice and 120 kg N and 26 kg P ha
1 for wheat. Potassium is generally not included in the recommendation and when it is the rates are only 25–50 kg K ha
1. Thus total NPK addition to RWCS adds to only 279 to 329 kg ha
1, which is far less than removal. At Pantnagar, an annual negative balance of 22 kg N, 10 kg P, and 242 kg K ha
1 was recorded (Nambiar, 1994). Thus, over years, nutrient depletion of RWCS soils can be a serious problem and can affect crop productivity. This would also explain why Zn and Mn deficiencies were first reported from the RWCS belt in India. In the Sichuan province of China, where mostly hybrid rice is grown, the average yield was 7.85 tons ha
1, with the highest recorded being 10 tons ha
1. The average yield of wheat was 3.76 tons ha
1, whereas the highest recorded was 6 tons ha
1. Thus the highest grain production in RWCS was 16 tons ha
1year
1 (Jiaguo, 2000). Nutrient removal per ton of grain produced was 21 kg N, 10 kg P, and 19 kg K (Shihua and Wenquiang, 2000). In China, there is considerable emphasis on organic manures. Recommendations in RWCS in the Sichuan Province are 22.5 tons of fine liquid dung, 30 tons of synthetic manure (bean meal, seed cake, etc.), 180 kg N, 20–33 kg P, and 150–187 kg K per hectare for a grain yield of 6 tons ha
1 (Yonglu et al., 2000). Farmers desiring higher yields must increase manure and fertilizer proportionately. The recommended ratio of organic manure to chemical fertilizer is 4:6 (on nutrient basis). These higher recommendations of fertilizer and the inclusion of organic manures could be the secret of sustainability of RWCS in China. A large number of experiments have been conducted in India on the nutrient management in rice and wheat crops individually and to review them entirely is beyond the scope of this chapter. A few references are cited here to bring out the main points with reference to RWCS.

RICE–WHEAT CROPPING SYSTEMS

1.

273

Nitrogen

Nitrogen is the key plant nutrient and good responses are obtained in both rice and wheat. The general recommendations are 100–120 kg N ha
1 for each crop in the RWCS. Many farmers in the RWCS belt apply 150 kg N ha
1 or even more to rice. One of the main factors responsible for this is the low recovery of N applied to rice (Cassman et al., 1998; Prasad, 1999). Using 15 N, George and Prasad (1989) showed that the recovery of N applied to rice was 31.0, 26.7, and 25.9% at 50, 100, and 150 kg N ha
1. Goswami et al. (1988), also using 15N, showed that the recovery of 60 kg N ha
1 applied to rice was 35.4% by rice and 4.1% by the succeeding wheat crop (residual N); the corresponding value at 120 kg N ha
1 was 31.2% by rice and 4.6% by the succeeding wheat crop (residual N). The recovery of N applied to wheat is higher and varies from 40 to 91% (Prasad et al., 1998). a. Causes for Low N Recovery. The main causes for low recovery of N in RWCS are (1) ammonia volatilization, (2) denitrification, (3) leaching, and (4) runoff and erosion (Prasad and Power, 1995, 1997). Because processes other than ammonia volatilization are more operative in the ricegrowing season, when monsoon rains are received or heavy and frequent irrigations are applied, losses of N are more in rice, leading to a lower recovery of N applied to rice than to wheat. Once urea is applied to a moist soil it hydrolyzes rapidly under subtropical conditions where rice and wheat are grown; most hydrolysis is over by 2 to 4 days (Fillery et al., 1986; Reddy and Prasad, 1975). At New Delhi, 8.5% of the applied urea-N was lost as ammonia during the first week after fertilizer application in the initial stages of rice growth (Sudhakara and Prasad, 1986a). Similarly, Sarkar et al. (1991) reported a loss of 15–20% of applied N when urea was broadcast in a wheat field. Simulating wheat- and rice-growing conditions in the laboratory, Prasad et al. (1999) reported a loss of 4.4% of applied N after 1 week of incubation when urea was broadcast, whereas it was 0.05% when urea was deep placed under well-drained conditions as obtained in wheat. Under submerged rice conditions, the loss of N due to ammonia volatilization after 1 week of incubation was 13.5% of applied N when it was broadcast on the surface. These losses can be reduced when urea is coated with neem or blended with a nitrification inhibitor (Prasad and Power, 1995; Sudhakara and Prasad, 1986b). The addition of pyrite, which is reported to have some nitrification-inhibiting properties (Blaise and Prasad, 1993), can also reduce ammonia volatilization. Neem (Azadirachta indica Juss) cake or oil coating of urea and use of pyrites are simple indigenous technologies for the Indian subcontinent and can be adopted easily in RWCS.

274

R. PRASAD

In China, ammonium bicarbonate is an important source of N, and ammonia volatilization losses from this fertilizer are likely to be high (Shihua and Wanquiang, 2000). Once urea is hydrolyzed and the resultant ammonia-N is nitrified, denitrification follows under submerged anaerobic rice-growing conditions. Denitrification is one of the major mechanisms of N loss from the soil and these losses can range from negligible to as high as 100 kg N ha
1 (Aulakh et al., 1992). Denitrification losses are the most under lowland rice conditions and range from little to as high as 64% of available N (Buresh and De Datta, 1990; De Datta and Buresh, 1989; Mohanty and Mosier, 1990). Losses from wheat fields in Canada and Europe varied from 1 to 33 kg N ha
1 (Aulakh et al., 1992). The best way to reduce denitrification losses is to use synthetic or natural nitrification inhibitors such as Nitrapyrin, DCD, neem cake or oil, and pyrites (Prasad and Power, 1995). There is not much information available on leaching losses of N. In a potculture study, the leaching loss was 11.5% of applied urea N and was reduced to 8.7% when urea was coated with neem cake (Prakasa Rao and Prasad, 1980). In a field study at Pantnagar on a silty clay loam soil, 12% of applied N was lost by leaching and these losses were reduced to 8% when urea was blended with neem cake (Singh and Singh, 1986). Leaching losses of N can be reduced by using slow-release fertilizers such as sulfur-coated urea, ureaform, isobutylidene diurea (Prasad et al., 1971), or neem cake or oil-coated urea (Prasad et al., 1993, 1999). Data on losses of N due to runoff and erosion in RWCS are not available, but the occurrence of such losses is well known to the farmers, which is the reason why farmers in the upper regions of a landscape do not apply heavy doses of fertilizer N. Slow-release N fertilizers would be ideal for such situations, but unfortunately these are not yet available to rice farmers at an appropriate price. b. Ways to Increase N Use Efficiency. Because N (or any other plant nutrient) use efficiency depends on the crop yield obtained, all agronomic management practices, such as date of sowing, plant population, water management, and weed management, need to be optimized and adequate plant protection needs to be provided to rice as well as to wheat in RWCS (Prasad, 1990). Application of N in small amounts is a proven tool to increase N use efficiency. Most N to rice or wheat is applied in two or three split doses. In rice, where N losses are more, the number of splits can be increased. The general recommendation for rice in the RWCS belt is half dose at transplanting or a week after transplanting and the rest half dose at panicle initiation (Prasad et al., 1970; Thakur and Kushwaha, 1970; ten Have, 1971). In the case of very long duration rice varieties, there could be three split

RICE–WHEAT CROPPING SYSTEMS

275

doses: half at transplanting, one-fourth at active tillering, and the rest at panicle emergence/flowering. However, in China the recommendation is to apply 70% at transplanting and the rest 30% one week after transplanting (Shihua and Wenqiang, 2000). The general recommendation for N application in wheat in India is in two split doses: half at sowing and half at first irrigation (21–25 days after sowing) (Bhardwaj, 1978). On very sandy soils, three split doses may be used. In China, 70% of the N dose is applied at sowing, 15% at the two-leaf stage, and the final 15% at jointing (Shihua and Wenqiang, 2000). Deep placement of N (5–8 cm below the surface) or application as pellets has been found to be significantly superior to broadcasting of urea at the surface (Prasad et al., 1970). Incorporation in soil is another method used to reduce the loss of applied N (Schnier et al., 1988, 1990). The bulk of fertilizer N in rice is still broadcast in most rice-growing countries. As regarding wheat, most farmers in the RWCS belt in the Indian subcontinent use a fertilizer-cum-seed drill and place the basal dose 4–5 cm below and to the side of the seed. This reduces ammonia volatilization losses associated with the broadcast application of N. As regarding sources of N, fertilizers containing nitrate-N are inferior to ammoniacal and amide-N-containing fertilizers for rice (Prasad et al., 1998). Sarkar et al. (1978) and Prakasa Rao and Prasad (1982) reported that ammonium sulfate was superior to urea. However, urea is the dominant source for nitrogen for rice in Asia due to a higher N content, less production and transportation costs, no need for other raw materials, such as sulfur, in the manufacture of ammonium sulfate, and compatibility with herbicides and pesticides for foliar application. For wheat, most N carriers are equally effective (Singh and Prasad, 1985). The role of slow-release fertilizers and urea supergranules in increasing N use efficiency has already been discussed and there are many reports for rice (Buresh, 1987; Prasad et al., 1971b; Shoji and Kanno, 1994; Stutterheim et al., 1994; Wada et al., 1991). Considering their importance and the role that these materials can play globally in increasing fertilizer N use efficiency and in reducing associated environmental hazards, the International Fertilizer Association in Paris has published information on controlled release and stabilized fertilizers in agriculture (Trenkel, 1997). As regarding indigenous materials, there has been considerable research in India on neem cake-coated urea (NCU) and the matter has been reviewed (Prasad et al., 1993). In rice at 100 kg N ha
1 the increase in yield due to NCU over uncoated urea was 11.1% (Reddy and Prasad, 1977) to 54.2% (Surve and Daftardar, 1985). Similarly, in wheat at 80 kg N ha
1 NCU produced 5.4% more grain than uncoated urea (Agarwal et al., 1990). Furthermore, application of NCU to rice results in residual effects in wheat (Prasad et al., 1981; Reddy and Prasad, 1977), and Sharma and Prasad (1978) reported that the optimum

276

R. PRASAD

dose of N for wheat could be reduced by 50 kg N ha
1 if slow-release fertilizer or nitrification inhibitors were used in the preceding rice crop. Higher economic returns due to neem cake coating of urea were reported by Prasad and Prasad (1980). Of late, a technique of coating urea with neem oil emulsion has been developed (Prasad et al., 1999b), which is being used in some urea factories in India. Thus slow-release fertilizers and nitrification inhibitors have a role in RWCS.

2.

Phosphorus

In RWCS, the response to P is less marked as compared to wheat (Bhardwaj, 1978; Prasad et al., 1980) in the Indian subcontinent because most soils are of recent origin and their fertility buildup still continues due to fresh deposits of sediments brought by river floods. In China, however, there are large areas under red and yellow earths, which are more weathered, and on such soils rice responds well to phosphorus (Yonglu et al., 2000). William and Walker (1969) reported that as the soil-weathering proceeds, the amount of occluded P (Fe- and Al-phosphates) having a coating of Fe- and Alhydroxides (oxides) increases. The increased availability of active soil P under flooded paddy conditions (De Datta, 1981) is due to the dissolution of occluded P (Patrick and Mahapatra, 1968). The increase in the availability of soil P on water logging is, however, not uniform in all soils (Mandal, 1979). It is for this reason that the same soil response to P is higher in wheat than in rice and has led to the recommendations in both India and China that if wheat is fertilized adequately, then rice can be grown on residual P (Gill and Meelu, 1983; Meelu and Rekhi, 1981 and Shihua and Wenqiang, 2000). However, Goswami and Singh (1976) analyzed data from a number of centers under the All India Coordinated Agronomic Research Project (AICARP) (Table XIII) and showed that it was not true, and the total response to P application in RWCS was the most at several centers when P was applied to both rice and wheat. Similar results were reported by Formoli et al. (1977) and Kolar and Grewal (1989). A national workshop on phosphorus in India also recommended an application of phosphorus to both rice and wheat in RWCS (Tiwari et al., 2001). From a 19-year study at Faizabad (India), Yadav et al. (1998) showed that in RWCS there was no response to rice or wheat in the first 5–7 years, but as the native soil P declined, the response to P increased and after 19 years it was 40 kg grain kg
1 P in rice and 74 kg grain kg
1 P in wheat. Low temperatures during wheat-growing seasons reduce the decomposition of soil organic matter and thus reduce the availability of organic P, which could be one factor responsible for the higher response of wheat to P.

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277

Table XIII Total Response (tons ha
1) of Rice + Wheat to Application of 26 kg P ha
1 at Several Research Centers of AICARP in India (Data Pooled over 3 Years)a P applied to Experimental center Raipur Jabalpur Kathulia farm Bichpuri Varanasi Masodha Kharagpur a

Soil

Both crops

Rice only

Wheat only

Red and yellow Black Red and black Alluvial Alluvial Alluvial Laterite

2.25 2.34 2.44 1.12 0.79 1.89 1.81

1.34 1.99 2.47 1.30 0.67 1.19 1.51

1.40 1.88 1.82 1.05 0.63 1.73 0.71

From Gowami and Singh (1976).

Table XIV Relationship between Soil Test Value for P and Agronomic EYciency of P in Rice and Wheat in India Agronomic eYciency of P (kg grain kg
1 P2O5) Crop Rice Rice Wheat Wheat

Low P

Medium P

High P

Reference

7 27 13 24

4 21 10 18

— — 2 11

Goswami (1975) Goswami (1975) Kapur et al. (1979) Tiwari et al. (1974)

Most recommendations for P application are made on the basis of Olsen’s 0.5 M NaHCO3 extractable P (available P) for neutral and alkaline soils obtained in the IGP of the Indian subcontinent. Data in Table XIV show that the response of rice to P was obtained on soils having low to medium Olsen’s P, whereas the response of wheat to P was obtained even on soils analyzing high in Olsen’s P. These data suggest the need for working out different limits for low, medium, and high values for Olsen’s P for rice and wheat. For better predictions of the response of rice and wheat to P, the Pfixing capacity of soil should also be considered; the response to P is generally more on low P-fixing soils. Dobermann et al. (1998) pointed out that the initial P flush due to submergence in rice paddies is followed by a decrease from the resorption or precipitation of Fe(ferrous)-P compounds (Kirk et al., 1998; Ponnamperuma, 1972). They further pointed out that a large proportion of P taken up by rice is drawn from P pools that are soluble under alkaline, aerobic conditions

278

R. PRASAD

[Fe(ferric)-P and Al-P], but which are transformed into acid-soluble forms as a result of submergence and reduction (Jianguo and Shuman, 1991; Kirk and Saleque, 1995). Therefore, suitable soil tests for rice should provide an index of this pool. Skogley and Dobermann (1996) further observed that ion-exchange resins can be used to estimate bioavailable nutrients because of their low ion concentrations in soil solution; their application to rice soils has been suggested (Boruah et al., 1993; Turner and Gilliam, 1976; Yang et al., 1992). The ion-exchange resin method has also been suggested as a universal soil test for N, P, K, S, Ca, Mg, Fe, Mn, Zn, Cu, and so on. For both rice and wheat crops it is generally recommended that P should be applied at transplanting/sowing in both India and China. However, several workers in India (Gupta et al., 1975; Katyal, 1978) have reported that application of 50% P at puddling and the rest at tillering (21 days after transplanting) was as effective as an application of all P at puddling. Similarly, some workers (Rana et al., 1978; Singh and Singh, 1979; Singh et al., 1980) have reported that a split application of P in irrigated wheat can be made if necessary. Thus, as compared to a nitrogen split, application of P has no advantage over a single application at transplanting/sowing. However, data available do suggest that if a farmer has failed to apply P at transplanting/sowing, the P requirements of crops can be met partially even by its application by 21 days after transplanting/sowing. In both rice and wheat, this coincides with the application of a second dose of nitrogen. In rice the general practice is to broadcast P at final puddling, which leads to its incorporation in soil. There is really no alternative to it. Katyal (1978) suggested the technique of dipping the rice seedling roots in a P solution or slurry for saving on fertilizer P, but Meelu and Bhandari (1978) failed to find any beneficial effects of this technique. For wheat, which is mostly sown by a fertilizer-cum-seed drill in the RWCS belt, P is generally placed 3–5 cm below and to the side of the seed, which is much better than the broadcast application (Meelu et al., 1974; Ray and Seth, 1975). Tandon (1987) observed that extra yield of wheat brought about by deep placement of P as compared to its surface broadcast application ranges from 300 to 800 kg ha
1. Most phosphate fertilizers containing P in water-soluble form are made by reacting rock phosphate with sulfuric acid or phosphoric acid, thus requiring sulfur as a raw material. Countries such as India, which do not have their own deposits of sulfur, have tried to study the relative efficiency of nitrophosphates, which are made partly or fully from nitric acid, and ordinary or single super phosphate (SSP) and ammonium phosphate (MAP and DAP) (Prasad and Dixit, 1976; Sekhon, 1979). In both rice and wheat, a large number of trials were conducted under the AICARP at research centers, as well as on farmers’ fields during 1953 to 1969. In these trials, SSP and MAP were found to be equally effective on neutral and alkaline soils, but on acid soils, nitrophosphates also performed

RICE–WHEAT CROPPING SYSTEMS

279

well (Chaudhary et al., 1979; Mahapatra et al., 1973; Prasad et al., 1971). For wheat, Hundal and Sekhon (1980) found that nitrophosphate at Ludhiana containing more than 50% water-soluble P (WSP) was as effective as SSP, whereas at Faizabad, Yadav and Verma (1983) found that 50% WSP was optimum for wheat. For rice, 30–50% of WSP in nitrophosphates has been found to be optimum. For RWCS, Misra et al. (1986) concluded that 60% WSP in nitrophosphate was the best, whereas Chaudhary et al. (1979) found DAP and nitrophosphate to be equally effective. Ground rock phosphate has also been tried for both wheat and rice. For wheat in neutral to alkaline soils, rock phosphate was found ineffective, but the rock phosphate–SSP mixture (1:1) was found nearly as effective as SSP (Mishra et al., 1980). In rice, rock phosphate was inferior to SSP or DAP on neutral to alkaline soils (Marwaha and Kanwar, 1981), but was as effective as SSP or DAP on acid soils (Panda, 1980). In conclusion, it may be said that for RWCS some water solubility in P fertilizers is desirable.

3.

Potassium

Soils of the IGP RWCS belt in India are dominated by illite and the associated minerals are vermiculite, chlorite, quartz, feldspar, and kaolinite, whereas in the RCWS, soils in other parts of India (Maharashtra, Gujarat, and Madhya Pradesh) are dominated by smectite and associated minerals are chlorite, kaolinite, illite, allophane, quartz, and feldspar (Tiwari et al., 1992). Total K in the alluvial soils of IGP ranges from 1.28 to 2.77% and exchangeable (1 N NH4OAC) K contents vary from 78 to 273 mg kg
1 soil (Tandon and Sekhon, 1988). Thus, in general, there is sufficient exchangeable K and adequate amounts of K-bearing minerals in the IGP soils to meet the requirements of RWCS. Soils in China practicing RWCS, however, are poor in K and adequate K fertilization is recommended for both rice and wheat (Kawaguchi and Kyuma, 1977; Shihua and Wenqiang, 2000). For 6 tons ha
1 wheat crop the recommended dose of K varies from 100 to 187 kg K ha
1 in the Sichuan province (Yonglu et al., 2000). According to Islam (1995), most of the soils in Bangladesh are low in exchangeable K. Trials on fields with high-yielding varieties of rice and wheat showed a good response to K even in the RWCS belt of IGP (Prasad and Mahapatra, 1970; Raheja et al., 1970; Singh et al., 1976); an application of 50 kg K ha
1 gave a response of 290 and 240 kg ha
1 of wheat and rice, respectively (Randhawa and Tandon, 1982). However, Tiwari et al. (1992), observed that rice tends to respond to potassium more than wheat.

280

R. PRASAD

Table XV Response (kg grain kg
1 K2O) of Rice and Wheat to K (60 kg P2O5 Over Adequate N and P) over Time in RWCS Regions of Indiaa Rice Region

1969–1971

1977–1982

1969–1971

1977–1982

6.7 4.0

8.9 5.8

4.2 2.8

10.6 6.5

3.7

8.2

1.7

5.9

Humid western Himalayan Subhumid Sutlej–Ganga alluvial plains (major RWCS belt) Subhumid to humid eastern and southeastern uplands a

Wheat

From Bhargava et al. (1985).

Table XVI K Balance Under DiVerent Rates of K Application after Four Cycles of Rice–Wheat Cropping Systems at Ludhianaa

K rate 0 25 50 75 a b

Total K uptake (kg ha
1)

Total K applied (kg ha
1)

Rice

Wheat

0 200 400 600

535 563 548 551

348 360 384 404

Total

Net K balance (kg ha
1)

Depletion of available Kb (kg ha
1)

Contribution from nonexchangeable K (%)

883 931 932 955


883
731
532
355

34 28 26 23

96 96 95 94

From Meelu et al. (1995). From surface 0 to 15-cm layer.

The response to K on research centers in India has not been so obvious; this is due to an initial K-rich status of soils. Bhargava et al. (1985) showed that the response of rice and wheat to K at research centers under AICARP increased over time due to the depletion of native soil K (Table XV). In longterm experiments under PDCSR in India, a response to K in the RWCS was obtained in the 12th year on an Alfisol at Pantnagar and in the 13th year on an Entisol at Faizabad (Hegde and Sarkar, 1992). In Kanpur, Tiwari (1985) also showed that the response of both rice and wheat increased over time. This is due to a heavy depletion of K over a long period from the soils by RWCS, as shown by Meelu et al. (1995) at Ludhiana (Table XVI). The average depletion in exchangeable K in Kanpur district soils under RWCS was 17% (Tiwari and Nigam, 1984). Some workers (Singh and Singh, 1978) reported that a response to K was obtained only when high levels of K and adequate P were applied

RICE–WHEAT CROPPING SYSTEMS

281

Table XVII Response of Rice to K at DiVerent Levels of N (Data Averaged over 6 Years)a Grain (tons ha
1) Kg N ha
1 (at 80 kg P2O5 ha
1) 100 150 200 a

Without K

With 50 kg K2O ha
1

kg grain kg
1 K2O

4.14 4.41 4.14

4.38 4.84 5.15

4.9 5.7 10.1

From Singh and Singh (1978).

(Table XVII), but Gangiah and Prasad (1999) and Aipe and Prasad (2001) failed to get a response to K even at high levels of K with adequate P. The most widely used soil test method for available K is 1 M NH4OAC (pH 7.0) extraction, but its suitability as a measure of plant available K remains controversial, especially when soils of different texture and clay mineralogy are considered together (Dobermann et al., 1998; Kemmler, 1980). This is more so due to a large contribution from nonexchangeable K (Table XVI). For lowland rice soils with a high K fixation capacity, K saturation (percentage of total CEC) is considered a better index of plant available K. On alkaline soils, which occupy about 2.5 million ha in IGP (Singh and Singh, 2001), reduced K activity in the soil solution due to preferential adsorption may contribute to low K uptake by rice even when ample K is available (Dobermann et al., 1998). Thus in addition to 1 M NH4OAC extractable K values, other soil properties, such as clay content, nature of clay minerals, CEC, and organic matter content, need to be considered before making recommendations for K fertilization in RWCS. Most K is applied at transplanting of rice or seeding of wheat. Lu and Shi (1982) reported that 51.8% of total K uptake in rice was during ear initiation to heading and 27.7% during grain filling and maturity. Similarly, in wheat, 69.1% of total K uptake was during jointing to ear initiation and 23.8% during flowering to maturity. This suggests a need for top dressing of K at later stages of growth of rice and wheat. A number of researchers in India (Das et al., 1970; Prasad and Chauhan, 2000; Singh and Singh, 1979) have shown the advantage of split application of K. According to Von Uexkull (1976), top dressing of K is advantageous (i) when the natural supply of K from soil and irrigation water decreases during later growth stages of a crop, (ii) when the soil becomes highly reduced (as in rice) and hydrogen sulfide, organic acids, Fe(ferrous), and carbonates accumulate and inhibit K uptake by crop plants, (iii) for poor tillering and late-maturing varieties, and (iv) during wet or rainy seasons. While the best time for top dressing will vary with the variety, soil type, and composition of irrigation water, application at maximum tillering and panicle initiation gives good results (Tiwari et al.,

282

R. PRASAD

1992). Top dressing with K is also useful in soils subjected to leaching losses of K. Mian et al. (1991) reported that leaching losses in Bangladesh could be as high as 0.1 to 0.2 kg K ha
1day
1. Because straw of rice or wheat contains most K, its incorporation or use as a mulch, as recommended in China (Shihua and Wenqiang, 2000), can help in maintaining the K status of soils. This emphasizes the need for residue incorporation in RWCS as discussed earlier. 4.

Balanced NPK Fertilization

Balanced NPK fertilization in RWCS is important (Dev, 1997; Kanwar et al., 1972; Lian, 1989; Mohanty and Mandal, 1989; Prasad, 2000; Prasad and Power, 1994; Rattan and Singh, 1997; Tandon, 1980). Data from some research centers under PDCSR are presented in Table XVIII and these bring out the importance of balanced NPK fertilization in RWCS. The following major points emerged from these data.

Table XVIII Change in Response to NPK over a Period of 10–12 years in RWCS at Some Centers Under AICRPCSa Response kg grain kg
1 nutrientsc

Controlb (tons ha
1)

N

P

Soil

Crop

Ad

Be

Ad

Be

R.S. Pura

Inceptisol

Pantnagar

Mollisol

Faizabad

Entisol

Varanasi

Alfisol

Rudrur

Vertisol

Rice Wheat Rice Wheat Rice Wheat Rice Wheat Rice Wheat

1.49 2.08 3.49 1.07 1.01 0.83 3.42 1.35 2.34 1.22

1.55 0.98 1.33 1.19 0.82 0.60 1.88 1.00 1.12 0.85

20.8 7.3 3.4 19.3 24.2 21.9 7.9 19.6 20.5 20.4

7.3 3.5 7.9 14.3 22.0 17.8 15.6 16.5 23.6 13.3

Center

Ad

K Be

18.7 28.2 12.2 13.0 4.1 7.3 5.1
15.4 14.2 26.4 17.6 33.4 10.7 10.0
0.4 8.3 5.4 36.3 4.8 13.5

Ad

Be


7.5 2.0 8.2 0.7 1.5 12.1 6.4 3.8 4.9 6.2

20.2 68.2 6.6 3.7 7.0 3.0 14.7 18.5 12.0 8.5

a Adapted from Hegde and Sarkar (1992). All India Coordinated Research Project on Cropping Systems, Modipuram. b Control—no fertilizer check plot. Response to P in presence of N and to K in presence of NP. c N at 120 kg N ha
1, P at 35 kg ha
1, and K at 33 kg ha
1. d Start of experiment 1977–1978 to 1980–1981. e Final year for which data were collected: 1986–1987 to 1989–1990.

RICE–WHEAT CROPPING SYSTEMS

283

1. Yields of both rice and wheat without fertilizer declined over time. 2. Response of both rice and wheat to N alone declined over time, showing the need for P and K and other nutrients. 3. Response to P in the presence of N increased over time, showing a decline in the available native soil P. 4. Response to K in the presence of N and P increased over time, showing a decline in the available native soil K. Thus in RWCS, balanced NPK (and S, discussed in the later section) fertilization is a must for sustained production.

5.

Sulfur

After NPK, sulfur is the fourth plant nutrient whose deficiency is widespread in the RWCS belt in India, China, and other countries (Messick and Fan, 2000; Pasricha and Aulakh, 1997; Sakal et al., 2001; Sarkar, 2000; Yadav et al., 2000). The following main factors are responsible for increased S deficiency in a rice–wheat cropping system. 1. Removal of large amounts of S (25–54 kg ha
1year
1) (Yadav et al., 2000c) year after year from the soil due to higher productivity of modern high-yielding varieties of rice and wheat. 2. Use of high-analysis fertilizers urea and DAP, which have replaced S-containing fertilizers such as ammonium sulfate and single super phosphate. 3. Environmental controls have reduced SO2 emission from industries. Atmospheric SOI2 liberated by the combustion of S-containing fossil fuels (coal, oil, and gas) is by far the greatest source of anthropogenic S emission and is the principal source of S for soils (Lefroy et al., 1992). Generally the amount of atmospheric S added to soils in the rural areas of industrialized regions varies between 5 and 10 kg ha
1year
1, whereas it is only 0–5 kg ha
1year
1 in other rural areas of China (Messick and Fan, 2000). 4. In the rice–wheat belt in India, about 20–40% of the soils tested analyzed low in available S (Singh, 2001) and the same is true for China (Messick and Fan, 2000). Because organic-S is an important component of soil S, soils of the RWCS belt in India, Pakistan, and Bangladesh, which are very poor in organic matter (<0.5% organic C), are really poor in native S. The C:N:S ratio was reported to be 100:7.9:1 in Alfisols, 100:8.7:1 in Mollisols, and 100:8.5:0.5 in Inceptisols of India (Tiwari, 1995; Tripathi and Singh, 1992). Generally the C:S ratio in soils in India is about 200:1 (Singh, 2001).

284

R. PRASAD Table XIX EVect of S on Grain Yield of Rice–Wheat Cropping Systema Decrease in grain yield

Center Agwanpur (Bihar)

Meerut (UP)

Mohammedabad (UP)

Gorakhpur (UP)

Average

a

S applied (kg ha
1)

Grain yield (tons ha
1)

tons ha
1

%

Agronomic eYciency kg grain kg
1 S

0 15 30 45 0 15 30 45 0 15 30 45 0 15 30 45 0 15 30 45

4.77 5.90 7.02 7.68 8.90 10.11 12.24 11.73 8.40 9.03 9.80 10.19 7.36 7.66 7.74 7.90 7.36 8.17 8.95 9.39

— 1.13 2.25 2.91 — 1.20 2.33 2.82 — 0.63 1.40 1.79 — 0.30 0.38 0.60 — 0.82 1.54 2.03

— 24 47 61 — 13 26 32 — 8 17 21 — 4 5 8 — 11 22 28

— 75 75 65 — 80 78 63 — 42 47 40 — 20 13 13 — 54 53 45

From Sarkar (2000).

Although cereals respond less to S than sugarcane, sweet potato, vegetables and oilseeds (rapeseed, peanut, soybean), and pulses, (Messick and Fan, 2000; Singh, 2001; Tandon, 1991), a good response to S has been reported for both rice and wheat (Sakal et al., 2000, 2001; Yadav et al., 2000a,c). The results of experiments conducted under TSI/FAI/IFA at four research centers on rice–wheat cropping are presented in Table XIX. In these experiments, 15–45 kg ha
1S was applied to rice and its direct effects on rice and residual effects on the succeeding wheat crop were studied. The response to S application varied from 4 to 61% over no S check. In terms of kg grain kg
1, it varied from 13 to 80%. In China the average response to S fertilization was 15.7 kg kg
1 S for rice and 13.9 kg kg
1 S for wheat (Messick and Fan, 2000). These and several other results from India (Tandon, 1987) and China (Messick and Fan, 2000) clearly show that S should be included in the balanced fertilizer recommendations for RWCS. Data for S balance in rice–rice cropping system are available from China and are given in Table XX. These results show a negative balance of
6 kg S ha
1year
1 when only NPK was applied. With the application

RICE–WHEAT CROPPING SYSTEMS

285

Table XX Sulfur Balance as AVected by S Fertilization in Rice–Rice Cropping System in the Guangdong Province of Chinaa

Treatment NPK NPKþ19.5 kg S ha
1 year
1 NPKþ30 kg S ha
1 year
1 NPKþmanure (kg S ha
1year
1) a

Rain þ irrigation (kg ha
1 year
1)

Crop removed (kg ha
1 year
1)

Leaching þ RunoV (kg ha
1 year
1)

Balance (kg ha
1 year
1)

10.5 10.5

10.5 12.0

6.0 6.0


6.0 12.0

10.5

15.0

6.0

19.5

10.5

12.0

6.0

16.5

From Messick and Fan (2000). Table XXI Recommendations for S Addition for DiVerent Crops on the Basis of Soil Test Value (0.15% CaCl Extractable)a

Available S (mg kg
1 soil)

S fertility class

Recommended dose of S (kg ha
1) for rice/wheat

Expected increase in yield (%)

<5 5–10 10–15 15–20 >20

Very low Low Medium High Very high

60 45 30 15 0

25–85 20–50 5–20 1–5 0

a

From Singh (2001).

of S or manure, the S balance was positive (12.0–19.5 kg S ha
1year
1) (Messick and Fan, 2000). Sulfur extracted by 0.15% CaCl2 (Williams and Steinburgs, 1959) has been found to be well correlated to the response of crops to S (Ghai et al., 1984; Shukla, 2001). With this method, a value of 10 mg kg
1 soil or less is considered low and a crop response to S is expected (Sarkar, 2000). Available S values, sulfur deficiency class, recommended amount of S, and expected increase in yield are given in Table XXI. Because S requirements of crops are more at early stages of growth, generally its application at transplanting/sowing of rice/wheat is recommended. When pyrite is used as a source it should be broadcast 7–10 days before transplanting/sowing. If the S application is missed at sowing, it may be top dressed up to 20–40 days after sowing (Singh, 2001). When soil application is not made at sowing and S deficiency symptoms are seen at later

286

R. PRASAD

stages of growth of the crop, three to five foliar applications of soluble salts of S, such as ammonium sulfate, potassium sulfate, and zinc sulfate, can be made (Singh, 2001). Soil application at sowing is the most effective method of S fertilization. The most commonly used sources of S, along with their S contents, are single superphosphate (12% S and 16% P2O5); ammonium sulfate (24% S and 21% N); ammonium phosphate sulfate (15% S, 16–20% N, and 20% P2O5); potassium sulfate (18% S and 50% K2O); zinc sulfate (15% S and 20% Zn); gypsum (13–20% S); elemental S (85–100% S); iron pyrites (22–24% S); phosphogypsum (11% S); and organic manure (varying content of S). Data from several experiments in India showed that ammonium sulfate, single superphosphate, elemental S, gypsum, and pyrites were equally efficient for most crops given in divergent soil-crop management situations in different agroecological regions (Singh, 2001).

6.

Micronutrients

With the adoption of modern HYV of rice and wheat and the application of high doses of NPK resulting in the removal of high amounts of micronutrients (Table XXII), their deficiencies have emerged in RWCS belts in most countries where the system is practiced. In India, a Zn deficiency was discovered first at Pantnagar (Nene, 1966) in tarai (forest hill) soils and then almost everywhere in the RWCS (Takkar and Randhawa, 1978). Similarly, a deficiency of iron in rice on coarse-textured alkaline soils was observed by Takkar and Nayyar (1979) and that of Mn in sandy to loam soils of Punjab for wheat in RWCS (Takkar and Nayyar, 1981). In highly calcareous soils of Bihar, Singh et al. (1985) reported that B deficiency is one of the constraints for sustaining high yields in RWCS. The percentages of soil samples analyzing low for different micronutrients in different states of India where RWCS is practiced are shown in Table XXIII. A deficiency of Zn is prevalent on all soils in all states. The deficiency of Fe is found to be the largest in sierozems of Haryana and lesser in Inceptisols and Entisols of Punjab and UP. Mn turns out to be the most serious constraint in coarse-textured Ustochrepts and Ustopsammants in Haryana, Punjab, and UP. A deficiency of B is most prevalent in calcareous soils of Bihar and in Entisols, Inceptisols, and Vertisols of Uttar Pradesh and Madhya Pradesh (Bansal et al., 1991; Dwivedi et al., 1993; Sakal et al., 1988). No Mo deficiency has yet been reported in rice and wheat. Of the various micronutrients, Zn is now included in fertilizer recommendations for the entire RWCS belt in India. Data on the removal of micronutrients by RWCS for some locations in India are given in Table XXII. In China, Mn and Mo are required by wheat and Zn by rice (Shihua and Wenqiang, 2000). The available Mo content in all RWCS soils is low

RICE–WHEAT CROPPING SYSTEMS

287

Table XXII Removal of Some Micronutrients (g ha
1 year
1) by RWCS in Indiaa

Cropping system

Economic produce (tons ha
1)

Zn

Cu

Fe

Mn

Rice–wheat–sorghum Rice–wheat–mungbean Rice–wheat Rice–wheat–cowpea(F)b

5.98 4.43 10.10 13.73

606 445 250 946

262 208 190 652

4583 4258 3430 5982

1238 879 800 1204

Location Pusa Hisar Pantnagar a b

From Rattan et al. (1999). Fodder.

Table XXIII Percentage (%) of Soil Samples Deficient in DiVerent Micronutrients in DiVerent States of India Where RWCS Is Practiceda State

Zn

Cu

Fe

Bihar Haryana Madhya Pradesh Punjab Uttar Pradesh West Bengal

47 62 63 47 64 9–68

2 0.5 0.1 0.1 0.4 —

4 26 3 12 9 —

a

Mn <1 4 3 2 6 —

B

Mo

31 — 22 — 24 —

— 28 18 — — —

Adapted from Takkar et al. (1997).

Table XXIV Average Content (mg kg
1) of Selected Micronutrients in Major Soil Types of RWCS in Chinaa Zn Soil Red soil Yellow earth Purple soil Limestone soil a

Mn

Mo

Total

Available

Total

Available

Total

Available

177 81 109 236

3.0 2.1 2.1 1.5

565 373 548 2264

120 70 206 746

2.43 1.53 0.55 0.68

0.14 0.14 0.08 0.14

From Shihua and Wenqiang (2000).

(Table XXIV), especially in arid soils where Mo is highly bound by Fe and Al oxides and is not available to crops (Li, 1983). Mn deficiency occurs in wheat only in the calcareous purple soils and light-textured alluvial soils in the upper Sichuan (Hu et al., 1981). However, on acid red and yellow soils, Mn could reach toxicity levels for both rice and wheat.

288

R. PRASAD Table XXV Threshold Values of Micronutrients in Rice and Wheat Plants Under Sand/Soila Culture Threshold values (mg kg
1)

Micro nutrient Zinc Cu Mn B a

Crop

Plant part

Crop/age (days after emergence/ transplanting)

Rice Wheat Rice Wheat Rice Wheat Rice Wheat

Leaves Leaves Leaves Top plants Leaves Leaves Young leaves Leaves

42–56 35 30–40 35 30–35 70 48 14–21

Acute

Deficient

SuYcient

Toxic

10 10 2 3 — 7 15 —

15 15 5 4 10 25 20 4

20 20 5 6 50 60 40 35

— 100 40 — — — 50 600

From Takkar et al. (1989).

The DTPA extractable micronutrient test (Lindsay and Norvell, 1978) has been found most successful in India for analyses of Zn, Fe, Cu, and Mn. For hot water-soluble B, the method of Berger and Tuog (1939) is being used. For Mo, the acid ammonium oxalate procedure of Grigg (1953) is used. The critical value of DTPA extractable Zn for rice in Indian soil ranges from 0.45 mg kg
1 soil for alluvial sandy soil to 0.70 mg kg
1 soil for the calcareous soils of Bihar in the RWCS belt. A critical value for DTPA-Mn for wheat was 4.0 to 4.7 mg kg
1 soil in Ustochrepts and Ustiprammants of Haryana and Madhya Pradesh and a value of 3.0 mg kg
1 soil was observed for the alluvial soils of Punjab. Regarding B, 0.52 mg kg
1 soil hot watersoluble B was considered critical (Singh, 1992). Plant tissue analysis is also used for determining micronutrient deficiencies in the RWCS belt in India, and the threshold values for different micronutrients in rice and wheat are given in Table XXV. These threshold values, determined under laboratory conditions, need confirmation under field conditions. For example, threshhold values of Zn, Mn, and B for rice are 15, 10, and 20 mg kg
1 leaf dry matter. These values could vary with variety, soil, and weather conditions. a. Zinc. A soil application of 10–25 kg ha
1 (higher doses for heavier soils) zinc sulfate (ZnSO4 · 7H2O) (21–22% Zn) is considered the best method, although dipping of rice seedlings at transplanting in 2–4% ZnSO4 has been found to be quite effective (Takkar et al., 1997). Studies show that a soil application of zinc sulfate may not be necessary each year or at least lower doses could be used in subsequent years. For example, in a study in Punjab, an application of 5.5 kg Zn ha
1 for the first four crops in the RWCS

RICE–WHEAT CROPPING SYSTEMS

289

followed by 2.75 kg Zn ha
1 for the next 8 crops was adequate (Takkar et al., 1997). A foliar application of zinc (0.5% solution of zinc sulfate mixed with some lime) may be used when a deficiency is detected at a later stage in the crop. b. Iron and Manganese. An iron deficiency is noted in upland rice or dryland rice nurseries and can be easily overcome by flooding the field or nursery bed. When the deficiency is seen in growing crops, a foliar application of a 0.5% solution of ferrous sulfate (FeSO4  7HO) (19% Fe) or FeEDTA solution can be used. Several sprays at 7- to 10-day intervals may be required. For soil application, a dose of 10–12 kg ha
1 ferrous sulfate is recommended. For manganese, a foliar application of sulfate (MnSO4 · 4H2O) (26–28% Mn) mixed with lime is preferred over soil application. It should be mentioned that Fe and Mn are present in soil in large amounts and changing the soil condition can overcome their deficiency, e.g., flooding the soils for upland rice. The addition of organic manure and green manuring can also help overcome these deficiencies. Another alternative is to use Fe and/or Mn efficient cultivars of rice and wheat. For example, Takkar et al. (1997) reported that wheat cultivars HD 2329, WH542, KSM3, PBW222, and KAL1-4 were able to take up more Mn from the soil and thus are more Mn efficient. c. Boron. For B, soil application is preferred and the sources are Borax (11% B), fertilizer borate (14% B), and boric acid (20% B); only 1–2 kg B ha
1 is required.

7.

Integrated Nutrient Management

As already pointed out, modern high-yielding varieties of both rice and wheat are heavy feeders of plant nutrients. To meet these heavy demands of plant nutrients, farmers have mostly resorted to the use of inorganic fertilizers, and the age-old practice of applying organic manures to the farm fields has almost vanished. Because farmers mostly apply large doses of N and some P and K, their continuous application sans organic manures has created deficiencies of secondary and micronutrients, which have already been discussed. This has led to the decline in yields of rice, wheat, or both (Nambiar and Abrol, 1989; Yadav, 1998, Yadav et al., 1998). Yadav (1998) reported that, on average at several locations in the PDCSR, continuous rice–wheat cropping for 16 years decreased the yield by 57% in unfertilized plots and by 32% in plots receiving N and P. Yadav et al. (1998) further reported that the highest rate of decline (89 kg ha
1year
1 in rice and 175 kg ha
1year
1 in wheat) was found when 120 kg

290

R. PRASAD

N ha
1 was applied. However, when balanced fertilization was practiced and 120 kg N, 35 kg P, and 33 kg K ha
1 were applied, the rate of decline in yield was reduced to 25 kg ha
1year
1 in rice and 62 kg ha
1year
1 in wheat. Yadav et al. (2000b) also showed that at some centers there was a general decline in partial factor productivity (kg grain kg
1 NPK) of fertilizers over the years (11 to 14 cycles of R-W cropping), e.g., at Ludhiana it decreased from 28.3 at the start of the study (1983–1984) to 24.9 at the end of the study (1996–1997). This forces the farmers to apply more and more fertilizer over the years to get the same increase in yield as in previous years This further deteriorates soil fertility and also creates environmental problems. For example, in Punjab, there has been an increase in nitrate content in well waters due to an increased use of nitrogen fertilizer (Singh et al., 1995). Integrated nutrient management (INM) involving the use of organic manures, green manures, and biofertilizers to meet part of the nutrient requirement is the only way to combat the situation. Studies on the possible substitution of inorganic N by FYM or Sesbania green manuring were conducted under PDCSR, and some data are presented in Table XXVI, which clearly show that the same yields of rice and wheat can be obtained with a 25% substitution of N by FYM or a 50% substitution of N with Sesbania GM applied to rice as with a 100% of recommended dose of NPK applied to rice and wheat (Hegde, 1998a,b). In New Delhi, Misra and Prasad (2000) showed that an application of 120 kg N ha
1 produced 8 tons ha
1year
1 grain in RWCS. This could be achieved by Sesbania cowpea (Vigna unguiculata) GM or FYM applied to rice without any fertilizer N; with 80 kg N ha
1 the grain yield of RWCS could be increased to 9 tons ha
1year
1. Information on integrated nutrient management is also available from the All India Coordinated Research Project on Long-Term Fertilizer (LTFE) scheme of the Indian Council of Agricultural Research in a number of cropping systems, including RWCS. Results from an experiment under this scheme at Pantnagar started in 1971 showed that continuous cropping of rice–wheat for 25 years reduced soil organic C from 1.48% to 0.5%, available P from 18 to 6.4 kg ha
1, available K from 125 to 99 kg ha
1, and available Zn from 2.70 to 0.79 mg kg
1. Application of 8 tons ha
1 FYM to wheat each year along with 100% of the recommended NPK led to higher crop yields, restored the original organic C status, and improved the availability of P, K, Zn, Fe, Mn, and Cu in the soil (Ram, 1998). From a study conducted from 1974 to 1997 on an alkali soil at Karnal, Swarup and Yaduvanshi (1998) also concluded that an application of FYM or Sesbania aculeate green manuring along with a judicious application of N, P, and Zn sustained RWCS. Meelu and Rekhi (1981) and Meelu et al. (1994) also showed the advantage of green manuring in rice–wheat CS in Punjab. With all the merits of FYM and green manuring, these practices have not really caught on with the farmers (Das and Biswas, 2002). With the

Table XXVI EVect of Integrated Nutrient Management on Grain Yield (tons ha
1) of Rice and Wheat at Some Research Centers Under AICRPCS in the Indogangetic Plains (IGP) of India (Average over 7–10 Rice–Wheat Cycles)a

Treatment (rice þ wheat) Control (no fertilizer) NPK þ NPKb N (50% FYM)c

Faizabad (Fluvents silt loam)

Varanasi (Aeric ochroqualfs silty loam)

Kanpur (Udic ustochrepts loam)

Kalyani (Fluvents clay loam)

Rice

Wheat

Total

Rice

Wheat

Total

Rice

Wheat

Total

Rice

Wheat

Total

Rice

Wheat

Total

Rice

Wheat

Total

2.1

1.2

3.3

3.0

1.7

4.7

1.6

1.1

2.7

1.1

1.0

2.1

1.9

1.0

2.9

1.3

0.8

2.1

6.3 5.7

4.5 4.7

09.8 10.4

4.7 4.0

4.0 3.8

8.7 7.8

4.0 3.5

4.6 4.6

8.6 8.1

4.0 3.7

4.0 4.3

8.0 8.0

4.3 4.1

3.3 3.5

7.6 7.6

3.5 3.4

2.6 2.4

6.1 6.3

6.0

4.2

10.2

4.1

3.7

7.8

3.7

4.3

8.0

4.0

3.8

7.8

4.4

3.1

7.5

3.7

2.7

6.4

6.3

4.4

10.7

4.4

3.9

8.3

3.6

4.7

8.3

3.6

4.2

7.8

4.1

3.2

6.9

3.7

2.9

6.6

6.6

4.0

10.6

4.5

3.7

8.2

3.9

4.7

8.6

3.9

3.9

7.8

4.3

3.0

7.3

3.8

2.3

6.1

0.15

0.12

0.22

0.12

0.17

0.12

0.13

0.10

0.16

0.12

0.15

0.12

PKþNPK N (25% FYM) PKþNPK N (50%) GMPK þ NPK N (25%) GMPK þ NPK LSD (P¼0.05)

RICE–WHEAT CROPPING SYSTEMS

Pantnagar (Hapludoll silty clay loam)

Ludhiana (Ustochrept loamy sand)

a

From Hegde (1998a,b). NPK (kg ha
1): Rice: Ludhiana 120-131-25.2; Pantnagar 120-26.2; Kanpur 120-26.2-50.4; Varanasi 120-26.2-33.6; Faizabad 120-26.2-50.4; and Kalyani 80-21.8-33.6. Wheat: Ludhiana 120-26.2-25.2; Pantnagar 120-26.2-50.4; Kanpur 120-26.2-50.4; Varanasi 120-26.2-33.6; Faizabad 120-26.250.4; and Kalyani 120-26.2-33.6. c Figures in parentheses indicate percentage of N supplied through FYM/Sesbania green manure in rice. b

291

292

R. PRASAD Table XXVII EVect of Sesbania Green Manuring (GM) and Mungbean Residue Incorporation (RI) on Grain Yield and Nitrogen Uptake by Rice and Wheat in RWCSa Grain (tons/ha)

Treatment Fallow Sesbania (GM)b Mungbean (RI) LSD (P ¼ 0.05)

Nitrogen uptake (kg/ha) in above ground parts

Mungbean

Rice

Wheat

Total

Mungbean

Rice

Wheat

Total

— — 1.3 —

5.0 5.3 5.3 0.13

3.2 3.4 3.6 0.18

8.2 8.6 8.9

— — 119.6 —

86.9 108.9 110.6 2.90

83.0 88.0 93.7 4.85

169.9 196.9 204.3

a

From Sharma et al. (1995). Plant N incorporated in soil due to Sesbania GM was 78.1 kg/ha, whereas that of mungbean was 6.8 kg/ha. b

mechanization of agriculture in the RWCS belt in IGP, the number of animals on the farm fields has been reduced considerably and FYM is simply not available. Similarly, green manuring has not found favor with farmers due to a lack of immediate monetary returns. Sharma et al. (1995) and Sharma and Prasad (1999) have therefore suggested the growing of shortduration (60 days) mungbean (Vigna radiata) during the summer months (May and June—the period between wheat harvest and rice transplanting), taking one picking and incorporating the legume residue before transplanting rice. This practice was found to be as effective as green manuring with Sesbania in RWCS and increased the productivity of the cropping system (rice þ wheat) by 0.7 tons ha
1year
1 and plant N uptake by 34 kg ha
1year
1 (Table XXVII). These studies showed a fertilizer N saving of 30–120 kg N ha
1 in RWCS. In addition, it gives a yield of 0.5 to 1.1 tons ha
1 of protein-rich grain of mungbean, which is so important for a protein– malnutritioned country such as India. This practice was also as good as green manuring with Sesbania in preventing the decline in soil organic C as observed in plots receiving only inorganic fertilizer (Prasad and Misra, 2001). Growing of summer mungbean in RWCS was tested on the farmers’ fields in Delhi during 1995–1996 and 1996–1997 (Sharma et al., 2000a). In 1995–1996, N was applied at 60 or 120 kg N ha
1 (with 20 kg P and 4 kg Zn ha
1), whereas in 1996–1997 there was only one dose of 90 kg N ha
1. Wheat was grown with 40 kg N, 20 kg P, and 30 kg K ha
1 to study the residual effects. Incorporation of mungbean residue increased the total productivity of RWCS over summer fallow by 1.0–2.5 tons ha
1 at 60 kg N ha
1 and 0.3–2.5 tons ha
1 at 120 kg N ha
1 in 1995–1996; in 1996–1997 the increase was 0.5 to 2.6 tons ha
1. In addition, 0.7-0.8 ton ha
1 proteinrich pulse grain was produced. The Food and Agriculture Organization

RICE–WHEAT CROPPING SYSTEMS

293

(FAO) of the United Nations has developed an IPNS model for the rice– wheat system (Roy and Ange, 1991). Using this model, it was predicted that the potential of the rice–wheat system was 11 tons ha
1 using 240 kg N, 39 kg P, and 100 kg K ha
1. By inclusion of a short-duration legume, taking a picking of pods and incorporating its residues in soil not only produced 1 ton ha
1 additional protein rich grain, but also made a net savings of 30 kg N ha
1. Thus the studies in India show the advantage of applying FYM and green manuring in RWCS. A more practical alternative seems to be growing of a short-duration mungbean, taking a picking of pods, and incorporating the legume residue. This also provides the farmer with a source of income at the end of the summer season and before rice transplanting and he/she will have cash in hand to invest in rice–wheat production. Quayyum et al. (2001) from Bangladesh also recommended growing mungbean after wheat and before rice for a sustainable RWCS. In addition to the contribution of Rhizobium through green manure/ legume residue/legumes in RWCS, other biofertilizers, such as blue green algae (BGA) and azolla, have a role in rice culture and can save 20–30 kg N ha
1 (Bhagyaraj and Tilak, 1997; Goyal, 1993; Kannaiyan, 1993; Singh, 1997; Singh and Bisoyi, 1989; Singh et al., 1990a; Venkataraman, 1979), whereas Azotobacter can fix 10–25 kg N ha
1 in wheat (Pandey and Kumar, 1989). However, no reports are available on the use of these biofertilziers in rice–wheat cropping systems as a whole. There has also been considerable research in India on phosphatesolubilizing organisms (PSO) and some of this concerns rice and wheat (Chhonkar and Tilak, 1997). The introduction of PSOs (Pseudomonas striata, Bacillus polymyxa, Aspergillus avamori, Penicillium digitatum, etc.) in the rhizosphere of rice and wheat (or other crops) increases the availability of P from insoluble phosphates such as rock phosphate and increases the utilization efficiency of ordinary superphosphate (Chhonkar, 1994). Inoculation of seeds or seedlings with PSOs can provide 13 kg P ha
1 equivalent of ordinary super phosphate (Gaur, 1990). PSOs could be useful in sustaining crop yields in RWCS when adequate P fertilization is not made.

D.

IRRIGATION 1.

AND

WATER MANAGEMENT

Irrigated Water Availability

In Asia, where water has always been regarded as an abundant resource, its per capita availability declined by 40–60% between 1955 and 1990; projections of the International Rice Research Institute, Manila, suggest that most Asian countries will have some water problems by the year 2025

294

R. PRASAD Table XXVIII Percentage (%) of Arable Land Under Irrigation in RWCS Countriesa

Country Bangladesh China India Nepal Pakistan a

1961

1990

2000

2020

5 29 15 4 64

26 45 26 33 81

32 44 29 44 87

37 45 32 54 94

From Gill (1994).

(IRRI, 1995). Agriculture in Asia accounts for 86% of total annual water withdrawals compared with 49% in North and Central America and 38% in Europe. Irrigated rice, in particular, is a heavy consumer of water; it takes 5000 liters of water to produce 1 kg rice, and RWCS consumes about 11,650 m3ha
1 water out of which 7650 m3ha
1 is by rice (IRRI, 1995). Assured irrigation is crucial for high yields in the intensive RWCS. The total irrigated area in Asia has increased rapidly from 80 million ha in 1960 to 132 million ha in 1990, an increase of 65% (Gill, 1994). Irrigated land as a percentage of total available land in five RWCS countries is given in Table XXVIII. Pakistan has the highest percentage of irrigated land, followed by Nepal and China. The importance of irrigation water in RWCS can be judged from the fact that Ladha et al. (2000) have divided the RWCS environments on the basis of the availability of irrigation water. 1. Favorable RWCS environments (FE)—areas with predominantly irrigated rice and wheat, e.g., state of Punjab in India and Pakistan and states of Haryana and western Uttar Pradesh in India. 2. Less favorable RWCS environments (LFE)—areas with predominantly rain-fed rice and irrigated/rainfed wheat, e.g., states of eastern Uttar Pradesh, Bihar, and West Bengal in India. Yields of rice and wheat obtained under these two environments are shown in Table XXIX; yields of both rice and wheat are much higher under FE than under LFE. Furthermore, data in Table XXIX are state averages; many farmers under FE produce as much as 8–9 tons ha
1 of rice and 5–6 tons ha
1 of wheat in Punjab and Haryana. Similarly, in the Sichuan province of China, the highest yield of rice recorded was 10.6 tons ha
1, whereas that of wheat was 6 tons ha
1 under FE (Jiaguo, 2000). Thus, under FE the total grain production for RWCS can be 14–16 tons ha
1, which is very close to the potential yields of 17–18 tons ha
1 predicted for

RICE–WHEAT CROPPING SYSTEMS

295

Table XXIX Wheat and Rice Yields (tons ha
1) Under Favorable (FE) and Less Favorable Environments (LFE) RWCS in Indiaa

States

FE

LFE

% of wheat area under irrigationc

Punjabd Haryana U.P. Bihar West Bengal

3.69 3.57 2.28 1.79 —

— — 2.43 1.71 2.00

96.7 98.4 92.2 87.8 72.5

Wheatb

FE

LFE

% of rice area under irrigationc

4.84 4.29 3.04 2.29 —

— — 2.45 1.58 2.68

99.1 99.6 60.4 30.8 24.6

Riceb

a

From Ladha et al. (2000). 1990–1993. c 1994–1995. d Punjab and Haryana are predominantly wheat states, whereas Bihar and West Bengal are predominantly rice states. In UP, the western part is predominantly a wheat area, whereas eastern UP is predominantly a rice area. b

India (Agarwal et al., 2000). One reason for the higher rice yields in China is that a major part of the rice area is under hybrid rice, which produces at least 1 ton ha
1 more than the prevailing HYV grown in India (Vidyachandra and Gubbiah, 1997). Another reason for lower rice yields in the FE RWCS belt in India is the preference for fine grain quality such as Pusa Basmati-1, which has a yield potential of 5.5 tons ha
1 and covers large tracts in the states of Haryana and western Uttar Pradesh. Basmati-type rice fetches better prices in the market and overcomes the disadvantage of its lower yields as compared to hybrids and other high-yielding varieties of rice. As regarding the source of water in India, tube wells are a major source in the FE region in western Uttar Pradesh, Haryana, and Punjab, whereas canal water is the major contributor in the LFE region in eastern Uttar Pradesh, Bihar, and West Bengal. Of late there has been great concern in India regarding overirrigation of rice and wheat in the FE region due to the free availability of water from tube wells (the electricity for agriculture is at low rates). This has created alarming changes in the water table depending on the area’s hydrology. In some pockets the water table has been pushed down so much that the overall natural vegetation of the area is decreasing, whereas in other regions, the rising water table is creating salinity/sodicity. Data in Table XXX clearly show the negative water table balance in parts of Haryana and Punjab states of India. However, Jagannath (2000) pointed out that in some parts of Haryana, the water table is rising at a rate of 10–30 cm year
1. Reasons for this include (i) seepage from the canal system,

296

R. PRASAD Table XXX Water Balance in Parts of Haryana and Punjab when RWCS Is Practiceda

District

Usable discharge (mm)

Draft (mm) (1989–1990)

Balance (mm) (1989–1990)

Haryana

Karnal Kurukshetra

1089 658

1499 1307


410
649

Punjab

Ludhiana Jalandhar Kapurthala Sangrur

1264 703 334 1285

1954 1491 668 2190


690
788
334
905

State

a

From Joshi and Tyagi (1991).

(ii) seepage from water courses and field channels, (iii) deep percolation from irrigated rice and wheat areas as a result of overirrigation, and (iv) development of a perch water table due to an impermeable layer. Water management in RWCS can be optimized by appropriate soil management to reduce percolation, proper scheduling of irrigation, use of the ground water, and utilization of rain water. 2. a.

Rice

Soil Management Practices.

i. Puddling. Puddling is associated with rice culture in all rice-growing countries. In this process, soil is worked with water to render it less pervious; the soil particles are reoriented and noncapillary pore space is destroyed (De Datta, 1981). Bodman and Rubin (1948) observed that puddling reduced the specific volume of a silty clay loam from 1.9 to 1.2 cm3g
1 in about 10 s. A puddled soil holds more water at lower potentials than in its natural state. Also, drying is slower in puddled than in nonpuddled soil. Puddling increases the bulk density of soil, reduces the hydraulic conductivity (and thereby percolation losses) and water requirement by rice (Table XXXI), reduces weeds, and eases transplanting (Sharma and De Datta, 1986. Furthermore, Singh et al. (2001) reported that puddling not only resulted in higher yields of rice but also of succeeding wheat over nonpuddling and saved 75 mm ha of irrigation water (Table XXXII). Similar results were reported by Samra and Dhillon (2000) from Ludhiana. Direct seeded rice has to be sown at the time of raising nursery during the hot summer months and has to be irrigated frequently.

RICE–WHEAT CROPPING SYSTEMS

297

Table XXXI EVect of Puddling on Bulk Density and Hydraulic Conductivity of Soil and Water Requirements of Ricea

Treatment Control Puddling Compaction a

Bulk density (g cm
3)

Hydraulic conductivity (10
4 cm s
1)

Water requirement of rice (mm)

1.46 1.73 1.68

5.70 0.45 0.48

3174 1532 1648

From Mitra and Ghosh (1989).

Table XXXII EVect of Puddling and Method of Seeding Rice on Grain Yields of Rice and Succeeding Wheat and Irrigation Water Requirement (Means over 3 Years)a Irrigation water requirement (mm ha
1)

Grain (tons ha
1) Treatments No puddling Direct seeding Transplanting Mean Puddling Direct seeding Transplanting Mean a

Rice

Wheat

Total

Rice

Wheat

Total

3.0 3.6 3.3

3.3 3.5 3.4

6.3 7.1 6.7

1500 1575 1537

400 400 400

1900 1975 1937

3.8 4.5 4.1

3.7 3.7 3.7

7.5 8.2 7.8

1475 1450 1462

400 400 400

1875 1850 1862

From Singh et al. (2001a).

One or two harrowings at optimum moisture for dry tillage followed by two puddlings by a rotary puddler and planking are generally enough for a good puddle. More than half the water requirement in rice production is often used to prepare the land (including puddling) and most of it is lost through percolation. Rice soils develop cracks on drying and about 60% of water applied percolates through these cracks (IRRI, 1995). ii. Compaction. Compaction is an alternative to puddling (Gupta et al., 1981) and requires less water. It refers to an increase in the bulk density of soil using a dynamic load. Its advantages are similar to those of puddling, which include increasing bulk density, reducing the hydraulic conductivity of soils, and reducing the water requirement by the rice crop (Table XXXI). Gupta and Woodhead (1989) reported that deep ploughing of the soil followed by compaction at optimum moisture by four to six passes of

298

R. PRASAD

an 800-kg roller was adequate. Compaction to a 5-cm depth for rice and a 10-cm depth for wheat significantly increased the productivity of RWCS. However, this practice has yet not been adopted by farmers. iii. Bunding. This is widely practiced by rice farmers all over the world. Bunding retains rain water. Rice farmers in several countries have permanent bunds. Because there is also much seepage loss through these bunds, many farmers plaster the bunds with mud to reduce these losses (IRRI, 1995). Bhuiyan et al. (1979) reported that in rain-fed rice, an increase in spillway height from 2 to 12 cm increased the depth of submergence and consequently reduced the number of water stress days during crop growth. iv. Critical growth stages. Water use by rice crop increases with crop age and is maximum during booting to flowering when evapotranspiration (ET) is the highest. Singh and Mishra (1974) reported that a 50% depletion of available water at the panicle initiation stage reduced the yield by about 34% and that at stem elongation and tillering stages the yields were reduced by 29 and 19%, respectively. De Datta et al. (1975) also reported that a soil water potential of
75 cb during the vegetative stage reduced grain yield by about 1.5 ton ha
1, whereas during the reproductive phase it reduced the yield by 2.5 tons ha
1 (over 50%). Water stress during the reproductive phase is a major factor reducing rice yields in rain-fed rice. v. Submergence. Most rice farmers consider continuous submergence of rice fields essential for good yields, leading to overirrigation in the RWCS belt in the IGP of India. Available data suggest that flooding to field capacity throughout the rice crop considerably reduces the number of irrigations and the amount of water used. It also gives higher water use efficiency. As regarding the depth of submergence, a depth of 3–10 cm is sufficient for the optimum yield and control of most weeds (Batchelor and Roberts, 1983; Oelke and Mueller, 1969; Pandey and Mitra, 1971). Tripathi (1992) showed that 7.5 cm ponding 3 days after drying of the soil was the best water management practice for soils varying from sandy loam to clay loam (Table XXXIII). This practice gave yields that were statistically not different from those obtained with continuous ponding and reduced water and irrigation requirement, runoff, percolation, and ET. Similar results were reported by other workers in RWCS in IGP (Moolani et al., 1968; Singh and Pal, 1973). 3.

Wheat

Wheat in the RWCS belt in IGP is an irrigated crop. The number of irrigations given depends on the (i) growth period of wheat—less irrigation in eastern IGP where wheat matures in March–April, (ii) soil type—more on

RICE–WHEAT CROPPING SYSTEMS

299

Table XXXIII EVect of Irrigation Practices on Grain Yield of Rice, Water and Irrigation Requirements and RunoV, Percolation, and Evapotranspiration Losses on DiVerent Soils (Average of 2 Years) (Rainfall 648 mm)a Clay loam Factors
1

Grain (tons ha ) Water requirement (mm) Irrigation requirement (mm) RunoV (mm) Percolation (mm) Evapo-transpiration (mm)

Silty clay loam

Sandy loam

Loam

Ab

Bc

A

B

A

B

A

B

6.01 1583 1125 207 893 690

5.53 1139 637 164 569 569

6.10 1602 1200 191 870 732

5.63 1220 787 150 599 621

6.31 1995 1500 149 1187 808

5.81 1523 975 140 893 625

5.62 2261 1775 161 1515 745

4.56 1806 1275 140 1154 65

a

From Tripathi (1992). Continous ponding 52.5 cm. c 7.5 cm ponding 3 days after drying of soil. b

lighter soils, e.g., Psamments, (iii) rainfall received, and (iv) contribution of the water table. Considerable research has been conducted in India on the irrigation of wheat. Earlier workers paid attention to the depth of irrigation. Singh (1945) reported that the first irrigation should be given when the soil dried to 66.75% of the field capacity by applying 7.6 cm of water. Gautam et al. (1966) and Raheja (1961) also suggested an irrigation depth of 6.7 to 7.6 cm. Prihar et al. (1978a) also pointed out that a 7- to 8-cm depth of irrigation water followed by most farmers who grow dwarf wheats was well within safe limits for loamy sand to sandy loam soils of Punjab. Later studies involved a climatological approach (Bandyopadhyay, 1997), and the irrigation depth/cumulative U.S. Pan evaporation (ID/CPE) ratio was used for scheduling irrigation. Prihar et al. (1978a,b) obtained maximum wheat yields and high water use efficiency in Punjab with ID/CPE ¼ 0.9 to 1.0 with 4.5 to 7.5 cm water from irrigation. In addition, wheat required 8–10 cm water for pre-sowing irrigation. There have been some efforts to study soil–plant–atmospheric water relationship, CO2, H2O exchange of crop canopy, crop modeling, and water production functions and development of crop coefficients (Kc) of wheat (Minhas et al., 1974; Kumar et al., 1985; Singh and Singh, 1997). Kc values measured at Karnal for tillering, heading, grain formation, and maturity were 0.47, 1.17, 1.02, and 6.35, respectively (Tyagi et al., 2000). A similar pattern in values was recorded at Pantnagar, with the maximum

300

R. PRASAD Table XXXIV EVect of DiVerent Growth Stages on Grain Yield of Wheat (tons ha
1)a

Irrigation at No irrigation CRI,b LT, LJ, F, M CRI CRI, LJ CRI, F CRI, M CRI, LT, F CRI, LT, M CRI, LJ, F CRI, LJ, M CRI, LT, LJ, F CRI, LT, LJ, M LSD (P¼0.05) a b

Clay loam (WT 0.4–0.8 m)

Silty clay loam (WT 0.66–1.4 m)

Loam (WT 1.8–2.4 m)

2.90 4.41 3.85 3.98 4.11 3.97 4.21 3.94 4.25 4.11 4.21 4.17 0.58

3.45 5.49 4.41 4.58 4.97 4.68 5.11 4.72 5.27 5.00 5.04 5.47 0.61

3.61 5.26 4.25 4.70 4.86 4.63 5.10 4.94 5.21 5.15 5.38 5.11 0.41

From Tripathi (1992). CRI, crown root initiation; LT, late tillering; LJ, late jointing; F, Flowering; M, milk.

being 1.00 eighty days after sowing (Agarwal et al., 1977). These studies will go a long way in optimizing irrigation water in wheat. As of today, many of these findings are at the research level. Irrigation at critical growth stages of wheat is considered the easiest approach to be adopted by farmers. Five to six growth stages have been recognized as critical for irrigation, namely crown root initiation (CRI), late tillering (LT), late jointing (LJ), flowering (F), milk (M), and/or dough (D) (Dastane et al., 1974; Agarwal and Khanna, 1983). However, irrigation at a particular stage depends on the soil moisture retention capacity of the soil, depth of the water table, current soil moisture, and climatic conditions. For tall wheat grown in India before the introduction of dwarf wheat from Mexico, two to three irrigations of about 7.5 cm depth each between tillering and grain development were considered desirable (Asana et al., 1958; Prashar, 1967; Singh et al., 1984). For dwarf wheats introduced in India in the late 1960s and now covering most irrigated wheat in the country, CRI is considered the most important and about an 80% increase in yield due to irrigation over no irrigation is achieved by this single irrigation. In soils where the water table is 0.5 to 0.9 m deep and where some winter rains are received, this single irrigation is adequate (Table XXXIV). Thus when water is available only for a single irrigation it should be applied at CRI. If irrigation water is available for two irrigations, the recommended stages are

RICE–WHEAT CROPPING SYSTEMS

301

Table XXXV Irrigation Timing (Days after Sowing) Based on Depth of Water Table (WT) and Soil Texturea

Clay loam (WT 0.5–0.7 m)

Silty clay loam (WT 0.8–1.4 m)

Loam (WT 1.6–2.4 m)

Sandy loam (WT 2.5–3.5 m)

Particulars

Ab

Bc

Ab

Bc

Ab

Bc

Ab

Bc

First Second Third

26 NId NI

26 NI NI

24 NI NI

24 NI NI

23 85 NI

23 76 107

19 81 104

19 71 103

a

From Tripathi (1992). 1982–1983. c 1983–1984. d No irrigation. b

CRI and flowering. For three irrigations the recommended stages are CRI, LJ, and F. For four irrigations the recommended stages are CRI, LT, LJ, and F/M. Some data on this are presented in Table XXXIV. The practice of submergence in rice leads to a recharge of the water table and a judicious utilization of it can save considerable irrigation water in wheat (Chaudhari et al., 1974). Irrigation requirements of wheat depending on the depth of the water table in some soils are given in Table XXXV. These data show that as the water table depth increases from 0.5–0.9 to 2.5–3.5 m, the number of irrigations required in wheat increases from 1 to 3. While adequate and timely irrigation is a must for high yields of wheat in the IGP of India and several other countries, in the middle and lower reaches of the Yangtze river, i.e., in central and southern China where 500–700 mm of rainfall may be received during the wheat-growing season, resulting in periodic water logging, adequate drainage is a necessity (Lianzheng and Yixian, 1994). Mostly an open-ditch kind of drainage system is practiced. For this purpose, 0.4- to 0.6-m-deep ditches parallel to or transverse to the length of the rice–wheat fields are provided, which are connected to 0.8- to 1.0-m-deep drainage canals surrounding the field (Fig. 6). These ditches and canals serve as drainage and irrigation channels.

E. WEED MANAGEMENT Weeds are the main reason for drudgery to the farmers, especially the women who do the most of the hand weeding. In wheat, manual weeding makes up 50% of the total labor requirement. For this, more and more

302

R. PRASAD

Figure 6 Plan of drainage system for wheat after rice in Nanjing, China. From Lianzheng and Yixian (1994).

farmers are turning to herbicides. The loss in grain yield due to weeds is estimated at 15–20% in transplanted rice and at 15–30% in wheat (Saraswat and Bhan, 1992). In irrigated transplanted rice the dominant weed species in shallow depth standing water (<2.5 cm) are Echinochloa colonum, E. crusgalli, Paspalum spp., Cyperus iria, and Fimbristylis miliaceae, whereas with more than 2.5-cm standing water these are Sphanoclea zeylanica, Monochoria vagenalis, Ammania baccifera, and Hydrolea zevlanica. A large number of weed species for puddled transplanted rice have been listed by Pandey (1999) and these include (in addition to those already listed) Panicum repens, Dactyloctenium aegypticum, Leptochloa chinensis, Eclipta alba, Phyllanthus niruri, Ischaemum rugosum, Caesulia axilaris, and Commelina benghalensis, The dominant weed species in wheat in the RWCS belt in India are Phalaris minor, Avena ludoviciana, A. fatua, Lathyrus apacha, Melilotus indica, Vicia sativa, V. faba, V. hirsuta, Anagalis arvensis, Chenopodium album, C. murale, Convolvulus arvensis, Euphorbia helioscopia, Asphodelus tenuifolius, Medicago denticulatus, Lipidium sativa, Trigonella polycerata, Carthamus oxycantha, Argemone mexicana, Polygonum spp., Poa annua, Lolium temulentum, Cynodon dactylon, and Launia spp. (Chhokar et al., 2002). Of such a long list of weed species in wheat, Phalaris minor (canary grass) has been a major problem in continuous rice–wheat cropping over the years (Khera et al., 1995). The critical period of crop–weed competition for both transplanted rice and wheat is 30–45 days after transplanting/sowing (Mishra, 1997). In addition to manual weeding and the use of push-type rotary weeders in some areas, both cultural practices and herbicides are used to control weeds in rice and wheat.

RICE–WHEAT CROPPING SYSTEMS

1.

303

Cultural Practices

In rice, puddling not only controls weeds but also changes the weed flora. Grassy weeds dominate in dry seeded rice, whereas sedges and broad-leaved weeds dominate in puddle and standing water conditions. Gajri et al. (1999) reported that pre-puddling tillage is also beneficial in reducing weeds in rice. Cultivation of a green manure crop such as Sesbania before rice and ploughing it down before rice transplanting reduces weed infestation. In wheat the suggested cultural practices are cross sowing and a higher seed rate. To overcome the increasing menaces of P. minor, it is suggested to change the rice–wheat CS by replacing rice or wheat in some years. Some data regarding this are presented in Table XXXVI. Changing the cropping system is strongly recommended in view of the reports of development of biotypes of P. minor resistant to isoproturon (Yaduraju and Singh, 1997).

2.

Herbicides

For rice, a pre-emergence application of butachlor at 1.25–1.5 kg a.i. ha
1, thiobencarb at 1.5–2.0 kg a.i. ha
1, or anilophos 0.3 kg a.i. ha
1 showed good control of weeds throughout the rice-growing season (Chander and Pandey, 1996; Saraswat and Bhan 1992). Other herbicides found effective in controlling weeds in transplanted rice include nitrofen (Singh and Bhandari, 1985), oxadiazon (Brar et al., 1997), pendimethalin (Singh et al., 1990b), and propanil (Pandey, 1999). In wheat, a postemergence application of isoproturon, methabenthiazuron, metoxuron, chloroturon, or 2,4-D at 0.75 kg a.i. ha
1 is recommended. For pre-emergence, an application of oxyfluorfen at 0.30 kg a.i. ha
1 or pendimethalin at 1.0 kg a.i. ha
1 is recommended (Gill

Table XXXVI EVect of Crop Diversification on Population of P. minora

Crop rotation Rice–wheatb (continuous for 10 years) Rice–berseem (Trifolium alexandrinum), rice–wheat Rice–berseem, sorghum–wheat Rice–potato, rice–wheat Cotton–wheatb (for 4 years) Rice–berseem, rice–berseem, rice–wheat a b

Population of P. minor (Nos. m
2)

Wheat yield (tons ha
1)

2350 255 190 255 38 28

3.0 4.2 4.5 4.0 4.6 5.0

From Banga et al. (1997). Isoproturon applied to wheat at 1 kg a.i. ha
1 30–35 days after sowing.

304

R. PRASAD Table XXXVII Glyphosate and Isoproturon on the Density of P. minor and Wheat Yielda P. minor (plants m
2) 60 days after sowing

Treatment Glyphosate (kg a.i. ha
1) 0 0.6 1.25 Isoproturon (kg a.i. ha
1) 0 0.75 a

Grain yield of wheat (tons ha
1)

1996–1997

1997–1998

1996–1997

1997–1998

215 140 21

98 90 65

2.76 3.07 4.31

1.12 1.71 1.87

128 58

118 46

3.40 3.73

1.74 1.82

From Prasad and Yadav (2000).

et al., 1979; Mustafee 1991; Yadav et al., 1986). In areas where P. minor and broad-leaved weeds are a problem, an application of isoproturon at 1.0 kg a.i. along with 250 g a.i. 2,4-D at 30–35 days after sowing is recommended (Dixit and Bhan, 1997). When applied at the rate of 4 kg a.i. ha
1, the butachlor residue in soil was 0.21 mg kg
1 soil and at lower levels no residue was detected. An application of butachlor or thiobencarb to rice up to 4 kg a.i. ha
1 had no harmful residual effect on succeeding wheat. Similarly, residue studies on isoproturon at 1.0, 1.2, and 1.5 kg a.i. ha
1 revealed that 20–40% of the chemical was lost within 30 days after application (DAA), and after 100 DAA the soil contained only 18–20% of applied chemical and by 120 DAA it was degraded to nondetectable limits (Saraswat and Bhan, 1992). Thus there are no residual effects of herbicides applied to rice on succeeding wheat or vice versa (Dixit et al., 2000); therefore, recommendations for weed control for the two crops are to be made separately. The need for effective weed control in wheat after rice was felt more with the introduction of zero-till seeding. At Modipuram (Prasad and Yadav, 2000), the zero-till plot received one irrigation after rice harvest, and glyphosate at different rates was applied after the emergence of P. minor (two to three leaf stage). Wheat was then sown with Pantnagar zero-till seed drill after 1 day of glyphosate application. Isoproturon was applied at 1 kg a.i. ha
1 35 days after sowing. Glyphosate was very effective in controlling P. minor and at 1.25 kg a.i.ha
1 increased the grain yield of wheat by 55.9% over the control in 1996–1997 and by 95.4% in 1997–1998 (Table XXXVII). Isoproturon also controlled the P. minor population, but

RICE–WHEAT CROPPING SYSTEMS

305

the increase in yield over no isoproturon treatment was only 9.8% in 1996– 1997 and 4.5% in 1997–1998. Similarly, Singh and Prasad (2000) showed that glyphosate was quite effective in controlling grasses (including P. minor) as well as broad-leaved weeds in wheat fields sown by broadcast or drilled with a Pantnagar seed drill and increased the grain yield of wheat by 20 to 62%. Sulfosulfuron has also shown promise in controlling P. minor (Chhokar et al., 2001).

IV. GENETIC MANIPULATION As already pointed out, RWCS has gained popularity only after the introduction of HYV (high yielding varieties) of rice from IRRI, such as IR-8 and IR-36, and dwarf Mexican wheat from CIMMYT, such as Lerma Rojo and Sonora 64. Taking the lead from IRRI and the CIMMYT National Agricultural Research System (NARS) of the countries adopting RWCS have developed a large number of HYVs and hybrids of rice and wheat. Khush (1987) suggested that the rice varieties for double-cropping situations should have the following characteristics. i. High yielding ability ii. Early duration iii. Multiple resistance to diseases and pests iv. Good grain quality v. Tolerance for saline soil problems These points are discussed briefly.

A. HIGH YIELDING ABILITY Potential yield studies of rice and wheat by Agarwal et al. (1994a,b, 2000) using the ORYZAIN model for rice and the WTGROWS model for wheat showed that the potential for rice in the IGP varied from 7.2 to 11.5 tons ha
1, whereas that for wheat varied from 4.75 to 8.1 tons ha
1, with higher values from Punjab, Haryana, and Uttar Pradesh having a favorable environment and lower values for Bihar and West Bengal having a less favorable environment. In their simulation studies they included medium duration (130–140 days) rice varieties such as PR-106, Pusa 44, Pant Dhan 4, Sita, Saryu 52, and Saket 4. The wheat varieties included in the study were PBW 343, HD 2329, WH 542, WL 711, HUW 206, K 8804, HP 1731, and HD

306

R. PRASAD

2285. The potential yield may be defined as the upper limit that can be achieved by the current varieties in a no constraint environment. Thus even today there is a wide gap between the yield potential of available HYVs (6–7 tons ha
1 in the case of rice and 5–6 tons ha
1 in the case of wheat) and the theoretical potential based on environmental and physiological parameters. Thus the yield plateau in rice and wheat varieties has not yet been reached and there is scope for the development of higher yielding varieties. The suggested desirable characters are (Pandey et al., 1992): a. Increased biomass production—selection should be made for • Fast leaf area development • Low maintenance respiration • Adequate growth duration (110–120 days) b. Increased sink size—selection should be for • Large spikelet number per shoot • Larger grain size c. Increased harvest index The development of varieties by hybridization of selected donor parents and handling the segregating generation by different methods such as mass selection, bulk method, pedigree method, and single seed descent is known as conventional breeding. National Agricultural Research Systems (NARS) of different RWCS countries have developed a large number of varieties suiting to different situations. Some new attempts to break the yield barrier in wheat even today adopt these techniques. An example is a recent attempt in India on exploiting some local germplasms with large spikes with spikelet numbers ranging from 40 to 56 against the traditional 36–42 and 1000-grain weight varying from 45–52 as against 36 to 39 in the traditional varieties. The grain yield in these new cultivars was 667–707 g m
2 as opposed to 553–625 in the traditional high-yielding varieties such as PB343 and HD2329 (Singh et al., 2001). Hybrid rice occupies a large area in China (Jiaguo, 2000) and is responsible for the high productivity of RWCS in that country. The presence of hybrid vigor in rice has long been known (Jones, 1926). Because rice is a self-pollinated crop, in the absence of any cytoplasmic male sterile (CMS) and restorer lines the idea of hybrid rice did not appear feasible until Chinese rice breeders found a sterile wild rice plant in the Hunan province in the mid-1960s and developed CMS lines utilizing this wild cytoplasm (Singh, 1999). This cytoplasm was named wild abortive (WA). Utilizing this and IRRI varieties IR 24 and IR 26 as restorers, successful hybrids were developed in China that gave a 20–30% higher yield in comparison to local varieties (Lin and Yuan, 1980). The development of hybrid rice has opened up a new opportunity for developing rice hybrids for successful commercial cultivation (Swaminathan et al., 1972).

RICE–WHEAT CROPPING SYSTEMS

307

A large number of hybrids have been developed in India, including APHR2 and DRRH1 in Andhra Pradesh, MGR1, COR1, and ADTRH1 in Tamil Nadu, and KRH1 and KRH2 in Karnataka (Vidyachandra and Gubbiah, 1997), UPHR-17 in UP, CNRH3 in West Bengal, and NDRH-3 in Delhi (Singh, 1999); the general yield advantage claimed is 1 ton ha
1. However, rice hybrids have not yet made a dent in the RWCS belt in India, where farmers prefer to grow scented Basmati rices, which have a price premium. The amount of efficient chemical hybridization agents (CHA) has received interest in the possibility of marketing F1 hybrids of wheat varieties (Ganga Rao et al., 2000; Mahajan et al., 2000). In India, a research effort on hybrid wheat using CHA was initiated in 1995 (DWR 2000–2001) and 41 different molecules have been synthesized and used. Out of these, 2 have been found and tried in WH542 to further fine tune the synergistic dose. The first multiplication of a hybrid wheat trial was conducted during 2000–2001 at the Directorate of Wheat Research, Karnal; Punjab Agricultural University, Ludhiana; and CCS Haryana Agricultural University, Hisar with 19 entries and PBW 343 and HD 2687 as checks. Mutation breeding involving ionizing radiations (X rays, gamma rays, and neutrons) and chemical mutagens (ethyle-methane sulfonate and nitrosomethyl urea) is also being attempted. One of the significant varieties developed in earlier years was that of wheat by gamma radiation and was named Sharbati Sonora (Swaminathan, 1978) in which the dark-brown color of Sonora-64 was changed to sharbati (amber), which is more acceptable to Indians. In recent years biotechnological techniques have also been attempted in rice. Two such techniques are (1) double haploid technology (Khush and Virmani, 1985; Raina, 1989) and (2) the development of transgenics.

B. EARLY DURATION The short turn-around period between rice harvest and wheat sowing in the Indian subcontinent and between wheat harvest and rice transplanting in China is a serious problem. A number of studies have been made to find out the best varietal combination for the highest productivity of RWCS in different parts of India under AICRPCS; some data are shown in Table XXXVIII. In these studies, combinations of short, medium, and long duration rice varieties and wheat varieties recommended for early, normal, and late planting for different regions were compared. Results showed that a combination of medium duration rice variety and wheat variety recommended for late planting was the best for the IGP in the north. Short duration varieties of rice due to their shorter duration and

308

Table XXXVIII Grain Yield (tons ha
1) of Rice and Wheat Varieties of DiVerent Durations in RWCS at Some Research Centers in Indiaa Kanpur Variety duration Rice–Wheat b

a b

Faizabad

Jabalpur

Navsari

Rice

Wheat

Total

Rice

Wheat

Total

Rice

Wheat

Total

Rice

Wheat

Total

Rice

Wheat

Total

3.81 3.81 3.81 5.17 5.17 5.69 4.42 4.51 4.24

3.51 3.63 3.93 3.60 3.67 4.16 3.35 3.64 4.12

7.32 9.44 7.74 8.77 8.84 9.85 7.77 4.15 8.36

2.65 2.85 2.83 3.77 3.77 4.12 4.33 2.56 2.42

4.50 4.62 4.83 4.31 4.48 4.58 5.21 4.58 4.46

7.15 7.47 7.66 8.08 8.25 8.70 6.54 7.14 6.87

3.70 3.64 3.68 5.16 5.09 5.08 4.21 4.21 4.16

4.97 4.69 4.89 4.80 4.70 4.95 4.37 4.28 4.55

8.67 8.33 8.57 9.96 9.81 10.03 8.58 8.49 8.71

2.71 2.55 2.31 2.38 2.53 2.15 2.99 2.87 3.30

3.28 3.58 3.33 3.44 3.58 3.19 2.19 3.37 3.10

5.99 6.13 5.64 5.82 6.11 5.34 6.18 6.23 6.40

4.19 4.13 4.11 4.06 4.06 3.94 4.64 4.56 4.85

3.11 3.46 3.39 2.86 3.49 3.17 2.86 3.40 3.24

7.30 7.59 7.50 6.92 7.55 7.11 7.50 7.96 8.09

From Hegde (1992). Short, 95–100 days; medium, 115–130 days; and long, 135–140 days.

R. PRASAD

Short –early Short–normal Short–late Medium–early Medium–normal Medium–late Long–early Long–normal Long–late

Varanasi

RICE–WHEAT CROPPING SYSTEMS

309

long duration of rice varieties due to their maturing in cold winter days produced less rice yield and affected the productivity of RWCS. In central (Jabalpur) and western India (Navsari) the productivity of RWCS was the most when a combination of late duration rice variety and wheat variety recommended for late planting was used. Thus proper selection of rice and wheat varieties is a must for achieving high productivity of RWCS. Short duration rice varieties have a place when a catch crop (such as toria or potato) between rice and wheat is used. However, a longer duration wheat variety may be an advantage in some situations. For example, in their zero-till studies, Mehla et al. (2000) reported that PBW 343 and WH 542, which mature a week later than HD 2329, gave higher yields. They pointed out that PBW 343 and WH 542 have a different phenology than HD 2329 and HD 2009. Varieties PBW 343 and WH 542 have a large vegetative phase and a short grain-filling period and are less affected by delayed sowings.

C. MULTIPLE RESISTANCE TO DISEASES

AND

PESTS

Conventional rice-growing regions are humid to subhumid and there are a large number of diseases such as blast caused by Pyricularia oryzae, brown leaf spot caused by Helminthosporium oryzae, sheath blight caused by Rhizoctonia solani, bacterial blight caused by Xanthomonas oryzae, Tungro virus, and Grassy stunt virus to name a few (Ou, 1985; Ramakrishnan, 1971) that take a heavy toll on the rice crop worldwide. Similarly, there are a large number of insect pests that attack the rice crop. Some important ones are brown plant hopper (BPH) (Nilaparvata lugens), white-backed plant hopper (WBPH) (Sogatella furcifera), green leaf hopper (Nephotellix nigropictus), rice mealy bug (Ripersia oryzae), rice aphid (Hysteroneura setariae), rice leaf folder (Cnaphalocrosis medinalis), rice swarming caterpillar (Spodoptera mauritia), rice gall midge (Pachydiplosis oryzae), and rice gundhi bug (Leptocorisa varicornis) (Atwal, 1986). Development of multiple resistance for diseases and insect pests is thus the only solution to the problem and has been pursued for quite some time (Siddiq et al., 1998). Wheat is also affected by a number of diseases such as black (stem) rust (Puccinia graminis tritici), brown (leaf) rust (P. striiformis), loose smut (Ustilago nuda), leaf blight (Helminthosporium spp.), blast (Alternaria spp.), and Karnal bunt (Neovossia indica) (Joshi, 1978; Joshi and Palmer, 1973). Important insect pests are termites (Microtermes obesi and Odontotermes obesus), Gujhia weevils (Tanymecus indicus), armyworms (Pseudaletia separata), and mites (Petrobia latens) (Bhatia, 1978). Development of multiple disease and pest-resistance in genotypes is a major goal of a wheatbreeding program (DWR, 2001-02).

310

R. PRASAD

Because rice and wheat are grown in different crop seasons having different climate parameters (temperature, rainfall, humidity), the diseases and pests in the two crops are specific to rice or wheat, and a specific breeding program for multiple resistance to diseases and pests for the RWCS has not yet been launched. A beginning has, however, been made regarding nematodes, and nematode working group partners in India, Nepal, and Bangladesh have identified Meloidogyne graminicola, Tylenchorhynchus spp. (T. persicus), Pratylenchus spp. (P. thornei), and Hirschmanniella spp. (H. oryzae) as emerging important parasites in the RWCS (Sharma et al., 2000c). A detailed account of this subject is beyond the scope of this review.

D. GRAIN QUALITY Grain quality parameters and indicators in rice and wheat vary from place to place. For example, the Japanese prefer sticky glutenous rice, whereas in the RWCS belt in IGP in India and in the entire southwest Asia the preference is for long, slender, fluffy grains with aroma that elongate and remain separate on cooking; this kind of rice is best for biryani or pulao, a dish made out of rice, vegetables, and mutton or chicken. Similarly, in wheat, durums with hard grains are preferred for macaroni, whereas aestivums with soft grains are preferred for chapati (an unleavened asian bread) making, the most popular way in which wheat is consumed in India and other countries of Asia. In rice grain, dimensions have high heritability and are inherited quantitatively. Cross breeding of high-yielding rice varieties from IRRI, such as TN-1 and IR-8 with basmati-type rices, has led to the development of Pusa basmati-1 (the most popular variety in the northwest RWCS belt in India), where grain quality characters are merged with a high-yielding ability; 5 tons ha
1 against 1.5–2.0 tons ha
1 in the basmati type. Grain quality characters measured include length and length–width ratio in milled grain (Table XXXIX).

Table XXXIX Grain Quality Characters in Milled Ricea Designation Extra long Long Medium Short a

Length (mm)

Scale

Shape

7.50þ 6.61–7.50 5.51–6.60 <5.50

1 3 5 7

Slender Medium Bold Round

From Jennings et al. (1979).

Length–width ratio 3.0þ 2.1–3.0 1.1–2.0 <1.1

Scale 1 3 5 9

RICE–WHEAT CROPPING SYSTEMS

311

Aroma is another characteristic in rice that has a high market value. Aromatic cultivars are found in all the three ecotypes, namely indica, japonica, and javanica. Diacetyl-1 pyrroline is the major chemical compound responsible for aroma in rice (Buttery et al., 1983). Inheritance of aroma has been studied by several researchers. Sood and Siddiq (1978) and Berner and Hoff (1986) have observed it to be monogenic and recessive, whereas Dhulappanvar (1976) showed from complementary genes a segregation ratio of 175 nonaromatic:81 aromatic. Suzuki and Shimokawa (1990) observed a ratio of 13 nonaromatic and 3 aromatic, indicating one dose of gene for aroma and one dose of inhibitor gene. When the seeds of high-yielding dwarf wheats ‘Sonora 64’ and Lerma Rojo were imported from CIMMYT, Mexico, the major objection of the Indian consumer was their dark-brown colour and shriveled nature of grain. However, over a very short span of time Indian plant breeders were able to change the color of grains to “amber” and made them more plump by cross breeding the dwarf Mexican wheat with native Indian wheat. In the initial years, considerable attention was given to protein content and protein quality, particularly for high lysine content in wheat genotypes (Austin, 1978). However, because there is no premium for nutritional quality in wheat in India, this line of research has not received much attention. The current thrust in aestivums is on chapati and biscuit-making qualities. Grain quality is also receiving considerable attention in durums where lines are being checked for semolina recovery, ß-carotene content, and grain weight. The Directorate of Wheat Research, Karnal, India, is promoting DW 1001 for the northwest plains belt. This cultivar has 12.5% protein, 6.60 ß-carotene, and a test weight of 80 g. This genotype is being registered as a genetic stock for quality and for the presence of the r-gli-45 band (DWR, 2000–2001).

E. BREEDING

FOR

SPECIAL SOIL PROBLEMS

In addition to nutrient deficiencies, which have already been discussed, a large proportion (about 2.8 million ha) in the IGP of India is highly alkaline (pH > 8.5) and contains an excessive concentration of soluble salts, a high exchangeable sodium percentage (>15), and calcium carbonate. The Central Soil Salinity Research Institute, Karnal, India, and other agricultural universities/institutes have bred varieties suitable for saline–alkaline soils. Such varieties in rice are CST7-1, Lunishree, CSRIO, CSR 5, Panvel 1, Panvel 2, Vytilla, Vytilla 3, and Vytilla 4 (Singh, 1999), whereas those in wheat are KRL 19, Raj 3077, and Job 666.

312

R. PRASAD

V.

SUSTAINABILITY OF RICE–WHEAT CROPPING SYSTEMS

Currently there is a growing concern in sustainability of RWCS as the growth rates of rice and wheat yields are either stagnant or declining (Chand and Haque, 1998; Ladha et al., 2000; Paroda, 1996). An analysis of food insecurity indicators (land degradation and salinization, extent of forest cover, ground water depletion, and nature of crop rotation) in rural India carried out by the M.S. Swaminathan Research Foundation (MSSRF) with support from the World Food Program (WFP) indicates that the Punjab– Haryana region (a major part of the rice–wheat belt of India), which today serves as India’s food basket, may become very food insecure in another 20 years (Swaminathan, 2002). The major issues are (1) declining yields, (2) declining factor productivity, (3) declining soil health, (4) declining water availability, and (5) disease and pest problems. The available information is discussed.

A. DECLINING YIELDS Several rice–wheat studies at the experimental centers reported a yield decline, mainly for the rice crop (Duxbury et al., 2000; Nambiar, 1995; Regmi, 1994; Yadav, 1998). Duxbury et al. (2000) showed that 8 out of 11 long-term rice–wheat experiments, which had run for more than 8 years, showed a decline in rice yield over time, whereas only 3 centers showed a decline in wheat yield. Of the 7 long-term rice–wheat experiments examined by Ladha et al. (2000), none had a significant yield decline in wheat, but rice yields at Pantnagar in long-term fertility experiments in India declined at a rate of 2.3% year
1; the rice yield decline of 2.7% year
1 at Ludhiana was not statistically significant. An analysis of yield trends in 30 longterm rice experiments with rice–rice or rice–wheat conducted in seven countries (China, India, Indonesia, Bangladesh, Vietnam, the Philippines, and Malaysia) covering a wide variety of soil types by Dawe et al. (2000) suggested that yield declines are not very common, particularly at yield levels of 4–7 tons ha
1. Ladha et al. (2000) pointed out that some of the variation in yield, however, may be related to changes in variables other than those associated with sustainability. Process-based models have been tried for RWCS by combining various approaches (Timina et al., 1995, 1996, 1998). IBSNAT/ IFDC-based CERES-rice and CERES-wheat models and Wageningen-based ORYZA-1 and WHEAT-W models using data sets from Pantnagar, India, and Nashipur, Bangladesh, confirmed yield decline over time.

RICE–WHEAT CROPPING SYSTEMS

313

Table XL Grain Yield of Rice and Wheat in Five RWCS States of India and Their Annual Growth Ratea Grain yield (tons ha
1) State

1972

1975

1985

Punjab Haryana Uttar Pradesh Bihar West Bengal

1.95 1.71 0.79 0.90 1.22

2.30 1.79 0.86 0.87 1.20

3.11 2.58 1.35 1.06 1.53

Punjab Haryana Uttar Pradesh Bihar West Bengal

2.29 1.95 1.26 1.34 2.15

2.32 1.76 1.17 1.28 2.02

3.09 2.72 1.33 1.59 2.48

Annual growth rate (%) 1995

1972–1985

3.34 2.58 1.82 1.33 2.07

4.0 3.7 3.1
0.8 NSb 0.5

1985–1995

Rice 0.9 0.8 3.3 0.9 NS 3.3

Wheat

a b

3.99 3.66 2.42 2.07 2.32

2.6 2.7 3.7 0.5 0.0

2.3 3.3 6.4 2.8 0.8 NS

From Kumar et al. (1998). Not significant.

Research centers, however, provide good agronomic management and may not really reflect the happenings at the farmers level. Economists have therefore used state average yields over years as a parameter to check on the yield trend. Chaudhary and Harrington (1993) reported that expansion of the rice and wheat area in Haryana had halted and that the growth of rice productivity had slowed down. Analyzing yield data of rice and wheat from five states of India (Table XL), Kumar et al. (1998) observed that only in Punjab and Haryana there was a lower growth rate in rice yields, and only in Punjab was there a slight decrease in the growth rate of the wheat yield. It should be mentioned that the rice and wheat yields are the highest in Punjab and Haryana, and thus a declining growth rate during 1985–1995 could be due to some areas already reaching the yield potential of the varieties present before 1985. Results of yield data analysis from Bangladesh, Nepal, India (five states), and Pakistan for two time intervals, namely 1970–1985 and 1985–1998, are given in Table XLI. In Bangladesh there was a decline in the growth rate of yields of both rice and wheat. One factor affecting yields was the import of wheat from the United States, Australia, and Canada under the food-aid program, providing disincentives to wheat growers in Bangladesh (Ladha et al., 2000). In Nepal there was a higher growth rate from rice and wheat in the 1985–1998 period as compared to the 1970–1985 period. Regarding the

314

R. PRASAD

Table XLI Growth Rates (% year
1) of Rice and Wheat Yields in Three Countries and Five States of Indiaa Rice Country/states Bangladesh Nepal India West Bengal Bihar Uttar Pradesh Punjab Haryana Pakistan a b

Wheat 1985–1998b

1970–1985

1985–1998b

2.03
0.16

1.99 1.49

7.71 1.76

0.75 2.16

1.20 0.69 3.64 3.61 3.42 0.71

2.66 2.28 3.35 0.66 0.70 1.51

0.58 1.42 3.75 2.88 3.05 2.58

2.09 2.89 1.97 1.97 2.33 2.06

1970–1985

From Ladha et al. (2000). 1995–1997 data for the states of India.

five states of India where RWCS is practiced, the trend was the same as in the analysis by Kumar et al. (1998). Thus the yield data analysis for RWCS countries in south Asia indicates that yield decline is not universal. In regions where such declines are recorded, the causative factors could be other than sustainability and need to be found.

B. FACTOR PRODUCTIVITY Factor productivity is the ratio of output and input in a production system. When only one input factor, such as fertilizer N, is taken into consideration, it is termed partial factor productivity (PFP) and generally a subscript is given to indicate the input. For example, PFP for nitrogen is written as PFPn (Prasad et al., 2000). When an entire fertilizer is taken into consideration, it is written as PFPf. PFP is easy to determine on the basis of field experimental data. However, total factor productivity (TFP) takes into consideration all the factors that go into production, e.g., land, seed, labor (human and animal), machinery, fertilizer, manure, pesticides, irrigation, and interest on capital input, and is therefore a more complicated exercise. Yadav (1998) studied PFPn from field experimental data from four research centers in India, and data are shown in Table XLII. Over a period of 16 years there was a decline in the PFPn at three centers in the case of rice but only at 2 centers in the case of wheat. Mean values showed a decline of PFPn in rice but not in wheat. Apparently the main factor was a decline in

RICE–WHEAT CROPPING SYSTEMS

315

Table XLII Partial Factor Productivity (PFPn) (kg Grain kg
1 N) for Rice and Wheat in RWCS at Start and After 16 Years of RW Cropping at Four Research Centers in Indiaa Research center

Starting year

After 16 years

% change

Rice Pantnagar Faizabad Sabour Rewa Mean

42.4 38.6 35.8 39.7 39.1

25.6 41.0 14.5 18.3 24.8


39.6 6.2
59.5
53.9
36.7

45.1 29.3 14.5 19.8 27.2

160.7
14.3
41.5 25.3 32.5

Wheat Pantnagar Faizabad Sabour Rewa Mean a b

17.3 34.2 24.8 15.8 23.0

From Yadav (1998). N applied at 120 kg N ha
1 to rice and wheat with 35 kg P and 33 kg K ha
1.

Table XLIII Trends in Indices of Factor Productivity (TFP) of RWCS in Punjab, Haryana, and Uttar Pradesh States of Indiaa TFP (%)

Annual growth rate (%)

State

1976b

1985

1992

1976–1985

Punjab Haryana Uttar Pradesh

75.8 84.2 99.3

97.9 103.7 128.4

103.1 103.9 120.1

3.2 2.4 2.2

1985–1992 0.8
0.1 NSc
1.2

1976–1992 1.9 1.4 1.6

a

From Kumar et al. (1998). Average figures for the triennium ending the year given. c Not significant. b

yield over years at some of their centers. Although not familiar with these calculations, farmers in Punjab, Haryana, and the UP (western) state of India have, over the years, increased their N application rates to rice. Kumar et al. (1998) studied the trends in TFP of the RWCS in the three states of India (Punjab, Haryana, and UP) and their data are shown in Table XLIII. These data clearly show a lower annual growth rate in TFP during 1985–1992 as compared to that during 1976–1985; in Uttar Pradesh, the TFP growth rate during 1985–1992 was negative.

316

R. PRASAD

Factor productivity studies in India thus show that the sustainability of RWCS is certainly questionable, at least in some regions. Socioeconomic factors, including the price policy of the governments, could play a key role in making RWCS sustainable.

C. SOIL HEALTH 1.

Chemical Properties

Data from the AICRPCS on organic C, available P, and available K are reported in Table XLIV, whereas those on available Zn, Cu, Mn, and Fe are reported in Table XLV. After 7–10 cycles of RWCS there was a decline in organic C and available P from initial data at two out of three centers, whereas in the case of available K, there was a decrease from initial data at all three centers. However, when NPK fertilization was done, there was an increase in organic C from initial data at Ludhiana and Faizabad, but not at Kanpur. Application of part N through FYM or GM further increased organic C in the soil, with the increase being more with FYM than with GM. Balanced NPK fertilization increased available P at all the three centers, and the increase was more when FYM was applied because additional P was applied with FYM. The available K in soil, however, did not reach the initial level even with NPK fertilization with or without FYM or GM. This shows that depletion of K from soil was more than its application. Available Zn, Cu, Mn, and Fe were studied only at Faizabad and there was a decrease from initial data in the control as well as in the NPK fertilized plots with or without FYM or green manure. This again shows that a depletion of Zn, Cu, Mn, and Fe was more than its addition in RWCS. Several other studies in India (Brar et al., 1998; Meelu et al., 1994; Sharma and Prasad, 1999; Sharma et al., 1995, 2000; Yadav and Kumar, 1998) reported an increase in organic C due to the addition of organic residues. Thus RWCS leads to a decline in soil organic C unless adequate fertilization and organic residue addition are practiced. Bronson et al. (1998) suggested that the degradation of soil organic matter is faster in rice–wheat than in rice–rice soils. Ladha et al. (2000) pointed out that soil organic C depletion may not be the only effect of rice–wheat cropping over a long period of time, but that the nature of the chemical composition of organic matter may also change. In continuously flooded rice–rice systems, Olk et al. (1996) showed an increase in phenolic compounds in soil organic matter, and preliminary studies indicate that this may also be happening in RWCS soils. From a 3-year study at New Delhi, Prasad and Misra (2001) showed that an increase in soil organic C in a short span of time may not be noted but that the addition of fertilizer N and legume residues certainly increases

Organic C (%) Treatments Initial Control (no fertilizer) NPKþNPKb N (50% FYM)þNPK N (25% FYM)þNPK N (50% GM)þNPK N (25% GM)þNPK a b

Available K (1 N ammonium acetate extractable) K (kg ha
1)

Available P (0.5 M NaHCO3 extracted) P (kg ha
1)

Ludhiana

Kanpur

Faizabad

Ludhiana

Kanpur

Faizabad

Ludhiana

Kanpur

Faizabad

0.33 0.36 0.42 0.48 0.44 0.46 0.45

0.40 0.13 0.32 0.30 0.20 0.38 0.30

0.37 0.23 0.39 0.51 0.45 0.46 0.45

11.2 7.8 25.0 35.5 28.8 21.3 15.3

11.2 12.4 15.1 18.1 11.6 13.5 10.6

13.8 7.6 20.4 19.4 22.0 17.9 19.0

101 92 96 99 99 92 92

348 122 151 172 192 175 145

355 277 290 305 292 293 281

From Hegde (1998a,b). Treatment details as in Table XXVI.

RICE–WHEAT CROPPING SYSTEMS

Table XLIV EVect of Integrated Nutrient Management on Organic C, Available P, and Exchangeable K in Soil After 7–10 Cycles of RWCS at DiVerent Centers under AICRPCS in the IGP of Indiaa

317

318

R. PRASAD Table XLV EVect of Integrated Nutrient Management on Micronutrient Status of Soils at Faizabad (India) after 12 Cycles of RWCSa Available (DTPA extractable) micronutrients (mg kg
1 soil)

Treatment

Zn

Cu

Mn

Fe

Initial Control (no fertilizer) NPK þ NPKb N (50% FYM) þ NPK N (25% FYM) þ NPK N (50% GM)þNPK N (25% GM)þNPK

2.02 0.86 0.71 1.07 0.94 0.98 0.96

2.40 1.06 0.95 1.10 1.13 1.13 0.99

12.6 7.8 7.9 9.2 8.9 10.5 9.0

17.0 10.8 12.0 14.0 13.1 19.2 17.5

a

From Yadav and Kumar (1998).

available (alkaline permanganate oxidizable) N in soils, which was more after the wheat harvest than after the rice harvest. Thus addition of fertilizer N and legume residues definitely increases the labile-N pool [the term suggested by Dudal and Deckers (1993)]. Glendining and Powlson (1995) also reported that application of 144 kg N ha
1 to winter wheat at Broadbalk for 122 years caused only a 20% increase in Kjeldahl soil-N but a 60% increase in mineralizable N. Thus while it is generally accepted that continuous RWCS over a long period of time without the addition of organic manures does bring about a decline in soil fertility; detailed information on different plant nutrients is yet not available. Data on temporal variations in soil organic C and available plant nutrients in RWCS are not at all available, but are necessary because of the widely different microenvironments in which rice and wheat are grown.

2.

Physical Properties

A number of studies have been done on the effect of puddling practiced while preparing land for rice transplanting on physical properties of soil. Destruction of large size aggregates and dispersion of particles by puddling result in their rearrangement, leading to a massive plastic mud of reduced porosity and higher moisture retention, which is the goal of puddling (Sharma and De Datta, 1986). Puddling of silty clay loam at Pantnagar converted 61.7% of the water-stable aggregates of a diameter greater than 0.5 mm into smaller fractions and

RICE–WHEAT CROPPING SYSTEMS

319

Table XLVI EVect of Crop Residues in Bulk Density (g cm
3) of Soils in RWCSa 1996–1997 Treatment Legume residue Fallow Sesbania Mungbean LSD (P¼0.05) Wheat residue No residue Residue LSD (P¼0.05) a

1997–1998

1998–1999

After wheat

After rice

After wheat

After rice

After wheat

1.58 1.50 1.49 0.09

1.54 1.47 1.46 0.05

1.61 1.47 1.43 0.10

1.51 1.46 1.44 0.05

1.49 1.40 1.41 0.02

1.53 1.52 NS

1.45 1.52 NS

1.56 1.46 0.09

1.48 1.46 NS

1.47 1.39 0.01

From Sharma et al. (2000).

reduced the mean weight diameter from 1.7 to 0.69 mm (Tripathi, 1992). Puddling in a sandy loam soil decreased larger aggregates of 20–50 mm from 30 to 17% and of larger than 50 mm from 20 to 2% (Gupta and Woodhead, 1989). However, a puddle soil becomes harder on drying and again forms larger clods with large size aggregates. Gupta and Woodhead (1989) reported that ploughing three times on puddled rice fields after rice harvest increased the aggregates of 50 mm from 3 to 43%. Thus there is a desirable change of aggregate sizes from the puddled rice soil when wheat is grown. The destruction in soil structure as judged by aggregate size distribution by puddling does not affect wheat production adversely. Singh et al. (2001) reported higher yields of wheat in puddled rice plots as compared to direct seeded rice plots. Puddling of soil for rice cultivation increases the bulk density of soil in RWCS. The bulk density of 15- to 22- and 25- to 32-cm layers of a silty clay loam soil planted to wheat after rice increased from 1.40 to 1.50 and 1.48 to 1.58 g cm
3, respectively (Tripathi, 1992). This increase in bulk density in the rice–wheat sequence can be reduced by the incorporation of crop residues (Table XLVI). The effect of a 9-year rice–wheat–cowpea sequence in long-term experiments at Pantnagar (Tripathi, 1992) showed that the hydraulic conductivity of a 0- to 10-cm layer in rice plots with 100% NPK was 0.230 cm h
1, whereas that in a 25- to 32-cm layer was 0.012 cm h
1; the corresponding values for a fallow plot were 0.86 and 0.04 cm h
1. Similarly, Sur et al. (1981) reported that the hydraulic conductivity of a 5.25-cm layer of a sandy loam soil under RWCS was only 33–55% of that under maize–wheat. Thus the aforementioned and several other studies on soil physical properties have centered around the effects of puddling in rice fields. What is

320

R. PRASAD

needed is information on the temporal changes in soil physical properties in RWCS on different soils and to relate these to the sustainability of RWCS.

D.

PEST PROBLEMS

Rice–wheat cropping regions fortunately have fewer disease and pest problems than rice–rice systems, with the latter being practiced in higher humidity and temperature conditions conducive to the growth of disease and pest-causing organisms. Nevertheless, there are disease and pest problems in the RWCS belt, some of which have emerged due to the introduction of rice in this nontraditional rice belt in India. Some pests, such as canary grass (Phalaris minor), have emerged in wheat in northern India only after the introduction of rice (Saraswat and Bhan, 1992). A survey conducted by Savary et al. (1997) in the RWCS belt in Uttar Pradesh, India, showed that mean yield losses due to weeds could be 13%, whereas the yield loss due to insect damage (dead hearts) could be 9.2%. Brown spot and sheath blight emerged as important diseases and losses could be 9.6 and 6.4%, respectively (Table XLVII). Of course, in the case of serious attack by any pest, the damage could be 27.3 to 69.5%.

Table XLVII Yield Loss Estimates Due to DiVerent Pests in RWCS in Uttar Pradesh, Indiaa Mean yield loss

Injury Weed infestation above the rice crop canopy Weed infestation below the rice crop canopy Dead hearts (Scirpophaga incertulas) Brown spot (Helminthosporium oryzae) Sheath blight (Rhizoctonia solani) Sheath rot (H. sigmoideum) Neck blast (Pyricularia oryzae) All injuries a

From Savary et al. (1997).

Maximum yield loss

Absolute (tons ha
1)

Relative (%)

Absolute (tons ha
1)

Relative (%)

0.30  0.06

6.2  1.2

2.77

55.2

0.34  0.07

6.8  1.4

2.54

52.6

0.46  0.07

9.2  1.4

2.63

52.4

0.33  0.03

6.6  0.6

2.43

48.4

0.32  0.06

6.4  1.2

3.49

69.5

0.02  0.02 0.06  0.02

0.4  0.4 1.2  0.4

0.12 1.37

2.4 27.3

1.43  0.27

28.5  5.4

—

—

RICE–WHEAT CROPPING SYSTEMS

321

VI. SOCIOECONOMIC AND POLICY FACTORS Studies on the effect of socioeconomic and policy factors on the productivity of RWCS have not been studied. One measure of socioeconomic factors is the amount of fertilizer consumed in a region. In the IGP RWCS belt, all the districts of Punjab and 80% of the districts in Haryana consumed more than 100 kg NPK ha
1 year
1 as compared to UP and Bihar, where the figures was only 49 and 40%, respectively (Table XLVIII). This showed up in the productivity of RWCS, as shown by the state average yields of rice and wheat in these states. The identification of constraints, which include fewer per capita income and less availability of credit, will go a long way in augmenting RWCS yields. As regarding government policies, the procurement of rice and wheat at preannounced prices by the government of India for the public distribution system (PDS) has been the major driving force in augmenting the production of RWCS, which in some states has spread at the cost of other crops, particularly grain legumes (Kumar et al., 1998), which were generally grown on marginal land. Similarly, import of a large quantity of wheat (1.0–1.5 million tons year
1) as food aid from wheat surplus donor countries such as the United States, Australia, and Canada in Bangladesh could have depressed the prices of wheat in the local market and provided disincentives to the growth of wheat production (Ladha et al., 2000). Information generated on costs and returns shows that boro rice has higher financial and economic returns than wheat; this encouraged rice–rice over rice–wheat cropping systems.

Table XLVIII Number of Districts Consuming More Than 100 kg NPK ha
1 year
1 and Average Yields of Rice and Wheat During 1998–1999 in RWCS States in IGP in Indiaa Districts consuming more than 100 kg NPK ha
1 year
1

State

Number

% of total districts in the state

Rice

Wheat

17 16 41 22

100 89 49 40

3.15 2.24 1.96 1.30

4.33 3.92 2.41 1.99

Punjab Haryana Uttar Pradesh Bihar a

State average yield (tons ha
1)

From FAI (1999–2000).

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Thus government policies and socioeconomic factors have an impact on RWCS. More detailed studies on these aspects are suggested.

VII. FUTURE RESEARCH NEEDS 1. Detailed information is needed on the decline in yield/partial factor productivity (PEP)/total factor productivity (TFP) to demarcate the regions where it is happening and diagnostic surveys are required in these areas to find out the causes for such declines so that ameliorative measures can be taken. 2. Information on the temporal availability of plant nutrients in RWCS is urgently required, especially for the plant nutrients that undergo oxidation–reduction cycles such as nitrogen, sulfur, iron, and manganese. Oxidation–reduction of Fe and Mn also affects the availability of P. No information is available on the effect of seasonal variation of submergence to well-drained conditions on the availability of these and other plant nutrients. 3. Studies are needed on the rate of decomposition of cereal and legume residues under rice- and wheat-growing conditions and how they affect the development of soil organic matter (SOM). The changes that SOM undergoes under such divergent physicochemical and environmental conditions are hardly understood. The highest yields of rice and wheat being obtained on soils with the lowest SOM in India is a myth that needs to be solved. Is it total agronomic management or something related to soil management? These studies will permit a better integrated nutrient management policy. 4. Development of better soil and plant analysis techniques are needed for a better prediction of the soil nutrient-supplying capacity of soils to permit more reliable fertilizer recommendations. 5. Simpler and better methods are needed for scheduling irrigation in rice and wheat to save each drop of water. Strategies need to be developed to prevent farmers from overirrigating rice. 6. Plant breeding research using modern techniques and biotechnology is needed to develop (a) high-yielding short-duration rice and wheat varieties suitable for different agroecological conditions, (b) high-yielding wheat varieties for late planting in RWCS, and (c) high-yielding rice and wheat varieties suitable for saline/sodic soils. 7. There is a need to develop disease and pest forecasting models for different agroecological zones where RWCS is practiced. 8. A rice transplanting machine suitable for transplanting conventionally grown rice seedlings of 25–50 days of age is still a dream. Growing small

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seedlings on plastic or PVC mats for which machines are available is not the general practice in RWCS. 9. Better machines for direct seeding of wheat after rice need to be developed. 10. Detailed socioeconomic studies are needed to determine the factors limiting the productivity of RWCS and to advise the government(s) on policies that will assure good economic returns to farmers practicing RWCS.

ACKNOWLEDGMENTS Thanks are due to Dr. P. R. Hobbs, cofacilitator of the Rice–wheat Consortium for the IGP, New Delhi and Regional Representative, CIMMYT, South Asia Regional Office, P.O. Box 5186, Lazimpat, Kathmandu, Nepal, for his kind help in getting the Chinese literature and to Dr. R. B. Singh, former director of the Indian Agricultural Research Institute, for encouragement in the author’s research in RWCS. Thanks are also due to Dr. R. K. Gupta, Facilitator, RWCIGP, CIMMYT-India, New Delhi for discussion on permission to include figures from RWCIGP Publications.

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Shoji, S., and Kanno, H. (1994). Use of polyolefin coated fertilizers for increasing fertilizer efficiency and reducing nitrate leaching and nitrous oxide emissions. Fertil. Res. 37, 147–152. Shukla, L. M. (2001). Evaluation of soil test methods for sulphur in soils of India. Fertil. News 46(10), 55–58. Siddiq, E. A., Reddy, A. P. K., Krishnaiah, K., and Bentur, J. S. (1998). Genetic improvement in rice for resistance to diseases and insects. In “IPS System in Agriculture” (R. K. Upadhyay, K. G. Mukerjee, and R. L. Rajak, Eds.), Vol. 3, pp. 75–104. Aditya Books Pvt. Ltd., New Delhi. Singh, A., and Kharub, A. S. (2001). Performance of zero tillage in wheat, evidences from participatory research. Fertil. Market. News 32(11), 1–5. Singh, A., and Pal, R. A. (1973). A note on the response of transplanted rice to nitrogen and water management practices. Indian J. Agron. 18, 376–377. Singh, B., Singh, Y., and Sekhon, G. S. (1995). Fertilizer-N use efficiency and nitrate pollution of ground water in developing countries. J. Contamin. Hydrol. 20, 167–184. Singh, B. P., Sakal, R., and Singh, A. P. (1985). Response of lentil varieties to iron application on highly calcareous soils of Bihar. Indian J. Agric. Sci. 55, 56–68. Singh, D. (1945). Water requirement of crops. In “Proc. Crops and Soils Wing, Board of Agriculture and Animal Husbandry, India”, pp. 166–168. Singh, D., Krishnan, K. S., and Bapat, S. R. (1976). Economics of fertilizer use based on experiments conducted in cultivators’ fields. Fertil. News 21(3), 8–14. Singh, K. K., and Gangwar, K. S. (2000). Comparative evaluation of conventional sowing and zero-till and strip till drilling of wheat after rice harvest: Extended summaries. In “Int. Conf. Managing National Resources for Sustainable Agricultural Production in the 21st Century. Feb. 14–18, 2000, New Delhi” (J. S. P. Yadav, et al., Eds.), Vol. 3, pp. 879–880. Indian Society of Soil Science, New Delhi. Singh, M., and Singh, K. S. (1979). Response of wheat to zinc fertilization at different levels of phosphorus in a loamy sand soil. J. Indian Soc. Soil Sci. 27, 314–320. Singh, M., and Singh, R. K. (1978). Potash application for profitable crop production. In “Proc. Symp. Potassium in Soils, Crops and Fertilizers”, pp. 260–272. Potash Research Institute of India, Gurgaon. Singh, M., and Singh, R. K. (1979). Split application of potassium in rice to maximize its utilization. Indian J. Agron. 24, 193–198. Singh, M., and Singh, T. A. (1986). Leaching losses of nitrogen from urea as affected by application of neem cake. J. Indian Soc. Soil Sci. 34, 766–773. Singh, M. V. (1992). Micronutrient management in rice–wheat system. In “Rice–Wheat Cropping System” (R. K. Pandey, B. S. Dwivedi, and A. K. Sharma, Eds.), pp. 114–133. Project Directorate for Cropping Systems Research, Modipuram. Singh, M. V. (2001). Importance of sulphur in balanced fertilizer use in India. Fertil. News 46(10), 13–35. Singh, O. P., and Bhandari, R. K. (1985). Relative efficiency of different herbicides in transplanted rice. Indian J. Weed Sci. 17, 47–49. Singh, P. K. (1997). Biofertilizers for flooded rice ecosystem. In “Fertilizers, Organic Manures, Recyclable Wastes and Biofertilizers” (H. L. S. Tandon, Ed.), pp. 113–131. FDCO, New Delhi. Singh, P. K., and Bisoyi, R. N. (1989). Blue green algae in rice fields. Phykos 28, 181–195. Singh, R., and Singh, J. (1997). Irrigation planning in wheat under deep water table conditions. Agric. Water Manage. 33, 19–29. Singh, R. B., and Paroda, R. S. (1994). Sustainability and productivity of rice–wheat system in the Asia-Pacific: Research and Technology Development Issues. In “Sustainability of Rice– Wheat Production Systems in Asia” (R. S. Paroda, T. Woodhead, and R. B. Singh, Eds.), pp. 1–35. ROAP, FAO, Bangkok.

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Swarup, A., and Yaduvanshi, N. P. S. (1998). Long-term nutrient management strategies for sustaining rice–wheat system in alkali soils of the Indo-Gangetic Plains. In “Long-Term Soil Fertility Management through Integrated Plant Nutrient Supply” (A. Swarup, D. Damodar Reddy, and R. N. Prasad, Eds.), pp. 260–271. Indian Institute of Soil Science, Bhopal. Takkar, P. N., and Nayyar, V. K. (1979). Iron deficiency affects rice yields in Punjab. Indian Fmg. 29, 9–12. Takkar, P. N., and Nayyar, V. K. (1981). Preliminary field observation of manganese deficiency in wheat and berseem. Fertil. News 26(2), 22–23. Takkar, P. N., and Randhawa, N. S. (1978). Micronutrient in agriculture. Fertil. News 23(8), 3–26. Takkar, P. N., Chhiba, I. M., and Mehta, S. K. (1989). Twenty years of coordinated research on micronutrients in soils and plants. Indian Institute of Soil Science, Bhopal. Bull. 1, 149–184. Takkar, P. N., Singh, M. V., and Ganeshamurthy, A. N. (1997). A critical review of plant nutrient supply needs, efficiency and policy issues for Indian Agriculture for the year 2000: Micronutrients and trace elements. In “Plant Nutrient Needs, Supply, Efficiency and Policy Issues: 2000–2025” (J. S. Kanwar and J. C. Katyal, Eds.), pp. 238–264. National Academy of Agricultural Sciences, New Delhi. Tandon, H. L. S. (1980). Soil fertility and fertilizer use research on wheat in India. Fertil. News 25(10), 45–78. Tandon, H. L. S. (1987). “Phosphorus Research and Agricultural Production in India”. FDCO, New Delhi. Tandon, H. L. S. (1991). “Sulphur Research and Agricultural Production in India”, 2nd Edn., FDCO, New Delhi. Tandon, H. L. S., and Sekhon, G. S. (1988). “Potassium Research and Agricultural Production in India”. Fertilizer Development and Consultation Organization, New Delhi. ten Have, H. (1971). Methods of nitrogen application for transplanted rice. Fertil. News 16(9), 23–25. Thakur, B. S., and Kushwaha, J. S. (1970). Effect of rates and time of application of nitrogen use on paddy. Fertil. News 15, 32–34. Timrina, J., Singh, U., Singh, Y., and Lansigan, F. P. (1995). Addressing sustainability of rice– wheat system: Testing and application of CERES and SUCROS models. In “Fragile Lives in Fragile Ecosystems”, pp. 633–656. IRRI, Manila, Philippines. Timsina, J., Singh, U., and Singh, Y. (1996). Addressing sustainability of rice–wheat system: analysis of long-term experimentation and simulation. In “Proc. 2nd Fertil. Symp. on Systems Approaches for Agric. Development (SAAD)” (M. J. Kropff, P. S. Teng, P. K. Agarwal, J. Bourma, B. A. M. Bouman, J. W. Jones, and H. H. van Laar, Eds.), pp. 383–397. Kluwer, Philippines. Timsina, J., Singh, U., Badrauddin, M., and Meisner, C. (1998). Cultivar, nitrogen and moisture effects on rice–wheat sequence: Experimentation and simulation. Agron. J. 90, 119–130. Tiwari, K. N. (1985). Changes in potassium status of alluvial soils under intensive cropping. Fertil. News 30(9), 17–24. Tiwari, K. N. (1995). Sulfur research and agricultural production in U.P. Sulphur Agric. 14, 29–34. Tiwari, K. N., Dwivedi, B. S., and Subba Rao, A. (1992). Potassium management in rice–wheat system. In “Rice–Wheat Cropping Systems” (R. K. Pandey, B. S. Dwivedi, and A. K. Sharma, Eds.), pp. 93–114. Project Directorate for Cropping Systems Research, Modipuram, Meerut, India. Tiwari, K. N., and Nigam, V. (1984). The change in potassium status of benchmark soils under intensive cropping. Potash Rev. Sub. 16 Suite 96(2), 1–7.

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INTERACTIONS OF NITROGEN WITH OTHER NUTRIENTS AND WATER: EFFECT ON CROP YIELD AND QUALITY, NUTRIENT USE EFFICIENCY, CARBON SEQUESTRATION, AND ENVIRONMENTAL POLLUTION Milkha S. Aulakh1 and Sukhdev S. Malhi2 1

Department of Soils, Punjab Agricultural University, Ludhiana 141004, Punjab, India 2 Agriculture and Agri-Food Canada, Research Farm, Melfort, Saskatchewan, Canada S0E 1A0

I. Introduction II. Nitrogen
Phosphorus Interaction A. Cereals and Millets B . Legumes C . Nonlegume Oilseeds and Other Crops III. Nitrogen
Potassium Interaction A. Cereals B . Vegetables, Horticultural, and Plantation Crops IV. Nitrogen
Sulfur Interaction A. Oilseeds and Pulses B . Cereals, Millets, Vegetables, and Plantation Crops C . Grasses, Perennials, and Other Forage Crops V. Nitrogen
Calcium and Nitrogen
Magnicium Interactions VI. Nitrogen
Micronutrients Interactions A. Zinc B . Copper and Manganese C . Iron, Boron, Cobalt, and Molybdenum VII. Nitrogen
Water Interaction A. Dryland Environments B . Fully and Partially Irrigated Environments VIII. Effects on Carbon Storage and Sequestration in Soil A. Temperate Regions B . Tropical and Subtropical Regions IX. Nitrogen Losses and Trends of Fertilizer Consumption A. Nitrogen Losses and Use EYciency 341 Advances in Agronomy, Volume 86 Copyright 2005, Elsevier Inc. All rights reserved. 0065-2113/05 $35.00

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M. S. AULAKH AND S. S. MALHI B . Global Consumption of N, P, and K Fertilizers C . P=N and K=N Ratios of Crops and Applied Fertilizers X. Conclusions and Future Research Needs Acknowledgments References

I. INTRODUCTION Among the 17 essential plant nutrients, nitrogen (N) plays the most important role in augmenting agricultural production, potential environmental risks, and impacting human and animal health. Nitrogen, which is required in the greatest quantity of all mineral nutrients absorbed by plant roots, is an essential component of protein. While the beneficial effects of fertilizer N application on crop production are well documented, concern on the long-term role of fertilizer N in maintaining soil productivity, crop quality (including elemental composition and balance, protein, oil, fatty acids), and environmental safety is being expressed more frequently in recent years. The long-term strategy of N use in agriculture likely will involve increased reliance on fertilizer N, biological N fixation (BNF) by leguminous crops, and wastes (including farm, urban, and industrial wastes) and their efficient management. Recovery of applied N by crops in field experiments has been found commonly ranging from 25 to 34% for rice (Oryza sativa L.) and 40 to 60% for other crops, with the global average value of about 50% (Mosier, 2002). Unutilized N may remain in the soil in various forms and=or get lost through several processes, including NH3 volatilization, denitrification, and nitrate leaching, which have been discussed in detail in several reviews (Aulakh et al., 1992; Carpenter et al., 1998; Goulding, 2004; Guillard et al., 1995; Malhi et al., 1991, 2002a; Singh et al., 1995; Zhang et al., 1995). For enhancing applied nitrogen use efficiency by crops (NUE), several management techniques have been developed for different soils, crops, seasons, and regions. Examples of these include (a) integrated and judicious use of chemical fertilizers and organic manures, (b) synchronizing N supply with crop need by split applications during crop growth, (c) reducing loss of applied N with nest or band placement or large urea granules in soil, and (d) use of slow-release fertilizers and nitrification inhibitors (Aulakh, 1994; Keeney, 1982; Malhi and Nyborg, 1985, 1988; Nyborg and Malhi, 1992). The amounts of different nutrients absorbed by a crop from soil may vary 10,000-fold, from 200 kg of N ha1 to less than 20 g of Mo ha1, and yet rarely do these nutrients work in isolation. As agriculture becomes more

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intensive, the extent and severity of nutrient deficiencies and the practical significance of nutrient interactions increase. Interactions among nutrients occur when the supply of one nutrient affects the absorption, distribution, or function of another nutrient (Robson and Pitman, 1983). In crop production, nutrient interactions assume added significance by affecting crop productivity and returns from investments made by farmers in fertilizers. Interaction between two or more nutrients can be positive (synergistic), negative (antagonistic), or even absent (reflected as additive effect). When the effect of one factor (e.g., nutrient) is influenced by the effect of another factor, the two factors are said to interact. When the crop yield reaches an early plateau, it may be due to the limiting supplies of another nutrient illustrating the operation of Liebig’s “law of the minimum” (Cooke and Gething, 1978). When that nutrient is supplied, yield will continue to increase until another factor becomes limiting. When solar radiation, temperature, and soil water availability are nonlimiting, plant nutrient requirements will be higher; for which Wallace (1990) proposed the “law of the maximum” in contrast to the “law of minimum.” The law of maximum states that when the need is fully satisfied for every factor involved in the process, the rate of the process can be at its maximum potential, which is greater than the sum of its parts because of a sequentially additive interaction (Wallace, 1990). Production of field crops has already entered into the stage of multiple nutrient deficiencies management. For instance, in south Asia, a farmer in the rice–wheat belt needs to manage four to six nutrients to safeguard and sustain an annual harvest of 10 tons grain ha1, whereas a tea planter in India targeting for a yield of over 4.5 tons tea ha1 must worry about seven to eight nutrients. Thus, when the combined effect of two factors is more than their additive effects, the interaction is positive. When their combined effect is less than their additive effects, the interaction is negative. Therefore, just because factor A þ factor B plot produces a higher yield than either A-treated or B-treated plot does not mean that there is a positive A
B interaction. A brief review on the interaction effects of N with P, K, S, and Cu has been given previously (Aulakh and Malhi, 2004). As N function in plant growth and nutrition is closely connected to C, the C=N ratio controls N availability and potentially affects interactions through the processes of organic residue decomposition and soil organic matter (SOM) formation in soil, biomass production (photosynthesis minus respiration) in plant, and energy flow in and through all levels of the ecosystem (Wilkinson et al., 2000). An understanding of the nature of different interactions, factors affecting them, and the ways and means of managing these for useful purposes is vital for developing, advocating, and practicing a balanced and efficient crop nutrient management strategy. Identification and exploitation of positive interactions hold the key for increasing returns in terms of crop yield, produce quality, and nutrient use efficiency from applied N.

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Knowledge of the negative interactions is equally valuable because the test of “precision crop nutrition” lies in the ability to minimize the losses from antagonistic effects. Nutrient interactions have a role to play in determining the course and outcome of two major issues of interest in fertilizer management, namely balanced fertilizer input and efficient fertilizer use. This article reviews and analyzes the available information to (a) examine the impact of interactions of applied N with other nutrients, nutrient cycles, and water on NUE, (b) consider the influence of NUE on the utilization of other nutrients and water, and on C sequestration and storage in soil, (c) compute relative consumption of major fertilizer nutrients (N, P, and K) for assessing their over, under, or balanced use in different regions, and (d) pinpoint the gaps in knowledge for future research needs to optimize the use of N and other nutrients for sustainable crop production and reducing environmental risks. The fertilizer use efficiency indicators considered in this chapter are (i) agronomic efficiency calculated as production of grain over control per unit of applied fertilizer nutrient (Novoa and Loomis, 1981), (ii) improvement in nutrient uptake as measured by apparent recovery efficiency, namely uptake of fertilizer nutrient by plant over control per unit of applied fertilizer nutrient (Dilz, 1988), and (iii) improvement in crop quality parameters such as protein, oil, and fatty acid content. Similarly, water use efficiency (WUE) computed as (i) crop yield m2 field area m1 water used and (ii) crop yield m2 field area m1 water transpiration or evapotranspiration is considered here. As the impacts can be on a local, regional, or global scale, examples have been cited for different levels. Emphasis is placed on the cereal crops that occupy more than 50% of the harvested area of crop land and contribute more than 75% to annual world food production, but other field crops, such as oilseeds and pulses, vegetables, horticultural crops, and perennials are also discussed. Keeping the practical utility of research in view, a preference has been accorded to results obtained from field experiments over greenhouse and pot culture studies.

II. NITROGEN
PHOSPHORUS INTERACTION The majority of soils around the globe are deficient in available N and are either low or medium in available P. These two nutrients account for a major share of the current annual fertilizer consumption (IFA, 2003). The N
P interaction can, therefore, be termed the single most important nutrient interaction of practical significance. This interaction is often synergistic, occasionally additive, and, in rare cases, may be antagonistic. The synergistic interactions between N and P help explain the effect, when applied as a banding beneath seed, on root growth and proliferation.

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A. CEREALS

AND

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MILLETS

It has frequently been shown that in a highly P-deficient soil, application of N alone has little impact on crop yields but N þ P application can dramatically increase the response to applied fertilizer (Table I). The contribution of a synergistic interaction between N and P in cereals can be 13 to 89% of the yield response to N þ P and 14 to 96% of NUE, depending on the yield potentials, level of soil fertility, and nutrient application rates. If a soil is more deficient in P than N, then application of N alone could cause a severe reduction in grain yield, as was observed by Sinha et al. (1973) in wheat (Triticum aestivum L.). Since application of P alone raised wheat grain yield by 682 kg ha1, the interaction impact was 79% on grain yield (Table I). Several studies show that crop yield and nutrient recovery are higher in N þ P-treated plots than with N or P alone. For example, the composite response based on a large number of on-farm fertilizer trials in India showed

Table I Influence of N
P Interaction on Nitrogen Use Efficiency (NUE) in Different Field Crops NUE (kg grain kg1 N)a With only N

With N þ P

20.3 (120)d 0 (120) 22.4 (120) 8.8 (120) 32.4 (75)

25.9 11.0 25.5 11.5 40.0

8.7 (60)

Field peas Cauliflower

10.3 (40) 66.7e (120)

Bromegrass IWG f Timothy

23.6 (50) 17.4 (50) 21.8 (50)

Crop Wheat Rice Corn

Sunflower

Interaction impact (%) Grain yieldb

NUEc

Reference

26 79 13 27 89

28 11 times 14 96 23

13.8

46

59

15.0 102e

30 23

46 355

30.8 24.2 30.0

5.4 34.4 2.7

Dwivedi et al. (2003) Sinha et al. (1973) Dwivedi et al. (2003) Singh (1991) Satyanaryana et al. (1978a) Aulakh and Pasricha (1996) Pasricha et al. (1987) Balyan and Dhankar (1978) Loeppky et al. (1999) Loeppky et al. (1999) Loeppky et al. (1999)

30.5 39.1 37.6

a [(Yield with applied fertilizer N, kg grain ha1) – (yield in control without N and P, kg grain ha1)]=[amount of applied fertilizer N, kg N ha1]. b Interaction impact on grain yield (%) ¼ 100 [(yield response to N þ P, kg grain ha1) – (sum of yield response to N and P individually, kg grain ha1)]=[sum of yield response to N and P individually, kg grain ha1]. c Interaction impact on NUE (%) ¼ 100 [(NUE with N þ P, kg grain kg1) – (NUE with N only, kg grain kg1 N)]=[NUE with N only, kg grain kg1 N]. d Value in parentheses indicates rate of applied fertilizer N (kg N ha1). e Fresh heads. f Intermediate wheat grass.

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that at an application rate of 120 kg nutrients ha1, the response rates and thus fertilizer use efficiency were higher with 90 kg N þ 30 kg P2O5 ha1 than with 120 kg N ha1 (Sharma and Tandon, 1992). Grain response per kilogram nutrient was higher by 11% when 120 kg nutrients ha1 were distributed as 90 kg N þ 30 kg P2O5 as compared to only 120 kg N ha1. In Vietnam, application of P reduced lodging and percentage of unfilled rice (Oryza sativa L.) grains caused by the use of N alone, remarkably improving yield response as well as NUE (Vo et al., 1995). Also, P has been found to be a key factor for preventing the decline in rice yield and NUE during a wet season of Vietnam (Tan et al., 1995). This 8-year study of Tan et al. (1995) further showed an increase of PUE from 100 kg grain kg1 P in the absence of fertilizer N to 160 kg grain kg1 P with the addition of N. Data on N
P interactions in sorghum [Sorghum bicolor (L.) Moench] at four locations in India having different soils are shown in Fig. 1. In all four

Figure 1 N
P interaction in sorghum at four locations in India. (A) Mishra and Singh (1978); (B) Roy and Wright (1973); (C) Venkateswarlu and Rao (1978); (D) Nagre and Bathkal (1979). Adapted from Sharma and Tandon (1992).

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347

soils, the yield response to N increased when P was applied. Steeper slopes of the N þ P curves as compared to N only also indicated higher fertilizer use efficiency. Graphs A and B represent sites that are moderately well supplied with available P, whereas soils of C and D are deficient in available P and show that the differences between N and N þ P treatments are bigger than in A and B. Thus, in soils that are severely deficient in P, application of N alone will produce only a small increase in yield, much below the potential. In certain situations even the contribution of the N
P interaction can be large enough to overshadow the effects of N or P alone. When N is provided as an ammonium or ammonium-producing fertilizer, the acidifying effect could enhance N concentrations in plants (Malhi et al., 1988) and P solubility in soil (Prasad and Power, 1997), thus providing a positive interaction. However, in those few soils that test high in available N and P, the addition of single or both element fertilizers may not provide a grain yield advantage, regardless of the type of crop, fertilizer, or its placement method (Buah et al., 2000). For nonirrigated crops, better root growth as a result of adequate P supply could enable the plants to absorb water from deeper soil layers during droughty spells, thereby increasing NUE as well. Results with rainfed sorghum in red soils show that the value of interaction effect was 10% of the total response at application rates of 20 kg N þ, 20 kg P2O5 ha1, 20% at a dose of 40 kg N þ, 20 kg P2O5 ha1, and 36% when each N and P were added at 40 kg ha1 (Venkateswarlu and Rao, 1978). Payne et al. (1995) reported alleviation of water stress with P fertilization resulting in improved NUE. In early season corn (Zea mays L.) under dryland conditions of Bhagalpur, India, the N
P interaction was synergistic at all levels of N and P applied, but a maximum interaction advantage was derived at 120 kg N þ 60 kg P2O5 ha1 (Table I). At this level, the interaction effect contributed 27% of the total yield response to N and P and 96% to the improvement in NUE. Thus, the greater the investment in nutrients, the more the need for balance. The N
P interaction may show different effects on the partitioning of grain and stover of various crops. For instance, the N
P interaction had a greater effect on grain than on the stover yield of sorghum (Roy and Wright, 1973) and corn (Tripathi, 1978), but the trend was opposite in millet (Maliwal et al., 1989). Also, a much more pronounced interaction effect has been reported for P uptake than for N uptake by crops (Table II). The possible reason why application of N alone resulted in a large increase in P uptake was the mining of soil P. As a result of this mutual benefit, improvements in efficiency and recovery of both N and P by crops could be considerable (Table III). Interyear variation may also be observed in the interaction pattern; the N
P effects were additive in year 1 and highly synergistic in year 2 (Satyanarayana et al., 1978b). Where a farmer cannot afford to apply both N and P in optimum amounts, it is better to apply smaller or suboptimal amounts of both N and P instead of a large amount of N alone. For instance, corn grown in red soils produced 370 kg more grain with the

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Table II The N
P Interaction Effect on N and P Uptake by Sorghum Over Control Without N and Pa Treatment

N uptake over control

Effect of N alone Effect of P alone Effect of N þ P Interaction effect Interaction contribution a

58.5 kg N 29.2 kg N 95.3 kg N 7.6 kg N 8%

P uptake over control

1

6.9 kg P ha1 4.8 kg P ha1 6.8 kg P ha1 5.1 kg P ha1 30%

ha ha1 ha1 ha1

Adapted from Roy and Wright (1973).

Table III Three-Year Averaged N and P Use Efficiency and Recovery in Rice and Wheat in Rice –Wheat Cropping Systema Treatment Rice 120 kg N ha1 26 kg P ha1 120 kg N þ 26 kg P ha1 Wheat 120 kg N ha1 26 kg P ha1 120 kg N þ 26 kg P ha1

NUEb (kg grain kg1 N)

ANRc (%)

PUEd (kg grain kg1 P)

APRd (%)

22.4 — 25.5

39.5 — 41.8

— 6.1 20.5

— 9.0 22.4

20.3 — 25.9

45.5 — 55.3

— 7.6 34.5

— 10.0 27.0

a

Modified from Dwivedi et al. (2003). NUE, as explained in footnote to Table I. c ANR (% recovery of applied fertilizer N) ¼ 100 [(uptake of N with applied fertilizer N, kg N ha1) – (uptake of N without applied fertilizer N, kg N ha1)]=[amount of applied fertilizer N, kg N ha1]. d PUE and APR, as described for NUE and ANR using P instead of N. b

application of 75 kg N þ 30 kg P2O5 ha1 as compared to 100 kg N ha1 without P (Satyanarayana et al., 1978a).

B. LEGUMES The interaction of N
P in legumes, including grain legumes such as pulses and oilseed legumes such as peanut (Arachis hypogae L.) and soybean [Glycine max (L.) Merrill], is more complex than in the case of nonlegumes. Its potential value declines once the biological N-fixing system has become functional 3–4 weeks after seeding and thus only a small starter dose of N is often sufficient. However, the interaction can also be modified by the amount of N fixed, which in turn will depend on the population and efficiency of

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native Rhizobium and whether inoculation was carried out. A weak or a negative N
P interaction probably reflects satisfactory biological N fixation (BNF) activity. This, in no way, would contradict the need for starter N along with P for legumes because grain yield increases per kilogram of applied N (20–40 kg N ha1) are substantial and very attractive in view of the high market value of pulses. For example, a 5-year field experiment revealed that fieldpea (Pisum sativum L.) grown without fertilizer N produced a grain yield of about 2100 kg ha1, whereas the application of 20, 40, and 60 kg N ha1 increased its yield to 2440, 2590, and 2710 kg ha1 (Bahl et al., 1995). In case the level of BNF is low, legumes may exhibit a large response to fertilizer N, as revealed by a study of Saimbhi and Grewal (1986); the yield of peas (P. sativum L.) increased by 2300 kg ha1 or 70% with applied N, and the N
P interaction was synergistic accounting for 14% of the N þ P response. In comparison, the interaction effect was less pronounced (9%) for pods plant1 and absent for plant height. A positive N
P interaction may indicate poor BNF and greater dependence on fertilizer N. In a field study conducted for 5 years in a loamy sand soil in the Punjab state of India, the interaction effect of N and P on yield and protein content of field peas was significant (Pasricha et al., 1987). For harnessing the optimum yield potential of field peas, the most effective combination was 40 kg N þ 30 kg P2O5 ha1, where the interaction impact was 23%. In French beans (Phasealus vulgaris L.), while N alone was beneficial only up to 30 kg N ha1, the crop made effective use of 60 kg N ha1 when this was combined with 100 kg P2O5 ha1 (Srinivas and Rao, 1984). Compared to the control plots, French bean yields could be increased more than five times by a judicious N þ P combination, of which 59% was due to the interaction effect. Phosphate application can create more favorable conditions for BNF. While application of N alone, particularly beyond 20 kg N ha1, reduced nitrogenase activity, a balance between N and P application maintained nitrogenase activity at a high level in field peas (Fig. 2). Thus, the

Figure 2 Effect of fertilizer N
P interaction on the nitrogenase activity of root nodules of field peas at flowering stage. Drawn with data from Pasricha et al. (1987).

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N
P interaction is favorable for BNF in legumes enhancing N fixation, as was also observed by Muller et al. (1993) and Amanuel et al. (2000) in faba beans (Vicia faba). Nodulation at the late flowering stage and consequent total N yield of faba beans were significantly improved by applied P in all the three sites studied in Ethiopia (Amanuel et al., 2000).

C. NONLEGUME OILSEEDS

AND

OTHER CROPS

Sunflower (Helianthus annus L.) yield was increased by both N and P, but the interaction between the two was not synergistic (Fig. 3). However, as discussed earlier, instead of adding only N, application of both N and P at lower rates gave better returns and use efficiency. At 40 kg nutrients ha1, the combination of 10 kg N þ 30 kg P2O5 gave 14% more yield than the application of 40 kg N ha1. In a field study in Argentina, Zubillaga et al. (2002) estimated that the maximum yield of sunflower can be increased by 20% with application of N and P together as compared to N alone. They suggested that P fertilization provided a more efficient use of fertilizer N by producing greater and consistent effects on crop performance most likely due to early root development. Available data on other oilseeds revealed that the interaction was positive in sesame (Sesamum indicum L.) (Daulay and Singh, 1982), absent in linseed=flax (Linum usitatissimum L.) (Thosar, 1986), and negative in castor (Venkateswarlu and Rao, 1978). Application of P to rapeseed (Brassica napus L.) and mustard (Brassica juncea L.) was more effective when combined with N, and as a general guideline, N and P2O5 are

Figure 3 Influence of N
P interaction on sunflower yield. Drawn with data from Yadav et al. (1974).

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recommended in a 2:1 ratio (Bhan, 1981; Pasricha et al., 1991). Application of excessive N could increase aphid infestation in rapeseed, whereas a combined application of N þ P suppresses its attack and increases the yield up to 300% (Khattak et al., 1996). In the case of cotton (Gossypium hirsutum L.), the interaction between N and P was synergistic and accounted for 15% of the response to N þ P in year 1 and 29% in year 2 (Raghuvanshi et al., 1989). The yield of cotton seed was increased by 132% with N, by 69% with P, and by 282% with N þ P. In experiments with cauliflower, marketable yield increased from 11 tons ha1 without fertilizer to 23 tons ha1 with N þ P (Balyan and Dhankar, 1978). No amount of N could increase the yield beyond 19 tons ha1, and the performance of 80 kg N þ 50 kg P2O5 was superior to 120 kg N ha1. Out of the total yield response to 120 kg N þ 50 kg P2O5, 70% could be credited to N, 7% to P, and 23% to their positive interaction. In field experiments on the forage seed response to N and P fertilization in northeastern Saskatchewan, Canada, Loeppky et al. (1999) reported substantial increases in NUE of perennial grasses with combined application of N and P as compared to N alone. For example, the NUE (kg seed kg1 N) values for N alone and N þ P together, respectively, were 23.6 and 30.8 for bromegrass, 17.4 and 24.2 for intermediate wheatgrass, and 21.8 and 30.0 for timothy (Table I). In this study, the relative increases in grass seed yield from applied N and P were related to available N and P in soil. Seasonal variations have also been observed in the impact of N
P interaction within the same crop species. For example, a direct response of pumpkin (Cucurbita pepo L.) to N and P was quite similar both in the summer and in the rainy season, but the N
P interaction was highly synergistic in summer season and absent or slightly negative in the rainy season (Sharma and Shukla, 1979). One possible reason for this differential response could be the fact that the highest yield was about 34 tons ha1 in the summer season and only 14 tons ha1 in the rainy season. This illustrates that nutrient interactions assume added practical importance at high-yield potentials and not at low levels of productivity. Interyear variations in N
P interaction effects were also observed in canola (Brassica napus L.) under western Canadian conditions, which were attributed to temperature and precipitation effects (Nuttall et al., 1992). Temperature increased the N and P concentration in plants primarily by enhancing their uptake rate per unit of root rather than increasing the rate of root growth (Ercoli et al., 1996). In the subtropics, a high temperature (26–45  C) coupled with a high moisture status in the rainy season compared to 3–20  C in winter enhances the solubility of native soil P and residual fertilizer P, leading to differential crop responses and fertilizer use efficiency in summer and winter seasons (Aulakh et al., 2003). Cultivars of the same crop species may also exhibit potentially useful specificities for fertilizer N-form preference (NO3 or

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NH4þ) and tolerance of NH4þ toxicity (Zornoza and Gonzalez, 1998), resistance to diseases (Slater et al., 1991), and root morphological plasticity=capability to alter the root:shoot ratio (Johnson and Biondini, 2001) that modify nutrient interactions. In summary, the positive N
P interaction is responsible for a sizable yield gain due to N þ P application and can account for a substantial share of yield response to N þ P application, leading to improvements in both NUE and PUE. The magnitude of this interaction is modified by soil type, level of available soil P, applied N and P rates, crop type, and climatic conditions. The overall trend of N
P interaction studies brings out the point that crop responses to N level off earlier, whereas those to N þ P enable the crop to produce higher yields. The P-deficient crop not only produces lower yield, its stand is often nonuniform and maturity is delayed. Thus, in situations where a farmer cannot afford to apply both N and P in optimum amounts, it is better to apply lower amounts of both N and P instead of a large amount of N alone.

III.

NITROGEN
POTASSIUM INTERACTION A. CEREALS

In addition to N, potassium (K) is the major plant nutrient absorbed and removed by crops in the largest amounts among all essential nutrients. Rice, for example, a heavy remover of K from the soil, could absorb up to 30 kg K2O t1 grain produced, which is about 50% higher than N uptake; rice– wheat and rice–rice cropping systems could remove 236 and 211 kg K2O as compared to 235 and 139 kg N ha1, respectively (Singh, 1992). After N
P interactions, N
K interactions are the second most important interaction in crop production. The significance of N
K interaction and its optimum management is increasing due to increasing cropping intensity, higher crop yield, and greater depletion of soil K. Crops with a high requirement of K such as corn and rice often show strong N
K interactions (Loue, 1978; Singh, 1992). Plants can absorb N either in cationic (NH4þ) or in anionic (NO3) form. There is a unique possibility of anion–cation as well as cation–cation interactions with Kþ. Most of the findings have illustrated that Kþ does not compete with NH4þ for uptake, rather it increases NH4þ assimilation in the plants and avoids possible NH4þ toxicity. Mengel et al. (1976) concluded that it was unlikely that Kþ competes with NH4þ for selective binding sites in the adsorption process. For example, when corn was grown in soil in a greenhouse at the lower rate of K application, leaf lesions occurred and the

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tissue yield of plants having lesions was lower with NH4þ-N as compared to plants receiving NO3-N (Dibb and Welch, 1976). At the higher rate of K application, leaf lesions disappeared and the yield of NH4þ-fed plants exceeded the yield of NO3-fed plants. However, there are also some reports to the contrary that NH4þ-N reduces the K concentration in plants (Faizy, 1979). While the response of rice to P is more or less uniformly high at all levels of applied N, the response to K increases with the amount of N þ P applied (Umar et al., 1986). Increasing application rates from 40 kg N þ 40 kg P2O5 ha1 to 120 kg N þ 140 kg P2O5 ha1 increased rice yield by 300 and 960 kg ha1 compared with 0 and 20 kg K2O ha1, respectively. Interestingly, application of NPK in the ratio of 120–40–0 and 40–40–20 produced similar rice yields, demonstrating higher nutrient use efficiency in the NPK treatment than with NP alone. Potassium increased rice yield by 250 kg ha1 (7%) when N and P2O5 were applied at 40 kg ha1 each, but by 910 kg ha1 (24%) at 120 kg N þ 40 kg P2O5 ha1. Increasing N and P application rates without K application is often not a sound proposition and does not increase crop yield beyond a certain level; also, higher levels of K are more effective at higher levels of N and P. Singh and Singh (1978) observed that a dose of 100 kg K2O ha1 was 2.5 times more effective in raising rice yield at 200 kg N as compared to 100 kg N ha1. Another study demonstrated that a weakly synergistic or additive N
P interaction could become highly synergistic when an adequate supply of K is ensured (Fig. 4).

Figure 4 Influence of N
P
K interaction on rice yield. Drawn with data from Chandrakar et al. (1978).

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Tropical soils such as Ultisols and Oxisols are poor in available P and K, and field experiments on such soils provide interesting data on N
K and N
P
K interactions. Data from Brazil show a positive N
K interaction in rice where a good response to K was obtained only when adequate N (90 kg ha1) was applied (PPI, 1988). Also, the response to N increased as the level of K was increased; the highest rice yield as well as NUE and K use efficiency (KUE) were obtained when both N and K were applied (Fig. 5). Thus, it is clear that the N
P
K interaction is helpful in increasing rice yields, provided N and P are applied at sufficient levels. Seasonal effects on the impacts of N
K interaction are evident from rice grown during the wet and dry seasons. In a study of Mondal et al. (1982), the N
K interaction was more prevalent in the dry season than in the wet season, possibly because of a more favorable growing condition, higher yield, and yield potential with resultant greater nutrient demand by the crop in the dry season. In the wet season, the best rice yield was 4.3 tons ha1 regardless of the level of N used, but 5.0 tons ha1 rice (16% higher) could be harvested with an application of 120 N þ 80 kg K2O ha1. In the dry season, the highest rice yield with 40 kg K2O ha1 was 6 tons ha1 but 7.4 tons ha1 (23% more) rice could be harvested by the application of K with high levels of N. However, in some situations the interyear variations in N
P
K interactions may be difficult to explain. For instance, in the southern United States, a maximum corn yield was obtained when 168 kg N and 29 kg P ha1 were applied in conjunction with 209 kg K ha1 in year 1 but without K application in year 2 (Obreza and Rhoads, 1988).

Figure 5 Effects of N and K fertilization on rice in Brazil. Adapted from PPI (1988).

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Long-term experiments with the wheat crop reveal that the response of crops to K increases with time. For example, KUE in wheat was in the range of 1.7–4.2 kg grain kg1 K2O during the 1969–1971 period, which increased to 5.6–10.6 kg grain kg1 K2O during 1977–1982 (Bhargava et al., 1985). When crop rotations are tested repeatedly on the same site, the situation changes; the available soil K status decreases with time due to the continuous removal by crops and changes the crop response to applied K. The response of wheat was observed only up to 30 kg K2O ha1 in a soil that tested medium in available K status (Sharma et al., 1978) and up to 90 kg K2O ha1 in low K-tested soil (Azad et al., 1993). A rice–wheat double-crop system occupies 26 million ha in south and east Asia and accounts for nearly one-fourth of the region’s food grain production. The alluvial soils of Indo-Gangatic plains under this rice–wheat system often show small responses to applied K, as these soils release sufficient amounts of available K from the K-rich illitic clay minerals (Aulakh and Bahl, 2001). However, in northeastern areas where high rainfall results in greater leaching losses of K, the supply of K from the soil minerals is low, the K content of groundwater is low, and significant responses of rice–wheat system to applied K could be obtained (Table IV). Macleod (1969) demonstrated that the optimum supply of K was important in promoting barley (Hordeum vulgare L.) grain and straw yield, as deficient K levels had a depressing effect, especially when N was supplied at high rates. Johnson and Reetz (1995) observed that adequate soil test K levels are critical to realize the full benefit of applied N for harnessing optimum corn yields and NUE in Ohio. Also, more of the applied N was left in the soil after harvest, resulting in lower profitability and creating a greater potential for a negative environmental impact.

Table IV Response of Rice and Wheat (kg Grain ha1) to Applied N, P, and K in Two Northeastern Districts of Punjab, Indiaa Gurdaspur district

Amritsar district

Treatment

Rice

Wheat

Rice

Wheat

Control 120 kg N ha1 120 kg N þ 60 kg P2O5 ha1 120 kg N þ 60 kg P2O5 þ 30 kg K2O ha1 LSD0.05 Number of experiments

3490 5120 5500 5830 160 97

1550 2430 3090 3440 40 122

3950 5660 6280 6500 150 89

2010 3600 4160 4300 120 84

a

Modified from Singh and Bhandari (1995).

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B. VEGETABLES, HORTICULTURAL,

AND

PLANTATION CROPS

Because K application is commonly practiced in several nonfood crops, the N
K and N
P
K interactions are also of equal importance in maximizing fertilizer use efficiency in vegetable, horticultural, and plantation crops. Hamilton and Bernier (1975) showed that celery, carrot, and lettuce could not do well without the balanced use of N, P, and K. Earlier reviews have shown tremendous effects of N
K interaction in vegetable crops such as potato (Solanum tuberosum L.) and sugarbeet (Beta vulgaris L.) (Loue, 1978), onion (Allium cepa L.), chillies (Capsicum frutescens L.), and tomatoes (Lycopersicon escuulentum Mill.) (Singh, 1992); root crops such as sweet potato, cassava, and colocasia; and fruits such as banana, guava, pineapple, apple, and several other crops (Gething, 1986; Singh, 1992). In a long-term study with cassava (Manihot esculenta Cranz) in North Vietnam, Nguyen et al. (2002) observed that use of N, P2O5, and K2O in a 2:1:2 ratio is most appropriate for obtaining optimum yields and tissue nutrient concentrations. In fact, the first report of a N
K interaction was on a sugarbeet crop at Rothamsted (Hall, 1905). The crop was grown for 3 years in succession on plots annually receiving various combinations of fertilizers. The effect of applying K in addition to P was absent without N and increased by 14% at 96 kg N ha1 and 36% at 206 kg N ha1. This spectacular effect of K came about partly through improvement in the yield of roots and partly because K counteracted the tendency for the sugar content to be lowered by high rates of N application. Such a phenomenon symbolizes the yield-forming role of interdependent processes such as N-driven photosynthesis and K-driven assimilation and translocation of the photosynthates. The gradient (slope) of the response to increasing N could be the same with or without K, or application of K may raise the plateau along with a change in the gradient of a crop response to N (Cooke and Gething, 1978). A third type of N
K relationship is possible where the responses to the two nutrients may show additive effects only. Fertilization with P can help enhance the ability of plants to respond to N and K fertilization, resulting in higher yields and nutrient use efficiencies (Wilkinson et al., 2000). Application of K increases the N content in grain and total N uptake by the crops, leading to improved NUE (Sangakkara, 1995). However, P and K concentrations of plants could also increase with increasing rates of applied N (Davenport and Provost, 1994; Pare et al., 1993). Kemp (1971, 1983) found that the effect of increasing N bioavailability on tissue K concentrations depends on K bioavailability in the root zone. Under conditions of high K availability, increasing the N supply increases K concentration and uptake, as K concentrations decrease at high N rates because of growth dilution or another limiting factor coming into play. The role of K nutrition is well established in providing the plant the strength for facing adverse

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climatic conditions such as low temperature (Carrekar et al., 1977) and drought (Sangakkara, 1995), regulating the activity of several enzymes (e.g., protopectinase, polygalacturonase, polygalacturonate transeliminase, pectin transeliminase, and cellulases) leading to the control of diseases such as sheath rot of rice plants (Jayasekhar and Prasad, 1986), and in building up resistance in plants toward the invading pathogens. Such functions of increasing crop resistance to diseases and pests have been reviewed extensively (Perrenound, 1977). In a 76-year experiment with sweet potato in Japan, Osaki et al. (1995) observed excessive accumulation of N compounds, disorder of phloem transport, and restricted P absorption under K-deficient conditions. Similarly, Bussi et al. (2003) observed that while high N fertilization aggravated fruit pitburn ailment in an apricot orchard, K fertilization along with N minimized pitburn incidence. Thus, increasing K levels in the fertilizer prescription, especially with N, can be utilized advantageously for protecting the crops from several health hazards and, consequently, for enhancing nutrient use efficiency. Compared to control plots of sugarcane (Saccharum officinarum), application of 400 kg N ha1 increased cane yield by 56.8 tons ha1 (133%), application of 350 kg K2O ha1 increased it by 4.7 tons ha1 (11%), but combined N þ K application raised it by 70.3 tons ha1 (165%) (Singh, 1992). The synergistic interaction of N þ K raised cane yield by 12.4 tons ha1 over 200 kg N and by 13.6 tons ha1 over 400 kg N ha1, accounting for about 20% of the response. In another study involving varying levels of NPK, the yield of sugarcane improved only when increasing the application of N and P was supplemented with K application (Singh, 1992). Genotypical differences have been observed in different crops for spatial soil K exploitation. On the same soil, where crops such as sugarbeet, which have a poor root system, show a decrease in sugar yield on N þ P without K plots from the beginning, cereals such as wheat, which have a dense and deep root system, may show a response to fertilizer K after several years (Orlovius, 1995). In summary, N
K and N
P
K interactions are essentially a factor at high levels of crop productivity; strongly positive and profitable interactions are possible in crops having a high K requirement, and a significant N
K interaction can be expected wherever higher doses of N are used to increase crop production. Its benefits are (i) a reduction in the dose of N, resulting in an economy of N to the farmers, (ii) help in enabling the plant to resist the damage from pests and diseases, (iii) a favorable influence on crop quality and biochemical constituents of the produce, and (iv) minimizing the amount of fertilizer N left in the soil after harvest and reducing the potential for a negative environmental impact. Because K performs functions in plant metabolism, promoting photosynthesis, conserving moisture, and speeding up the transport of products of metabolism between different parts of the

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plant, harnessing the N
K and N
P
K interactions could increase the efficiency of applied N.

IV. NITROGEN
SULFUR INTERACTION Sulfur (S) is the fourth major fertilizer nutrient along with N, P, and K. The deficiency of S has been reported with increasing frequency in the past several years all over the world (Scherer, 2001). Among different regions, Asia represents the region with the highest S fertilizer requirement. Continuous mining of S from soils has led to widespread S deficiency and a negative soil budget. There are numerous areas of the world where soils contain insufficient amounts of plant-available S to sustain the optimum growth of crops. Deficiencies of S occur most commonly on soils having low organic matter and coarse texture and those located in humid climates. The increasing S deficiencies in soils are attributable to several factors, such as (i) adoption of high-yielding crop cultivars, which demand a high fertility level and result in greater exploitation of soil reserve nutrients and removal of much larger quantities of nutrients in the harvested crop, (ii) increased cropping intensity—intensive cultivation to grow more crops annually on the same land, (iii) a drastic decline in incidental additions of S through fertilizers, atmospheric SO2, especially around industrial cities, pesticides, and other agrochemicals, and (iv) the increased use of high-analysis S-free fertilizers (Aulakh, 2003). In the 1950s, S-containing fertilizers were common sources of N and P, as most of N as ammonium sulfate and P as single superphosphate (SSP) were applied. The consumption of fertilizer N and P has increased tremendously since then; however, the use of N and P fertilizer compounds that contain little or no S has also increased. Both N and S are vital constituents of plant proteins and are closely associated in their synthesis and play a key role in plant oil production. Application of N in the absence of sufficient S leads to the production of amino acids that are not incorporated into proteins, and plants synthesize the required amounts of S-containing amino acids when S is applied (Finlayson et al., 1970). When soils are deficient in available S, growth of all crops is drastically reduced. While N directly affects the photosynthesis efficiency of plants, S affects the photosynthesis efficiency indirectly by improving the NUE of the plants, as was evident from the relationship between N content and photosynthetic rate in the leaves of “with S”- and “without S”-treated Brassica plants (Ahmad and Abdin, 2000). In “without S” plants, photosynthesis was linearly related to leaf N content only up to 1.5 g m2, whereas the relationship was linear even beyond 1.5 g m2 in S-treated plants. Rapeseed plants grown on S-limiting soils suppress the

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development of reproductive growth and could even lead to poor seed set (Nuttall et al., 1987; Nyborg et al., 1974) or pod abortion (Fismes et al., 2000). Glucosinolates that are produced in Brassica species as a result of optimum S fertilization have been effective in inhibiting soil-borne fungal pathogens, such as “take-all infection” in wheat crop (Angus et al., 1994).

A. OILSEEDS

AND

PULSES

Oilseeds and legumes are more sensitive to S deficiency and more responsive to S fertilization than cereals and grasses due to their higher requirements for S. The quantity of S removed from soil for optimum crop yields is highest for oilseeds, followed by pulses and the lowest for cereals (Aulakh and Chhibba, 1992). In a 3-year field study conducted on S-deficient Gray Luvisol soils in Saskatchewan, Canada, application of N fertilizer alone reduced yield, oil content, and S uptake of canola seed (Malhi and Gill, 2002a). Compared to N alone, N þ S fertilization increased yield, oil content, and S uptake of seed (Table V). On six sites, average NUE was 2.0 kg seed kg1 N when N fertilizer was applied alone and it increased more than five times (10.2 kg seed kg1 N) when both N and S fertilizers were applied. The decline in seed yield with only N fertilization on S-deficient soils could be considered due to excessive accumulation of toxic levels of N metabolites in the plant, and adversely affecting several plant attributes as mentioned earlier. McGrath and Zhao (1996) observed an increase of 42–267% in the seed yield of Brassica napus with the application of 40 kg S ha1 along with 180 and 230 kg N ha1. Without S application, the seed yield declined drastically due to S deficiency when the N fertilization rate increased from 180 to 230 kg N ha1. Such severe negative impacts when N alone was applied to S-deficient soils on seed yield, oil content and production, protein content, and NUE in rapeseed and mustard crops have also been observed in several other studies from Canada (Janzen and Bettany, 1984; Nuttall et al., 1987), India (Abdin et al., 2003; Aulakh et al., 1980, Table V Effect of Fertilizer N (120 kg N1) with or without S (30 kg S ha1) Application on Seed Yield Oil Content, and S Uptake of Canola in Northeastern Saskatchewan, Canada (average of Six Site Years)a Parameter

No fertilizer

Seed yield (kg ha1) Oil content (%) S uptake (kg S ha1) a

Modified from Malhi and Gill (2002a).

406 40.5 1.0

N alone

NþS

140 37.3 0.4

1228 41.4 4.4

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M. S. AULAKH AND S. S. MALHI

1995; Tandon, 1991) and Europe (Fismes et al., 2000; Walker and Booth, 2003). For example, a field study conducted in India on a soil testing low in available S showed 25% of the total increase in oil yield of mustard due to N þ S application and a marked increase in the recovery of N and S by the crop, resulting in higher NUE and sulfur use efficiency (SUE) (Sachdev and Deb, 1990). The astounding impact of N and S on each other’s recovery by the plant is illustrated in Fig. 6. Apparent fertilizer N recovery (ANR) in mustard seed increased from 25 to 42% and was accentuated from about 65 to 80% in rapeseed (seed þ straw) when N and S were applied together. The trends were similar for the apparent S recovery. Responsiveness of rapeseed to the N
S interaction may vary with site, season, form of S, and genotypes. For instance, the high glucosinolate cultivar ‘Rafal’ was less responsive (59%) than the very low glucosinolate cultivar ‘Tapidor’ (288%), with cultivar ‘Cobra’ (66%) coming somewhere in

Figure 6 Influence of N
S interaction on recovery of N and S by mustard seed and rapeseed (seed þ straw). Drawn with data from Aulakh et al. (1980, 1995).

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between (Walker and Booth, 2003). The relative content of different fatty acids in some oilseeds determines its use. An adequate supply of N, P, and S accelerates the metabolic pathway of linolenic acid synthesis, as it resulted in a large decrease in the percentage of stearic, oleic, and linolenic acids with a concurrent increase in the content of linolenic acid (Fig. 7). Linseed oil, with high linolenic acid and low oleic acid, is used to manufacture paints, oilcloths, and linoleum. Field experiments with pulses such as chickpea (Cicer arietinum L.), lentil (Lens cultinaris Medik), mungbean (Vigna radiata), blackgram (Vigna mungo), pigeonpea (Cajanus cajan (L.) Millsp.), and cowpea [Vigna unguiculata (L.) Walp] showed significant increases in grain yield due to balanced N, P, and S fertilization. For adequate rates of N þ P application, the response to S varied from 3% in cowpea to as high as 20% in lentil, as was presented in earlier reviews (Aulakh, 2003; Aulakh and Chhibba, 1992; Tandon, 1991). Several studies have shown the interaction effects of S with N and K to be synergistic in influencing the yield, quality (protein and amino acid synthesis), and nutrient uptake by different pulse crops (Tandon, 1992). In the case of N
P
S interaction, a differential behavior of one nutrient in relation to the concentration or rate of application of other nutrients has been documented. For example, in a field study with soybean, adequate levels of 25 kg N, 80 kg P2O5, and 40 kg S ha1 increased the seed and oil yield of soybean from 597 and 111 kg ha1 in control to 1735 and 412 kg

Figure 7 Influence of balanced application of fertilizer N, P, and S on the synthesis of linolenic acid in linseed oil. Drawn with data from Aulakh et al. (1989).

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ha1, respectively (Aulakh et al., 1990). However, application of excessive P (120 kg P2O5 ha1) created an imbalance and reduced the seed and oil yields. Adsorption and desorption of anions commonly used as fertilizers such as H2PO4, HPO42, PO43, and SO42 on colloidal soil surfaces occur simultaneously. Phosphate is a stronger competitor for anion adsorption sites; therefore, the large applications of P could further accentuate S deficiencies by causing concurrent desorption of SO42-S from soil (Pasricha and Aulakh, 1991) and its subsequent leaching with irrigation and rainwater. Such environmental problems could occur more commonly in coarse-textured soils with low organic matter, which have little SO42 retention capacity but have high percolation rates.

B.

CEREALS, MILLETS, VEGETABLES, AND PLANTATION CROPS

Cereals, which have relatively low S requirement, have shown significant responses to applied S. Several studies are available revealing an average cereal grain yield response from 15 to 41% (Aulakh, 2003; Scherer, 2001; Tandon, 1991). The high proportion of significant responses is particularly noteworthy in rice and wheat. The yield of wheat, grown in the coastal plain of Virginia, increased linearly with N þ S application (Reneau et al., 1986). In four different field studies in India, application of S with N and P produced an additional yield of 700 to 1300 kg and 400 kg ha1 of wheat and corn, respectively (Aulakh and Chhibba, 1992). In bread wheat, perhaps the most striking effect when the concentration of S in grain is decreased below a certain level is that dough properties change; the dough becomes stronger and less extensible, reducing the pop-loaf quality (Naeem and MacRitchie, 2003). The N absorbed in excess of protein synthesis requirement accumulates as nitrates, amides, and free amino acids in wheat and corn (Friedrich and Schrader, 1978; Stewart and Porter, 1969) and excessive levels of these metabolites are considered to be toxic (Steinberg et al., 1950). The 35S studies showed that the percentage uptake of fertilizer S in corn leaves and stems increased significantly with increasing levels of N and S due to a strong N
S interaction; conversely, application of N alone as NH4þ or NO3 resulted in a significantly higher utilization of native soil S (Dev et al., 1979; Jaggi et al., 1977). Mixing urea with elemental S in a 4:1 ratio prior to its surface application onto a calcareous soil enhanced the NUE of pearl millets from 15 to 48% while reducing the NH3 volatilization by about 50% (Aggarwal et al., 1987). In onions grown in an S-deficient soil, the highest dry matter (DM) and dry bulb yield was produced by 60 kg N þ 40 kg S ha1 (Sachdev et al., 1991). For both these parameters, the N
S interaction was synergistic and contributed

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Table VI Effect of Low and High N Rates with and without S Fertilizer Application on Fertilizer N Recovery in Onion Bulbsa Treatment

Fertilizer N in bulbs

60 kg N ha1 (no S) 60 kg N þ 40 kg S ha1 120 kg N ha1 (no S) 120 kg N þ 40 kg S ha1

11.8 kg ha1 18.1 kg ha1 (þ53%) 17.4 kg ha1 19.7 kg ha1 (þ13%)

a

Modified from Sachdev et al. (1991).

18–20% to the total response (Table VI). While the combined application of N and S produced the highest dry bulb yield, excessive levels of applied N produced high-moisture onions. Sulfur application markedly increased the NUE. Fertilizer N recovered in bulbs was more from 60 kg N þ 40 kg S ha1 than that from 120 kg N ha1 without S application. Aulakh et al. (1977) reported a potato tuber yield of 8.4 tons ha1 with the application of adequate NPK, but was increased to 12.1 tons ha1 when 25 kg S ha1 was also applied. A differential response among cultivars of the same crop could result in a significantly different response to S, as illustrated for four cultivars of wheat (Triticum aestivum L.) (Aulakh and Chhibba, 1992), coffee (Coffea Arabica) (Rao, 1988), and tobacco (Nicotiana tabacum L.) (Gopalachari, 1984).

C. GRASSES, PERENNIALS,

AND

OTHER FORAGE CROPS

In forage crops, the highest yields are generally obtained with N þ S application, suggesting that the optimum ratios of N and S fertilizers must be worked out for different soils and forages. The combined application of 60 kg N þ 40 kg S ha1 gave a 10% extra yield increase than the sum of their individual effects in Chinese cabbage (Hazra, 1988). Although a dry forage yield of 3 tons ha1 of Chinese cabbage could be obtained with an application of either 56 kg N ha1 alone or 35 kg N þ 40 kg S ha1, the combined use of both N and S seems to be the best choice because (i) the cost of lower rates of N þ S is less than the high rate of N alone, (ii) there is a higher impact on crop quality, and (iii) there is a positive effect on long-term soil fertility for sustainable production. Aulakh et al. (1976) concluded that NO3 and other soluble N compounds accumulated in alfalfa (Medicago sativa L.) forage when S was not supplied in an adequate proportion to the N supply. Thus, imbalanced N:S use could lead to NO3 poisoning of animals that are fed on such forage. Another example of positive environmental impacts of N
S interaction was illustrated by Brown et al. (2000) while working with permeable grassland soil in the United Kingdom

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Table VII Two-Year Averaged N Uptake by Perennial Grass, N Denitrified and Leached, and Nitrate-N Concentrations in Leachate in a Permeable Halse Soil of the United Kingdom with Application of Low and High Rates of N with or without S (Adequate P and K Applications Were Given)a 200 kg N ha1 Parameter N uptake (kg N ha1) N denitrified (kg N ha1) N leached (kg N ha1) Peak nitrate-N concentration (mg N l1) a

450 kg N ha1

Without S

With S

Without S

165 18.9 5.2 1.8

207 9.6 3.6 1.3

278 18.5 52.1 28.4

With S 332 12.5 17.5 7.9

Modified from Brown et al. (2000).

(Table VII). Application of the optimum amount of S along with N could drastically reduce NO3 leaching, leading to a significant increase in herbage DM by 27% and N uptake by 26%. In a 13-year field experiment on a Dark Gray Chenozem loam soil in Saskatchewan, average forage DMY was 1.41, 4.64, and 5.32 tons ha1 year1 for an unfertilized control, 112 kg N þ 11 kg S ha1, and 112 kg N þ 11 kg S þ 40 kg K ha1 treatments, respectively (Nyborg et al., 1999). Averaged over 13 years, NUE was 8.4 kg DM kg1 N year1 with the application of N alone and increased more than four times to 41.4 kg DM kg1 N year1 when S fertilizer was applied in combination with N. Application of K fertilizer in addition to N and S further increased the NUE to 47.5 kg DM kg1 N year1. In field experiments in Arkansas, the highest N recovery by coastal bermudagrass was reported where S was applied along with N (Phillips et al., 1995). Similarly, S recovery increased with increasing N rate (Phillips and Sabbe, 1994). In a field study on N and S fertilization of pasture oats in China, Wang et al. (2002) suggested that application of S fertilizer is the most appropriate way to increase forage productivity, quality, and N fertilizer use efficiency, as well as meeting S requirements of grazing sheep on S-deficient soils. In this experiment, a combined application of N and S gave a much higher dry matter and protein yield, DM digestibility, and average daily weight gain of sheep compared to N or S alone (Table VIII). Sulfur utilization from soil increased from 22.2% with S alone to 32.6% with N þ S and increased from S fertilizer from 20% with S alone to 28% with N þ S together. In summary, the studies clearly demonstrated that for economic and stable production, both N and S should be applied in appropriate ratios. Collectively, the results indicate that adequate N and S nutrition during plant growth is highly desirable and their application at optimum rates is required to improve the efficiency of one another not only for crop yield but also for produce quality in relation to protein, oil production, and fatty acid

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Table VIII Effect of Fertilizer N (138 kg N1) with or without S (30 kg S ha1) Application on Forage Dry Matter Yield (DMY), Protein Yield (PY), N and S Content, N:S Ratio, DM Digestibility, and Weight Gain of Sheep in a Pasture Experiment on Oats in Chinaa

Fertilizer treatment No fertilizer N only S only NþS a

DMY (kg ha1)

PY (kg ha1)

N content (%)

S content (%)

4753 8154 5276 9104

606 1180 674 1375

2.04 2.32 2.04 2.42

0.14 0.12 0.24 0.20

N:S ratio

DM digestibility (%)

Average daily gain of sheep weight (g day1)

14.40 19.51 8.51 12.03

59.5 62.3 61.6 69.0

105.2 139.3 106.7 173.3

Modified from Wang et al. (2002).

content. The N
S interaction studies indicate that maximum yield is only attained when the two nutrients are provided in a balanced way and correct diagnosis of nutrient deficiency is vital. If a S deficiency is misdiagnosed as an N deficiency and additional N is applied as a consequence, then the crop growth would be adversely affected and a greater penalty would result in terms of crop yield and quality, nutrient use efficiency, and excessive accumulation of NO3 and other toxic metabolites in forages, plus negative environmental effects such as leaching of NO3, denitrification, and ammonia volatilization. The response of crops to N
S interaction, however, could vary according to site, season, form of S, crop, and genotype.

V. NITROGEN
CALCIUM AND NITROGEN
MAGNICIUM INTERACTIONS Although Ca requirements for plant growth and metabolism are low, it has great significance in balancing levels of other nutrients, including N. Fertilization with NO3-N generally enhances the Ca and Mg concentration in plants driven by the need for a cation–anion balance. When N is supplied as NO3-N, electrical neutrality is maintained internally by its reduction in synthesizing organic acids by the release from roots of anions such as OH or HCO3 or by the uptake of cations (Wilkinson et al., 2000). When N is supplied as NH4þ-N, internal electrical neutrality is maintained by the release of Hþ or by uptake of anions. Application of lime and farmyard manure (FYM) significantly increased water-soluble N and fixed NH4þ in the acidic soils of India, leading to increased N uptake by soybean and wheat (Bishnoi et al., 1984; Prasad et al., 1986). In a highly acidic soil (pH 4.5), a substantially higher rice yield obtained with the combined application of

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lime and NPK than with NPK or lime alone indicated that soil acidity is the main constraint in the utilization of soil nutrients by the crop (Fageria and Baligar, 2001). Once acidity is corrected, the uptake of soil N, Ca, and some other nutrients increases many folds. Other associated problems, such as high concentrations of Al and Mn, reduced BNF, and decreased root growth, may lead to a decline in water and nutrient use efficiencies. In one of the experiments conducted by Malhi et al. (1995a) in the Prairie Provinces of Canada, the grain yield of barley was 2.1 tons ha1 without lime and 3.1 tons ha1 with lime at a 50 kg N ha1 rate (i.e., an increase of NUE by 20 kg grain kg1 of applied N) and was 2.3 tons ha1 without lime and 3.5 tons ha1 with lime at a 100 kg N ha1 rate (i.e., an increase of NUE by 12 kg grain kg1 of applied N). These findings suggest that on acid soils, crops fertilized with N would show a yield and NUE advantage from lime. Sodic Solonetzic soils are also deficient in Ca for optimum plant growth and can be reclaimed by applying gypsum to replace Naþ with Ca2þ on the cation-exchange sites. In a Black Solonetzic soil in Alberta, Canada, an application of gypsum increased the concentration of extractable Ca and reduced the sodium adsorption ratio (Malhi et al., 1992). In this experiment, a N
Ca interaction not only improved the soil chemical properties and crop yield, but also enhanced the concentration of Ca, K, and Zn in the flag leaf of barley while decreasing Na concentration.

VI. NITROGEN
MICRONUTRIENTS INTERACTIONS Deficiencies of different micronutrients are not widespread, but whenever they occur, they can result in a serious reduction in grain yield and quality of crops and utilization efficiency of other nutrients and water. However, in certain situations, more than one micronutrient can become deficient and are needed for optimum crop production and quality. For instance, field experiments on corn in Egypt showed that sowing of corn seeds soaked in a Zn, Mn, and Fe mixture could enhance NUE, leading to a remarkable improvement in grain yield, N recovery, and saving of N fertilizer, and at the same time reduced the potential for pollution of soil and groundwater from leached nitrate-N (Teama, 2001).

A. ZINC Enhanced crop growth due to applied N at a marginal level of Zn in soil often induces Zn deficiency, causing a decline in the crop response to N itself. Practically, a N
Zn interaction is an important factor in nutrient

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367

management for all those field crops that require moderate to high amounts of N ( (Bajwa and Paul, 1978; Kene and Deshpande, 1980; Kumar et al., 1985; Sakal et al., 1988; Verma and Bhagat, 1990). For instance, as the N supply to rice increased, Zn deficiency became more acute (Singh and Singh, 1985). In another field study, application of ZnSO4 increased the response of rice to urea-N by 400 to 600 kg grain ha1 (Savithri and Ramanathan, 1990). Thus, N and Zn showed synergistic effects and the best yield could be obtained with the optimum combination of both. When this optimum combination of N and Zn for obtaining best yield is disturbed either by high doses of N or Zn, the yield generally decreases. In a field experiment on a sandy loam calcareous soil of Bihar, India, maximum benefits from Zn application were derived only under an optimum supply of NPK (Table IX). Nitrogen application has been reported to influence Zn absorption by plants and vice versa. In corn, the Zn concentration in shoots was highest when both N and Zn were applied together followed by the application of Zn alone, N alone, and no-fertilizer treatment in descending order (Dev and Shukla, 1980). This shows that for maximum utilization of native soil Zn or applied Zn, the presence of adequate amount of N is essential. The differences among N sources with regard to efficiency of Zn utilization may be attributed to the effect of the accompanying anion on the mobility of Zn as well as to the reduction in soil pH, which enhances Zn availability. Application of 200 mg N kg1 soil through (NH4)2SO4 caused a decrease in soil pH from 8.4 to 7.9 three weeks after its application, leading to the increase in soil-available Zn from 0.34 to 0.49 mg kg1 soil (Dev and Mann, 1972). An adequate supply of N also enhanced the translocation of Zn from roots to other parts of pearl millet plants in the presence of applied N (Kumar et al., 1985). The synergistic N
Zn interaction has also been reported to increase the N concentration in different crops (Hulagur and Dangarwala, 1983; Kene

Table IX Effect of Different Zinc Levels without and with N, P, and K Application on Grain Yield of Wheat (kg ha1)a Rate of Zn (kg Zn ha1)

Treatment N (kg N ha1) 0 50 100 LSD0.05 a

P (kg P2O5 ha1)

K (kg K2O ha1)

0

5

10

0 30 60

0 25 50

1450 2730 3530

1580 2880 3840 220

1640 3030 4040

Modified from Sakal et al. (1988).

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M. S. AULAKH AND S. S. MALHI

and Deshpande, 1980; Singh and Tripathi, 1974), as Zn helps accelerate protein synthesis and the BNF efficiency of legumes. Application of 5 mg Zn kg1 soil significantly increased the BNF by cowpea to 156.7 kg ha1, relative to 129 kg ha1 for a no-Zn control (Yadav et al., 1984). The better utilization of N due to a synergistic N
Zn interaction could also markedly increase the energy values, carbohydrates, total lipids, and lysine and histidine amino acids in addition to proteins in cereals as well as in legumes (Dwivedi and Randhawa, 1973; Kene and Deshpande, 1980).

B. COPPER

AND

MANGANESE

Numerous reports suggest that N
Cu interactions could be synergistic or antagonistic. Camp and Fudge (1939) were the first to report that Cu deficiency symptoms became more severe when N was applied to Cudeficient soils. Thereafter, this was confirmed by a number of studies. Copper-deficient citrus leaves were found to contain a higher amount of N than Cu-sufficient leaves (Camp and Fudge, 1939). However, in Brassica juncea, an antagonistic N
Cu interaction was observed only when both were in excess supply (Antil et al., 1988). At lower levels of Cu (2.5 and 5 mg Cu kg1 soil), the effect of N on Cu uptake was synergistic. It has been reported that cereals having protein-rich grains are more susceptible to Cu deficiency than those poor in grain proteins (Nambiar, 1976). Wheat grown on Cu-deficient soils is highly susceptible to the disease “stem melanosis” caused by Pseudomonas cichorii, which could be effectively controlled by the application of Cu (Malhi et al., 1989; Piening et al., 1987). In a 3-year field experiment with wheat receiving 110 kg N ha1 on a Cudeficient soil in Saskatchewan, the no-Cu control plot produced 1566, 1620, and 1262 kg grain ha1 in 1999, 2000, and 2001, respectively (Malhi et al., 2003b). The corresponding grain yield with a foliar application of 0.25 kg Cu ha1 as Cu chelate-EDTA at the flag-leaf growth stage was 2709, 2675, and 2641 kg ha1. While the NUE with the N alone ranged from 9.3 to 12.0 kg grain kg1 N, it increased to 19.6–20.1 kg grain kg1 N with the N þ Cu application. The availability of Mn is controlled by the total quantity of Mn, pH, SOM, and redox potential in soils. Manganese uptake can be stimulated by either or both forms of N. The NO3 form may lead to a greater uptake of Mn2þ, whereas the NH4þ form may increase the bioavailability of Mn by acidification. Schomberg and Weaver (1991) showed that Mn decreased BNF in arrowleaf clover (Trifolium sp.) more than mineral N uptake. Consequently, the potential impact of excess soluble Mn in the root zone was partially offset by the availability of mineral N for uptake and metabolism.

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C. IRON, BORON, COBALT, AND MOLYBDENUM The interaction of N with Fe, B, Co, and Mo is of great economic significance, especially in legumes. This is because these four micronutrients are closely associated with steps in the process of BNF. Iron is an integral part of nitrogenase, ferrodoxin, leghaemoglobin, and cellular enzyme systems in nodules (Evans and Russel, 1971). When Fe and Zn are in short supply in soils, Rhizobium fails to function and fix N2, as has been observed in French beans (Garg, 1987). An application of 5–10 mg Fe kg1 soil alone or in combination with Zn developed N-fixing nodules and increased the yield of French beans, leading to a remarkable increase in NUE. Most of soil Fe is present as unavailable Fe(III), which must be reduced to the Fe2þ form before plants can take it. The acidic nature of some N fertilizers enhances the availability of micronutrient cations including Fe in soils. In neutral to alkaline soils with low available Fe, increased acidity with NH4þ may enhance the availability of Fe2þ by promoting the reduction of Fe(III). In a sand culture experiment, irrespective of the Fe source (Fe-citrate, Fe-EDTA, Fe-EDDHA), the iron requirement for the normal growth of rice plants receiving N in the form of nitrate or urea was about four times higher than that of plants receiving N as ammonium nitrate (Takkar et al., 1989). The uptake of N by several rice cultivars grown on sandy loam soil increased at the lower dose of Fe, but was reduced at higher levels of iron (Tandon, 1982). Such behavior could be due to a reduction in yield because of excessive Fe or the ability of plants to utilize Fe efficiently at lower application rates. Boron is important for the synthesis of glutamine, development of nodules in legumes, and pollen tube growth. Application of B increased the N concentration in chickpea (Yadav and Manchanda, 1979), lentil (Singh and Singh, 1983), and peanut (Patel and Golakia, 1986), presumably due to the favorable effect of B on nodulation as nodule counts were found to increase by 37% over no-B control (Patel and Golakia, 1986). Conversely, increasing rates of N significantly decreased the boron concentration in wheat, barley, and alfalfa at the boot stage, illustrating that N application is helpful in alleviating B toxicity in soils low in available N (Aggarwal and Yadav, 1984; Gupta, 1976; Willett et al., 1985). However, optimum use of B is very much necessary as indiscriminate use of B could cause B toxicity in plants. For example, application of B beyond 3.5 mg kg1 soil in sandy loam and 4.5 mg kg1 soil in clay loam soil becomes toxic to chickpea (Singh et al., 1976), illustrating that the safe and toxic limits differ with soil texture. Cobalt is required by Rhizobium for fixation of N2 in legumes as it plays a vital role in the formation of vitamin B12, which is essential for the formation of hemoglobin. However, studies demonstrating the impacts of N
Co interaction on NUE are lacking.

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Molybdenum is important for the nutrition of legumes, as it is essential for the activity of enzyme nitrogenase. Application of 2 mg Mo kg1 soil significantly improved nodulation, dry weight of nodules, leaf area, shoot dry weight, N content, and yield of French beans (Acharya and Biswas, 2002). In a study with Dark Yellow Oxisol soil in Brazil, the application of 10 kg urea-N ha1 at planting and 40 kg N ha1 side dressed in conjunction with 20 kg Mo ha1 by foliar spray resulted in the highest grain yield and consequently NUE in dry beans (Fullin et al., 1999). Molybdenum is also essential for NO3 reduction in nonlegumes, and hence NUE and crop quality. While summarizing the interactive effects of Mo with other nutrients, Gupta (1997) concluded that N applications over time might decrease Mo uptake. Part of the N
Mo interaction may arise from the opposite effects of NH4þ and NO3 forms on soil pH, which would change Mo availability.

VII. NITROGEN
WATER INTERACTION Water and N are the most important factors controlling crop growth and grain production. Soil moisture conditions affect the availability, movement, and uptake of nutrients by crops. Ideally, for the most efficient use of soil and fertilizer N, adequate quantities of water must be available throughout the crop growth period. Among different factors that influence the NUE, water seems to be the most critical. Much of the increase in the yield and quality of field crops during the last half century has been due to improved cultural practices, including increased soil water supply, which is frequently the limiting plant growth factor even in humid tropics. Thus, it is not surprising that the provision of irrigation facilities, especially where groundwater is of good quality, has rapidly expanded crop production and enhanced crop yield. Water is stored in the soil before it is taken up by plants via its roots and is then transported to foliage and is lost to the atmosphere through transpiration. Thus, retention and movement of water within soil, proliferation of the root biomass in the soil profile, and uptake of soil water by plants in relation to atmospheric evaporative demand determine WUE. Therefore, impacts of the N
water interaction are, to a large extent, controlled by plant roots, which help the crop maintain effective capacity for absorbing nutrients as well as water, and more so from subsoil. In addition to several other factors (discussion of which is beyond the scope of this review), the time and extent of soil wetting have profound effects on the root development of crops, which in turn determine the water extraction pattern of crops, as has been shown for the response of dryland wheat to wetting patterns varying from year to year (Singh et al., 1975). Gajri and Prihar (1985) revealed that the 2-year mean root mass densities of wheat in 0- to 180-cm and 30- to 180-cm soil

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layers were 70 and 140% higher in early postseeding irrigation than without it. Gajri et al. (1989) illustrated that early wetting not only increased root biomass and length, but also influenced the rate of downward root extension. Selection of crops and cropping sequences for high WUE and NUE are dictated by the availability of water. Because the water availability spectrum vis-a`-vis NUE is quite different under (i) rain fed or dryland and (ii) partially or fully irrigated environments, these are hence discussed separately.

A. DRYLAND ENVIRONMENTS The amount and intensity of precipitation, melting snow, topography, infiltrability, and water retentivity of soil, and depth of root zone determine the amount of plant-available soil water. The crop yield response and recovery of applied N are influenced by the soil water status in several ways. While inadequate soil moisture results in poor crop growth, leading to a reduced uptake of nutrients and low NUE, excessively wet soil conditions cause substantial N losses by leaching and denitrification of NO3-N, resulting in low NUE. In many dryland areas, the yield response of crops to fertilizer N is related to the total amount of precipitation (Campbell et al., 1993a; Nuttall et al., 1992). With an average rate of 60 kg N ha1, Nuttall et al. (1992) obtained a canola seed yield of 2460 kg ha1 in a year with 162 mm of rainfall in the growing season, whereas seed yield was only 370 kg ha1 in a year with 95 mm rainfall. In a 22-year study with bromegrass (Bromus inermis Lyess) in Alberta, 112 kg N ha1 increased the forage yield from 4.3 to 6.6 tons ha1 when precipitation in the growing season increased from 116 to 256 mm (Malhi et al., 2004c). In a field investigation in China, recovery of applied N increased from 6.4% in drought years to 58.6% in high or normal rainfall years (Dang and Hao, 2000). Under rain-fed conditions, it is not only the total water that becomes available in a season, but also its time of availability during the crop growth period that affects the NUE. Sandhu et al. (1992) showed that the amount and distribution of rainfall during two main phases of crop development (vegetative and reproductive phases) greatly influenced the NUE of rain-fed wheat. Seasonal rainfall of less than 150 mm, received as half in the vegetative phase and the other half in the reproductive phase (1:1 distribution), was more effective than 2:1 or other patterns in increasing the wheat grain yield. However, for seasonal rainfall exceeding 150 mm, the 2:1 distribution between vegetative and reproductive phases was more effective than the 1:1 distribution. The additional rainfall of 100 mm received in the 2:1 pattern reduced the N requirement for a given yield by 30 to 49 kg N ha1 compared with the same rain received in the 1:1 fashion. In studies with dryland wheat

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in Saskatchewan, in addition to the amount and distribution of rainfall during two main phases of crop development, the available moisture storage at seeding also affected the NUE (Read and Warder, 1974). Thus, Selles et al. (1992) suggested fertilizer recommendations according to different levels of available water, which soil testing labs have adopted. Conservation of soil moisture, for example, by eliminating tillage and mulching, would thus enhance crop yields and NUE. In a field experiment on a Gray Luvisol soil of Alberta, an increase in the grain yield of barley with an application of 50 kg N ha1 was 570 kg ha1 under zero tillage (ZT) as compared to 410 kg ha1 under conventional tillage (CT) (Izaurralde et al., 1995). The significantly higher NUE of 11.4 kg grain kg1 N under ZT as compared to 8.2 kg grain kg1 N under CT (Izaurralde et al., 1995) was most likely achieved by conserving more soil moisture under ZT (Aulakh and Rennie, 1986; Bonfil et al., 1999; Malhi and O’Sullivan, 1990; Nyborg and Malhi, 1989). While working with a ZT system, Campbell et al. (1993b) also observed an excellent relation between dryland wheat yield and available water, fertilizer N rate, and soil nitrate-N. The conservation of moisture as determined by topography or landform within a field could influence crop yields, NUE, and WUE. For example, a concave landform, which retains more spring soil moisture than a convex position after melting of snow, provided a greater yield response of canola to fertilizer N, higher N uptake, and recovery of applied 15N (Malhi et al., 2004b; Pennock et al., 2001). In perennial grassland experiments in Alberta and Saskatchewan, NUE of 34–44 kg DM kg1 of applied N was more than double in relatively moist areas than the 11- to 19-kg DM kg1 N obtained in dry areas (Malhi, 1997; Malhi et al., 1997a, 2004a). From data in 15N-labeled experiments in various parts of the world, several researchers (Malhi, 1995; Malhi et al., 1995b, 2004b; Pilbeam, 1996) observed that there was more recovery of 15N fertilizer in the crop under humid or subhumid environments, whereas the recovery of 15N fertilizer was more in the soil under dry or semiarid environments. This poor plant NUE and higher accumulation of NO3-N in soil increase the potential for nitrate-N leaching from applied N (Sardas, 2002). Under water-scarcity conditions, application of N helps enhance both WUE and NUE. Kmoch et al. (1957) showed that N application enhanced total water use, as well as the depth of water extraction by winter wheat. Compared with the unfertilized crop, Brown (1971) and Bond et al. (1971) reported increased water use by N-fertilized winter wheat as well as spring wheat. Heitholt (1989) found that optimum N supply, as reflected by leaf N concentrations, promoted higher WUE in drought-stressed wheat in the southern Great Plains of the United States. In a similar study with a dryland corn–wheat rotation in Punjab, a 80-kg N ha1 application to wheat slightly changed the water extraction from 0 to 90 cm, but resulted in almost a 100%

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373

greater water extraction from the 90- to 180-cm soil layer compared with the unfertilized crop (Singh et al., 1975). Better rooting and accelerated root extension into deeper layers and greater use of soil-stored water due to applied N have been observed in a number of studies from several countries (Gajri et al., 1989; Prihar et al., 2000). In fact, a yield goal with a given water supply could be achieved using various combinations of fertilizer N with available soil moisture at seeding and rainfall during vegetative and reproductive phases of crop development (Benbi et al., 1993). However, when precipitation is adequate and well distributed, the N supply could become the major factor in controlling yield (Stout et al., 1988). Under such nonstressed conditions, WUE in wheat increased with increasing N up to 140 kg N ha1 (Eck, 1988). For pearl millet production in West Africa, the addition of fertilizer increased soil water use over the control (Bationo et al., 1993).

B. FULLY AND PARTIALLY IRRIGATED ENVIRONMENTS Irrigation water in certain regions may be plentiful and is used to meet the water requirements of crops, whereas in others it may be unable to meet total crop needs. Under both situations, N and water have been shown to exhibit strong synergistic interactions with respect to crop yield, yield components, NUE, WUE, and environmental impacts. Under constrained irrigation resources, small supplemental irrigation at a crucial growth stage could substantially improve crop yield and NUE. Several 15N-labeled and other studies have shown that irrigation could significantly increase the recovery of applied N in grain and straw at harvest, ranging from 10% in wetter years to over 60% in drier years (Garabet et al., 1998; Geesing et al., 2001; Hartman and Nyborg, 1989). Prihar et al. (1989) observed that 85% of the variations in dryland wheat yield could be explained by water supply and applied N. Whitfield and Smith (1992) reported a NUE of 20.7 kg wheat grain kg1 N with the application of 150 kg N ha1 under irrigation compared to a NUE of 5 to 1.5 kg grain kg1 N with an application of 150 kg N ha1 without irrigation. In a study in Victoria, Australia, irrigated canola accumulated 35 kg N ha1 more than without irrigation in one of two years (Taylor et al., 1991). In Punjab, with a water supply of 300 and 450 mm, an application of 80 kg N ha1 increased the 4-year averaged wheat yield from 2.2 and 2.7 tons ha1 without N to 3.0 and 4.5 tons ha1, respectively (Prihar et al., 1981). In Egypt, rapeseed receiving irrigation at 18- to 22- and 29- to 30-day intervals had seed yield increases by 29.5 and 10.9%, respectively, over those irrigated at a 41-day interval (Shahin et al., 2000). Thus, a simultaneous increase in water and N supply produced remarkably higher yields than those obtained with water and N alone.

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For achieving maximum NUE and WUE, applications of water and fertilizer should be in concert to minimize NO3-N losses from the soil profile and to maximize uptake by the crop. For example, on a low-water retentive porous sandy loam soil, Chaudhary and Bhatnagar (1977) obtained a maximum wheat yield with 150 kg N ha1 applied in three splits in combination with 360 mm water applied in seven splits. In contrast, the yield was lowest with full application of N at seeding and 360 mm water supplied in four splits. Thus, instead of fewer large applications, small but frequent irrigations often show higher benefits both in terms of crop production and WUE (Saini et al., 1989) and reducing leaching of the nitrate (Singh and Sekhon, 1976). Similarly, a number of field studies have shown that fertilizer N interacts strongly with levels of irrigation for crop yield and WUE (Prihar et al., 2000; Rao et al., 1991). Gajri et al. (1993) showed low WUE with high irrigation at no-N, as well as with high N at zero irrigation, indicating that the crop suffered from N and water stress, respectively. Highest WUE obtained at intermediate irrigation and N rates suggest that both inputs should be at optimum rates. Furthermore, the irrigation schedule for crops must consider available water storage in the potential root zone and distribution of rainfall. It is, therefore, necessary to optimize allocation of the available water supply among various periods of crop growth. Using their method based on equimarginal productivity, Sandhu et al. (2000) demonstrated that fertilizer N and water could play a substitutional role for each other to achieve a medium yield target (Fig. 8). For example, under a water supply of 350 mm, 90 kg fertilizer N ha1 is required to achieve a wheat grain yield target of 5 tons ha1. An additional 50-mm water supply reduces the N requirement to 40 kg N ha1 for the same yield target. However, there are very few options for obtaining high wheat grain yield targets of 6 tons ha1, which require high amounts of both fertilizer N and irrigation. Balanced use of N and P could further improve WUE. In a study on Loess slope farmland of China, combined application of N and P in the ratio of 3:1 resulted in the highest synergistic interaction in increasing soybean yield by 87 to 470% and WUE by 70 to 438% over their individual applications (Chen et al., 2003). Another study in China showed that N and P fertilization promoted the growth of a wheat root system, leading to increased WUE (Zhang and Liu, 1993). Irrigation practices that encourage utilization of soil-stored water also decrease deep-drainage losses of water and nutrients. Hoogenboom et al. (1987) obtained a deeper and more prolific rooting pattern of soybean by withholding irrigation. However, withholding early irrigation could be more detrimental to root proliferation and more so on coarse textured soils that dry faster and develop greater mechanical resistance (Prihar et al., 2000). Under such conditions, water added a few weeks after seeding not only

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Figure 8 Wheat yield isoquants for computing optimal fertilizer N and available water supply to obtain targeted 4, 5, and 6 tons grain ha1. Adapted from Sandhu et al. (2000).

becomes available to the crop itself, but also has a priming effect on the use of soil-stored water and nutrients. Clarke et al. (2001) also confirmed these findings in their study with sandy loam soil in Berkshire, United Kingdom, where applying water to winter wheat at very early growth in the spring encouraged canopy development and improved both N recovery and grain yield. Similarly, in China, the effect of limited irrigation on wheat yield and NUE was highest at the jointing stage, followed by booting, tillering, and grain-filling stage in decreasing order (Deng, 2002). In addition to the seasonal water supply, water retentivity of soil and optimal N supply determine the NUE. For instance, the NUE was lower on less water-retentive loamy sand soil than on sandy loam soil (Table X). At 80 kg N ha1, NUE increased with an increase in irrigation up to 200 mm. With 120 kg N ha1, the NUE did not increase with increasing irrigation from 50 to 125 mm, but increased remarkably when irrigation was further increased to 200 mm. With 40 kg N ha1, NUE at 200 mm irrigation was lower than that at 125 mm. The modeling analysis further revealed that clay soil is more productive than sandy soil in terms of grain yield, WUE, and NUE in the high and medium rainfall zone due to the low nitrate-leaching potential and water retentivity of clay soil (Asseng et al., 2001). Irrigation also helps improve the NUE by placing the fertilizer N in the appropriate soil zone where it is less prone to NH3 volatilization losses and is accessible to the growing roots. For example, application of urea-N before

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Table X NUE in Wheat (kg Grain kg1 N) as Affected by Application of Fertilizer N and Water in Different Combinations on Two Soilsa Rate of N (kg N ha1) Number of irrigations Loamy sand 0 1 2 3 Sandy loam 0 1 2 3 a

Total irrigation water added (mm)

40

80

120

0 50 125 200

5.3 23.3 23.0 19.5

4.8 12.0 17.6 20.0

0.9 9.8 8.8 14.8

0 50 125 200

8.5 20.2 33.2 30.2

5.5 18.4 25.5 30.3

1.5 17.8 17.0 23.7

Adapted from Gajri et al. (1993).

preseeding irrigation has been found to be superior to drilling of N at seeding in wheat (Sandhu and Sidhu, 1996). In their study with sandy loam soil, 39% of the fertilizer N applied before preseeding irrigation was located in the 20to 60-cm layer after irrigation, which, being in the moist zone for a longer period, (a) enhanced its absorption by the plant roots, (b) supported root growth in deeper soil layers, and (c) minimized NH3 volatilization. The 15Nlabeled studies of Malhi (1995) and Malhi et al. (1996) confirmed pronounced improvement in the plant recovery of broadcast urea-N on ZT soil or on perennial grassland soil when it was followed by an immediate water supply. Similarly, the controlled N
water interaction field study of Hartman and Nyborg (1989) confirmed that band placement of urea-N into the subsoil was much superior than surface broadcast-incorporated N in enhancing crop yields and plant recovery of applied 15N, as well as in reducing N immobilization in soil, especially under drought conditions. The foregoing discussion reveals that both NUE and WUE are interdependent and that the efficiency of one input is influenced by the adequacy of the other; their optimal use can ensure great benefits due to a synergistic N
water interaction. However, application of N should be reduced under a limited availability of soil moisture because excessive N produces vigorous vegetative growth, resulting in greater water loss via transpiration (Kappen et al., 2000), leading to a water deficit (Herwaarden et al., 1998). However, the excessive irrigation frequency may increase grain yield but could decrease grain quality (Gill and Singh, 1999). Also, application of excessive N accompanied by heavy irrigations, as in rice crops, can cause NO3-N to move below the rooting zone and ultimately reach groundwater (Aulakh et al.,

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377

2000) and enhance denitrification losses and emission of N2O (Aulakh et al., 2001b) and CH4 (Aulakh et al., 2001c). In other crops such as wheat, super optimal rates of fertilizer N and irrigation could produce excessive vegetative growth without any benefit to grain yield (Parihar and Tripathi, 1989). The review of literature thus revealed that high yields, NUE, and WUE could be sustained with minimal N losses by split applications of fertilizer, combined with an appropriate irrigation schedule, to ensure absorption of N from a deep soil profile by plant roots.

VIII.

EFFECTS ON CARBON STORAGE AND SEQUESTRATION IN SOIL

The sustainability of agricultural production is linked to soil quality, which in turn is a function of SOM. Organic matter improves soil tilth, biological activity and diversity, aids air and water movement, promotes water retention, and reduces soil erosion, in addition to influencing pesticide efficacy and its decomposition process. Soil organic C (SOC) is an index of SOM, which is the major source of plant nutrients. Cultivation practices cause a substantial decrease in total organic C in soil (Malhi et al., 2003a; McGill et al., 1988), which may be contributing over time to the increased levels of atmospheric CO2 causing global warming. The maintenance of SOC at existing levels or its enhancement by sequestering C is important in sustaining and improving the soil quality and productivity and in ameliorating the greenhouse effect. Carbon sequestration occurs when a given set of management practices lead to a positive balance in the flow of C to soil (Izaurralde et al., 1998). Improved NUE as a result of other management practices, including the interaction of N with other nutrients, as discussed in preceding sections, could influence the storage of SOC. The effects of NUE are expected to be greatly different in temperate regions than in tropical and subtropical regions, as temperature is the predominant singular factor controlling the rate of mineralization of SOM, the discussion is thus presented accordingly.

A.

TEMPERATE REGIONS

In temperate regions, where mineralization of SOM is slow and crop residues are generally returned to the soil, long-term applications of N to annual crops have often shown a considerable increase in SOC. The total organic C (TOC) after 10 years of N fertilization in barley in soil was increased significantly (Nyborg et al., 1995b; Solberg et al., 1997). Crop

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residues, including roots, are the primary source of organic materials added to the soil in many cropping systems. The increase in TOC in 0- to 15-cm soil was linearly (R2 ¼ 0.76*; p  0.05) related to the amount of C returned to the soil in crop residues, which was associated with the increase in crop yield with N fertilization (Nyborg et al., 1995a). For example, in this study, seed yields of barley were 898, 2092, 1085, and 2643 kg ha1, respectively, in the no-N ZT, surface-broadcast 56-kg N ha1 ZT, no-N CT, and broadcastincorporated 56-kg N ha1 CT treatments. The corresponding values for TOC were 32.1, 42.0, 28.7, and 34.5 tons C ha1, and for total N (TN) were 2.77, 3.74, 2.51, and 3.01 tons N ha1, respectively. The increase in TOC was 14% after 18 years of continuous wheat (Janzen, 1987), and the cropping systems comprising wheat, fallow, flax, lentil, rye (Secale cereale L.), and perennial forages showed an increase of 2.8 to 9.5 tons TOC ha1 (Campbell et al., 2000). These observations are further supported by the presence of higher SOC in cropping systems that included forages in 4 of 9 years (Angers et al., 1999) and that were under long-term ZT management (Campbell et al., 2001; Dormaar and Carefoot, 1998). While evaluating the effects of 35 years of different cropping systems, Gregorich et al. (2001) observed that soils under corn monoculture cropping had about 70–80% less C than those under continuous grass; however, the effect of fertilizer application on the enrichment of SOC by about 6 tons C ha1 was observed only under the corn monoculture. In a 10-year tillage and N management experiment in Kansas, Matowo et al. (1999) found that concentrations of SOC increased with an increasing rate of N fertilizer application to sorghum under both ZT and CT systems, with the largest increases of 14.5 to 19.2 g kg1 soil in the surface 0- to 2.5cm layer. They demonstrated that SOC in different soil depths could be influenced by the N source, rate, and method of placement. As most of the biologically related characteristics are generally SOC driven, enhanced accumulation of SOC is often associated with a proportionately increased size of labile pools of microbial biomass C, light fraction organic C (LFOC), microbial biomass N, and hydrolyzable and potentially mineralizable N. A study by McCarty and Meisinger (1997) in the United States showed that the application of fertilizer at 135 kg N ha1 caused a substantial increase in TOC, TN, biomass N, and active N in ZT soils compared to the no-N control. While the application of fertilizer N at an excessive rate of 270 kg N ha1 tended to suppress biologically active N pools, it had no detrimental impact on TN or TOC, suggesting that adequate fertilizer application and other management practices can improve soil quality. Similarly, studies in Georgia suggested that SOC and organic N could be conserved and aggregation of soil improved by sequestering atmospheric CO2 and N2 into the soil by using ZT with cover crops and N fertilization (Sainju et al., 2001, 2003). While SOC, TN, microbial biomass C, and LFOC remained

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379

unaffected in unfertilized long-term ZT management, these parameters showed positive responses to fertilization (Campbell et al., 2001). Research on perennial forages has shown that C and N sequestration in soil is influenced by the rate and source of N fertilizer application (Baron, 2001; Malhi et al., 2002b, 2003c,d; Mensah et al., 2003). With the addition of N fertilizer at 168 kg N ha1, the ability of perennial forages to sequester C in soil was increased by about 50% from 50.3 g C kg 1 soil in the no-N control to 75.5-g C kg1 soil (Malhi et al., 1997b). On a Solonetzic soil where different rates of N were applied to smooth bromegrass, the amount of TOC and TN increased with the N fertilization rate (McAndrew and Malhi, 1992). Among different N sources used in their study, urea produced the smallest increase in TOC, whereas the largest increase was realized with ammonium nitrate. Studies in Saskatchewan have shown that the addition of N and S to a grass forage stand substantially increased DM yield, TOC, and levels of LFOC compared to the no-N control (Nyborg et al., 1997, 1999). In these experiments, forage DM, NUE, TOC, and TN all increased substantially with N þ S treatment after 13 years, but the value of these parameters decreased in the N-only treatment because of a nutrient imbalance (Malhi et al., 2004d). For example, mean annual forage dry matter yields were 1.33, 1.12, and 4.84 tons ha1 in the unfertilized control, N alone, and N þ S treatments, respectively. The corresponding values for TOC in the 0- to 37.5-cm soil were 183.4, 170.4, and 202.3 tons C ha1. The optimum amounts of forage yield, TOC, and TN with a combined application of N and S illustrate the importance of balanced nutrition of crops. In a grassland study in Alberta, Canada, the mass of TOC and LFOC in surface and subsurface layers increased with the N rate (Table XI). While the maximum mass of TOC in the soil profile (130 tons C ha1) was observed at 224 kg N ha1, the maximum gain in the mass of TOC with each kilogram of applied N (10.9 kg C kg1 N) was at the lowest rate of 56 kg ha1 of applied N and had the lowest gain in TOC (3.0 kg C kg1 N) at the highest rate of 336 kg N ha1 (Malhi et al., 2003d). In this experiment, the annual average hay yield increased from 1.41 tons ha1 in the no-N control to 5.82 tons ha1 with 224 kg N ha1. Because most of the aboveground portion of bromegrass was removed as hay, the increase in TOC and LFOC in soil was mainly associated with the increased root biomass of forage grasses in response to N fertilization (Lorenz, 1977; Malhi and Gill, 2002b) and possibly some biomass of fallen dead leaves. These studies suggest that when aboveground bromegrass production is increased with proper fertilization, the corresponding increase in root biomass contributes to sequester more SOC. The preceding discussion indicates that fertilizer N is more effective on grasslands managed as hay than cereal cropping systems, most likely due to a greater production of root biomass by forage grasses and a reduction in tillage frequency compared to cereals.

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Table XI Mass of Total Organic C and Light Fraction Organic C after 27 Annual Applications of Six N Rates to Bromegrass Grown as Hay on a Thin Black Chernozemic Soil in Alberta, Canadaa Annual rates of N (kg N ha1 year1) Soil depth (cm)

0–5 5–10 10–15 15–30 Sum

0

21.2 18.1 15.3 33.5 88.1

224

336

SEMb

Total organic C mass in soil (tons C ha1) 25.8 28.3 31.3 32.4 20.4 20.2 20.7 21.2 17.0 17.6 18.1 20.2 41.5 46.1 45.0 56.0 104.7 112.1 115.2 129.9

33.2 20.3 17.0 44.2 114.7

1.2*** 0.6* 0.9* 3.8* 4.6***

56

112

168

Light fraction organic C mass in soil (tons C ha1) 0–5 5–10 10–15 15–30 Sum

1.74 0.73 0.50 0.74 3.71

4.14 1.38 1.01 1.64 8.18

7.83 1.53 1.11 2.21 12.68

11.87 2.05 1.02 1.68 16.62

13.87 2.44 1.27 2.22 19.80

13.10 2.70 1.28 1.62 18.70

0.75*** 0.11*** 0.08*** 0.25*** 0.84***

a

Modified from Malhi et al. (2003d). Standard error of means. *p  0.05. ***p  0.001. b

B. TROPICAL

AND

SUBTROPICAL REGIONS

Under tropical and subtropical climate, the mineralization of SOM is accelerated by the prevailing high temperature. Moreover, crop residues are generally removed from the field, especially in developing countries, to use them for other purposes or are burned to facilitate fast and easy land preparation. The literature is replete from several countries of these regions that applications of N alone or in combination with P and K do not show pronounced effects on SOC in field crops; SOC is slightly decreased (Aoyama and Kumakura, 2001; Belay et al., 2002; Kapkiyai et al., 1999; Yadav, 1998), maintained due to a quasi-equilibrium established between mineralization and added C through root biomass (Aulakh et al., 2001a; Roy et al., 2001), or shows a small increase over a prolonged period (Benbi and Biswas, 1997; Bhatnagar et al., 1994). For example, in a long-term experiment with an annual corn–wheat–forage cowpea-cropping sequence in Punjab, India, application of N alone or in combination with optimal P and K for 22 years exhibited a small change in SOC (Fig. 9). However, application of FYM in conjunction with optimum NPK increased SOC from 2.0 g kg1 soil at the start of the experiment to 4.2 g kg1 soil, along with a proportionate increase in alkaline KMNO4-extractable N (potentially

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381

Figure 9 Changes in soil organic carbon in the surface 0- to 15-cm layer of semiarid soil in the subtropics under different fertilizer treatments to annual corn–wheat–forage cowpea for 22 years. Drawn with data from Benbi and Biswas (1997).

available N) from 105 to 134 kg N ha1 (Benbi and Biswas, 1997). Similarly, SOC increased from 3.6 to 6.1 g kg1 soil in a short period of 2 years when organic materials and NPK were applied together (Kumar et al., 2000). In a field study with a corn–wheat rotation in Rajasthan, India, fertilizer application at 120 kg N and 17.5 kg P ha1 gave the highest grain yield and showed an increase in SOC from 2.1-g kg1 soil in the unfertilized control to 3.3-g kg1 soil after 11 years (Bhatnagar et al., 1994). In fact, several studies have shown that a long-term application of N alone usually decreases SOC, whereas applications of P and K along with N minimize the depletion of C from soil and tend to stabilize or enhance SOC (Gangaiah and Prasad, 1999; Kumar and Yadav, 2001; Sharma and Subehia, 2003; Tolanur and Badanur, 2003). In a long-term experiment with annual fertilization to a wheat–corn rotation from 1982 to 2000 on a calcareous sandy loam soil under irrigation in China, the concentration and mass of TOC and TN increased with a balanced fertilization of N, P, and K as compared to an unfertilized control and was maximized when all nutrients were applied together (S. Yang, personal communication). For example, the mass of TOC in the 0- to 20-cm soil was 19.6, 20.2, 20.9, and 21.4 tons ha1, respectively, in the unfertilized control, N, NP, and NPK treatments. In this study, the corresponding mean seed yields obtained in these treatments were 3430, 4886, 6995, and 7509 kg ha1, respectively (Yang et al., 2004). This suggests a close relation between SOC and crop yield increase from balanced fertilizers applications. The situation could be markedly different when crop residue or stubbles are incorporated into soil after crop harvest. For example, in a 59-year experiment with sugarcane in South Africa, SOM in the surface 10-cm soil

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M. S. AULAKH AND S. S. MALHI

increased with increasing inputs of crop residues along with annual NPK fertilizer applications (Graham et al., 2002). Similarly, SOC was substantially improved with the application of NPK þ FYM to potato-based cropping (Roy et al., 2001). In the humid ecosystem at Kalyani, India, an integrated nutrient supply through inorganic and organic sources to a rice–wheat system (where soil remained submerged during the rice-growing period) had pronounced effects on SOC (Hegde, 1998). In a 4-year study with an annual rice–wheat rotation in the semiarid subtropical climate, fertilizer N and P had no effect on SOC, but green manure application resulted in significantly higher SOC concentrations (Table XII). The incorporation of wheat or rice residue accentuated SOC deposition and reduced soil bulk density. These results exhibited a positive relationship of NUE with SOC (r ¼ 0.66, p  0.05) and an inverse relationship of SOC with soil bulk density (r ¼ 0.94, p  0.01). Such improvements in soil physical conditions (decreased bulk density and resultant improved water infiltration rates and soil structure) and increased SOC play an important role in the wheat crop following the puddle rice culture in a rice–wheat cropping system for establishing seedlings and also because wheat, unlike rice, is a deep-rooted crop. Few reports are available from subtropical and tropical regions that indicate that when ZT management is adopted, it could further enhance SOC. For instance, in a long-term experiment with 17 consecutive crops of corn in Table XII Effect of Integrated Use of Fertilizer Urea N (FN), Green Manure (GM), Wheat Residues (WR), and Rice Residues (RR) on Rice Yield, Nitrogen Use Efficiency, Soil Bulk Density, and Carbon Sequestration in Rice–Wheat System in Subtropicsa Treatmentb Rice Control 120 kg FN ha1 GM20 þ 32 kg FN ha1e WR6 f þ GM20 þ 32 kg FN ha1 120 kg FN ha1 LSD0.05 a

Rice yieldc (tons ha1)

NUE (kg rice grain kg1 N)

Soil bulk densityd (g cm3)

SOCd (g kg1)

120 kg FN ha1 120 kg FN ha1

3.40 5.62 5.85

— 18.5 20.4

1.60 1.60 1.54

3.74 3.71 4.05

120 kg FN ha1

5.92

21.0

1.50

4.92

RR6 f þ 120 kg FN ha1

5.63

18.6

1.54

4.33

0.05

0.22

Wheat

0.24

Modified from Aulakh et al. (2001a). Basal P was applied in all treatments to both rice and wheat. c Three-year (year, 2–4 of the experiment) mean yields. d Measured at the end of 4-year experiment. e Amount of 120 N kg ha1 applied through 20 tons GM and the balance through fertilizer N. f Wheat residues (WR) and rice residues (RR) applied at 6 tons ha1. b

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383

western Nigeria, the mean SOC was 18.6 g kg1 soil under ZT as compared to 12.2-g kg1 soil in CT (Lal, 1998). Moreover, the impact was much higher when recommended fertilizers were applied and crop residues retained. These results show that the regular input of crop residues along with inorganic fertilizers improve soil quality and more so in ZT management. In a rice monoculture, where soil remains submerged for the whole year, a higher accumulation of SOC is frequently observed due to slower decomposition under anaerobic conditions (Cassman et al., 1996; Sahoo et al., 1998). In an 8-year annual rice–rice sequence experiment at Hyderabad, India, application of fertilizers at a recommended dose of 120 kg N, 26 kg P, and 33 kg K ha1 increased SOC from 4.9 g kg1 soil in the unfertilized control to 7.3 g kg1 soil (Mohammad, 1999). Similarly, in a 2-year period, the soil under a rice–rice cropping system in Philippines accumulated 2736 kg C ha1 as compared to only 457 kg C ha1 in a corn–rice system (Witt et al., 2000). In summary, adequate and balanced fertilization can be used to improve SOC in soil by sequestering more atmospheric C. The increase in organic C concentrations in soil is influenced by N rate, source, application time, and placement method. The majority of the C storage in soil occurs in the surface layers, and increasing the duration under ZT management causes the thickness of C stratification to increase. The change in LFOC, a potential soil quality indicator, is more responsive and sensitive to N application than TOC. Perennial forages can sequester more C in soil than cultivated annual crops because of elimination of tillage. The increased C storage in soil from N application is due to an increase in aboveground crop residue production and root biomass induced by fertilization, and resultant residue C input to the soil, thereby sustaining or improving the fertility, quality, and health of the soil. In subtropical and tropical regions, despite the fast decomposition of SOM, proper management of NPK nutrients can maintain soil fertility by reducing the depletion of C from soil and increasing C sequestration rates. It appears that adoption of ZT management, increased use of balanced fertilization from inorganic and organic sources, and retention of crop residues would increase SOC storage in agricultural lands in the future.

IX. NITROGEN LOSSES AND TRENDS OF FERTILIZER CONSUMPTION A. NITROGEN LOSSES

AND

USE EFFICIENCY

Recovery of applied N by crops under field conditions ranges from 25 to 34% for rice and 40 to 60% for other crops, with global average value of about 50% (Mosier, 2002). The unutilized N may remain in soil in various

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forms and=or get lost through several processes, including NH3 volatilization, denitrification, and nitrate leaching, and the literature is replete with such evidence (Aulakh, 1994; Aulakh et al., 1992; Goulding, 2004; Keeney, 1982). Nevertheless, a brief mention of the fate of N in applied fertilizers is made in this review. An example of how fertilizer NUE decreases as N in excess of that needed for economic rates of crop production is shown by a study conducted by Broadbent and Carlton (1979). Their results and synthesis of the results by Legg and Meisinger (1982) revealed that maximum NUE was found at the same fertilizer N rate needed to obtain maximum corn yield. When N was applied in excess of this amount, large amounts of NO3 accumulated in the soil profile, which were susceptible to denitrification and leaching. Residual NO3 in the soil profile could be leached with irrigation water. High rates of leaching and nitrification in permeable or porous soils and relatively high fertilizer N rates combine to make NO3 leaching a serious problem in many irrigated soils (Aulakh et al., 2000). In intensively cultivated semiarid subtropical region of Punjab, where average fertilizer N consumption increased from 56 to 188 kg N ha1 year1 during 1975 to 1988, NO3-N concentration in the shallow well waters increased by almost 2 mg liter1 (Aulakh and Bijay-Singh, 1997). The NO3 concentration of the Santa Ana River of California increased from an average of 2 mg liter1 in 1930 to about 6 mg liter1 in 1969 (Ayers, 1978). In Nebraska, NO3-N of groundwater increased, on average, from 2.3 mg liter1 in 1961 to 3.1 mg liter1 in 1971 while fertilizer N use quadrupled and irrigation increased 50% (Muir et al., 1973). Thus, fertilizer N in excess of crop potential utilization leads to losses to the environment; obviously, considerable room for improving management to decrease losses exists.

B. GLOBAL CONSUMPTION

OF

N, P, AND K FERTILIZERS

In addition to N losses, excessive N application can lead to a decline in crop production through deficiencies of macro- and micronutrients in production systems. The foregoing subsections revealed that NUE could be improved by the optimum and balanced use of different plant nutrients. Among these, the majority of N, P, and K is supplied by synthetic fertilizers. Since 1960–1961, global synthetic N-fertilizer consumption has increased from 10.8 to 82.8 Tg (1 Tg ¼ 1012g) N in 2001–2002 (IFA, 2003). The corresponding increase in the consumption of P and K fertilizers was from 4.7 to 14.6 Tg P and 7.0 to 18.7 Tg K (IFA, 2003). There is no doubt that these fertilizers have contributed significantly to continuing increases in grain production to meet the increasing demands of both human and livestock population. However, the global distribution of fertilizers has changed markedly in the past few decades. While N, P, and K fertilizer use, as well as

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Figure 10 Fertilizer N, P, and K consumption in developed and developing parts of the world. Drawn with data from IFA (2003).

grain production, has declined in developed countries since 1985, they have continued to increase linearly in the developing world, although at different rates, over the past three decades (Fig. 10). Nitrogen is used in optimum and even excessive amounts, whereas P and K are not always supplemented adequately (Aulakh and Bahl, 2001; Ma, 1977; Mosier, 2002; Zhu, 1997).

C. P=N AND K=N RATIOS OF CROPS

AND

APPLIED FERTILIZERS

A balanced and judicious use of fertilizers is the key to efficient nutrient use and for maintaining soil productivity. Balanced fertilization requires an optimum input of N, P, and K in the ratios needed to maintain soil fertility to optimize crop productivity and to minimize N losses. The main cereal crops, such as wheat, rice, and corn, typically have P=N ratios in both grain and straw in the narrow range of 0.15–0.24 (Fig. 11). Oilseeds such as

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Figure 11 P=N and K=N ratios of common cereals, oilseeds, pulses, and other crops. Note that in the case of sugarcane and potato, data are for canes and tubers, respectively. Drawn with data from TFI (1982) and Aulakh and Bahl (2001).

sunflower, rapeseed, and linseed=flax (Linum usitatisimum L.) have similar P=N ratios in seed, but are much lower in straw (0.07–0.10). Legumes such as soybean, peanut, and mungbean grain have relatively lower P=N ratios (0.05–0.12) because they accumulate high amounts of N through BNF. In case of sugarcane, the P=N ratio is 0.25. The K=N ratio of crop straw or stover is much higher than the P=N ratio in grains, respectively, ranging from 1.85–2.38 as compared to 0.19–0.84 in the grain of cereal crops, 1.05– 3.57 as compared to 0.15–0.22 in oilseeds, and 0.19–0.89 as compared to 0.04–0.21 in legumes (Fig. 11). Potato tubers have a K=N ratio of 1.48 as compared to a P=N ratio of 0.20. According to the Fertilizer Institute, if P and N fertilization is required, these should be applied in a P=N ratio of

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0.15 (TFI, 1982). As K is also more susceptible to leaching than P, removal of K from the field is much more than P. The ratio of global consumption of P=N in 1995 was 0.17 (0.39 P2O5=N) and K=N was 0.22 (0.26 K2O=N) and has been predicted up to the year 2030 to remain relatively constant (Mosier, 2002). However, a large disparity in fertilizer consumption ratios exists within countries of a continent as well as among different continents (Table XIII). In North and Central America, the United States and Canada are using near optimum N and P but K

Table XIII Consumption of Fertilizer N, P, and K Along with Their Ratios in Major Consuming Countries of Different Continents in 2000–2001 (FAO, 2003) Fertilizer N, P and K consumption Continent and country North and Central America United States Canada Others South America Brazil Argentina Others Europe France Germany Spain UK Russian Fed Others Asia China India Pakistan Malaysia Japan Others Oceania Australia New Zealand Africa Egypt South Africa Others World

N (000 ton: N)

P (000 ton: P)

K (000 ton: K)

P=N ratio

K=N ratio

10251.3 1554.4 1347.3

1663.4 267.9 137.7

3689.0 256.8 145.5

0.162 0.172 0.102

0.360 0.165 0.108

1999.3 481.3 906.4

1111.0 137.3 170.1

2398.2 23.4 64.1

0.556 0.285 0.188

1.200 0.049 0.071

2316.0 1847.6 1113.7 1030.0 960.0 5855.5

347.2 153.4 248.1 124.0 122.3 2862.1

858.1 451.5 388.0 315.4 149.4 1828.4

0.150 0.083 0.223 0.120 0.127 0.489

0.371 0.244 0.348 0.306 0.156 0.312

22482.0 10920.2 2265.7 525.0 487.0 9532.8

3671.1 1840.4 295.9 110.6 255.0 1534.3

2778.4 1300.8 19.0 539.4 317.8 1460.6

0.163 0.169 0.131 0.211 0.524 0.161

0.124 0.119 0.008 1.027 0.653 0.153

1002.2 242.0

478.9 200.0

168.1 114.5

0.478 0.826

0.168 0.473

1073.4 411.0 450.0 81624.5

66.1 95.2 109.9 14259.8

37.3 107.1 108.6 18386.5

0.062 0.232 0.244 0.175

0.035 0.260 0.241 0.225

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M. S. AULAKH AND S. S. MALHI

consumption is suboptimal in Canada due to high K testing soils. In South America, Brazil is using well above optimal proportions of N, P, and K. In fact, the K=N ratio in Brazil is the highest in the world, as fertilizer N is used in relatively small amounts for the predominantly grown soybean crop. On the other side, all other countries in this continent may need to enhance the use of K fertilizers. European countries show fewer variations in P=N and K=N ratios and are quite close to desirable levels except Germany, where the P=N ratio is very low (0.08), and Russia with the lowest K=N ratio of 0.16. Within Asia, China and India, which are the highest consumers of fertilizers in the world, perhaps need to use substantially more K. While Malaysia ranks second in the K=N ratio (1.03), Pakistan has the lowest K=N ratio of 0.008 in the world. In Africa, Egypt uses relatively low proportions of P and K fertilizers. Amazingly, where P=N ratios in different regions=countries vary 10-fold (0.083 to 0.826), K=N ratios (0.008 to 1.20) vary 150-fold. There appears to be a potential for imbalance in P and K fertilization in the future that may present problems for food production. Regions where crop residues are not returned to the field and=or which have degraded soils, deficiencies in P and K may limit production and quality of crops, even though N may be applied in adequate or excessive amounts. For instance, in India and China, where almost 50% of the global N fertilizer is used, K=N ratios of 0.124 and 0.119 (Table XIII) are far below the K=N ratio removed by the crops (Fig. 11). However, these guiding ratios might not be applicable in all situations, as the need and use of N, P, and K fertilizers could vary with crops, soils, and management practices. For instance, legumes use only a small starter or pop-up dose of N and, therefore, fertilizer P=N and K=N ratios for these crops should be much higher than other crops. The depletion of K can be avoided to some extent by taking care to return all crop residues to the field. For soil supplying capability for K and management effects, a specific example of data from Punjab, the cradle of the Green Revolution in south Asia, is cited here. Punjab, a northwestern state covering only about 1.5% of the geographical area and producing about 11% of total food grains of India, contributes 64% wheat and 42% rice in the national food pool. Despite intensive cropping and high productivity, the use of fertilizer K in Punjab is almost negligible (0.04 K=N). However, its removal by crops is 19% greater than that of N. Mining of soil K has progressively increased from 132,000 tons in 1960–1961 to 683,000 tons in 1998–1999, and the present K balance is negative (Aulakh and Bahl, 2001). Apparently the negative K balance has not affected crop productivity, which appears to be stabilized around 16 kg food grains kg1 nutrient used as compared to only 8 kg food grains kg1 nutrient at the India level. This is due to the sufficient release of available K from the K-rich illitic alluvial soils and the return of K to the soil by burning 70% of K-rich rice straw in the field (Aulakh and Bahl, 2001). History reveals that in the early

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sixties, when fertilizer responsive high-yielding crop cultivars were introduced, optimum yields could be obtained with the application of fertilizer N only. However, the bumper harvests soon depleted other nutrients and within a few years P deficiency appeared in a big way. This was followed by a deficiency of Zn, and application of Zn with the adequate dose of N, P, and K enhanced the N recovery and NUE by crops in such intensively cropped soils (Benbi and Biswas, 1997). As crop demand for K increases with larger N and P applications and the reserves of soil K are being depleted faster, future long-term high productivity cannot be maintained in such systems if balanced fertilization is not practiced.

X. CONCLUSIONS AND FUTURE RESEARCH NEEDS The global distribution of fertilizer use has changed markedly in the past few decades. While N, P, and K fertilizer use has declined in developed countries since 1985, it has continued to increase in the developing world at linear rates. During the past five decades, the role of fertilizer N in augmenting food grain production has been widely recognized in both the developed and the developing world. The experience of the past half-century has revealed that fertilizers are the kingpins of the green revolution and are the best hope for meeting food challenges in the future. Even though agricultural production has increased dramatically, along with a matching increase in the consumption of fertilizer N, the NUE remains relatively low, with a global average of about 50%. The inefficient use of fertilizer N in most parts of the world has led to losses of unutilized N to the environment through leaching and gaseous emissions. Thus, increasing NUE remains a clear goal for maintaining food production while avoiding excessive N use and undesirable environmental pollution. In most of the regions, N is used in optimum and even excessive amounts, while P and K are not always supplemented adequately. The ratios of global consumption of P=N and K=N are 0.17 and 0.22, respectively, and have been predicted to remain relatively constant for the next 3 decades. However, a large disparity exists in fertilizer consumption ratios within countries of a continent as well as among continents. The synergistic N
P interaction is responsible for a sizable yield gain leading to considerable improvements in both NUE and PUE. Most of the studies reported from several regions pointed out that crop responses to applied N level off earlier, whereas a synergistic response to N þ P enables the crop to produce markedly higher yields. Higher levels of N are thus only effective when combined with higher rates of P. Similarly, applied N enhances the crop response to increasing levels of P, and consequently the

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quadratic response to varying rates of applied P could continue to be linear up to higher rates of P. In situations where farmers cannot afford to apply both N and P in optimum amounts, it would be better to apply smaller amounts of both N and P instead of large amount of N alone. Studies on the N
P interaction have helped to understand and interpret the complex effects of field management and to identify approaches in different ecosystems to enhance the benefits and to develop new strategies. For instance, synergistic interactions between N and P have helped explain the effect their banding has on root growth and proliferation and also on the development of appropriate N þ P fertilizer combinations. Significant N
K and N
P
K interactions could be expected where higher doses of N are used to increase crop production. These interactions are strongly positive and profitable at high levels of crop productivity in crops having high K requirements. Hence, exploiting the N
K and N
P
K interactions could remarkably increase the efficiency of applied N. The split application of N and K is used increasingly in fertilizer practices, which helps in creating a better interaction of K with N, particularly in situations where farmers are using low amounts of N. The precaution, however, is needed to synchronize the application of N and K at the most N-demanding plant growth stages. Such a practice would be highly beneficial in coarsetextured porous soils. The N
S interaction studies indicated that a maximum crop yield is only attained when the two nutrients are provided in a balanced way, and correct diagnosis of nutrient deficiency is vital. If S deficiency is misdiagnosed as N deficiency and, as a consequence, additional N is applied, then the crop growth would be affected adversely and a greater yield and NUE penalty would result. A large number of reports suggest that N and S nutrition during the plant growth is highly desirable and their application at optimum rates is required to improve NUE and SUE, as well as to maintain oil content and fatty acid quality in oilseeds and protein concentration in most of the crops. Information on N
Ca and N
Mg interactions is scanty and is mainly related to the positive effects of lime in acidic soils and gypsum in sodic=Solonetzic soils for correcting soil pH and improving plant growth. In certain situations, one or more micronutrients may become deficient, and their application is needed for optimum crop production and quality. While the N
Zn interaction is highly synergistic, numerous reports suggest that the N
Cu interaction could be either synergistic or antagonistic. The interaction of N with Fe, B, Co, and Mo is of great economic significance, especially in legumes, because these micronutrients are closely associated with one or the other step in the process of BNF. Interaction of N with water plays an important role in root biomass production and growth, especially in the deeper soil layers, for extracting essential

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nutrients in both dryland and irrigated environments. The efficiency of both N and water is influenced greatly by the adequacy of each other, and their optimal use can ensure large benefits due to synergistic N
water and N
P
water interactions. In situations where irrigation water is plentiful, excessive irrigation must be avoided, as it could drastically decrease grain quality and enhance the downward movement of NO3-N below the rooting zone, ultimately reaching the groundwater. The best strategy for sustaining high yields, NUE, and WUE with minimal N losses would be splitting applications of fertilizers in a combination with an appropriate irrigation schedule in order to optimize absorption of N from the deep soil profile by plant roots. Adequate and balanced fertilization plays a significant role in increasing the storage of organic C and N in soil to improve its fertility, quality, and health by sequestering atmospheric C. Most of the C stored in soil occurs in the surface layers and it increases with duration at a slow rate. The majority of total C stored in soil is in the light fraction organic matter, particularly under ZT and perennial grasslands, and LFOC (a potential soil quality indicator) is more responsive to N application than TOC. Perennial grasslands, even when hay is removed, sequester more C in soil than in cultivated annual crops. The increased C storage in soil from proper fertilization is due to an increase in the aboveground crop residue production and root biomass and the resultant residue C input to the soil. The amount of increase in SOC in soil is linked to the quantity of crop residues, and is associated with crop yield, nutrient uptake, efficiency, and recovery, which are influenced by N rate, source, time, and method of application. Even in subtropical and tropical regions where SOM decomposes much faster, proper management of NPK nutrients can maintain soil quality by reducing the loss of C from soil and increasing C sequestration rates. The literature suggests that adoption of ZT management, increased use of balanced fertilization from inorganic and organic nutrient sources, and returning of crop residues to soil would increase C storage in agricultural lands in the future. The role of environmental factors and management practices in regulating NUE in field crops is now better understood. Nutrient interactions and availability of nutrients (e.g., Zn, Cu, Fe, and Mn) are regulated by a number of physical, chemical, and biological factors, such as pH, redox potential, temperature, soil organic matter, and water status in soils. Similarly, the nature and magnitude of interaction of N with other nutrients and water are determined by soil and crop type, level of available N and other nutrients in soil, rate of applied N and other nutrients, and climatic conditions. The effect of each individual parameter on crop growth, yield, and quality under controlled conditions is well established but their intertwined impacts often cannot be predicted with reasonable accuracy under field conditions. During the past few decades, extensive information has become available on NUE in field crops, which has enhanced our understanding on the nature

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of interactions of N with other nutrients, processes involved, and their impacts under different environmental and agronomic settings. The “best management system” is not fixed but depends on the major limiting factors in each individual region, country, state, or farm. A synergistic interaction is entirely a bonus, being an outcome of the skillful balancing of nutrients. It adds to the returns and not to the cost, thus raising the benefit:cost ratio further. Collectively, the benefits of improved use efficiency of N and other nutrients achieved by their balanced and optimum use include the following. i. Reduction in the dose of N resulting in an economy of N to the farmers. ii. Realizing high yield potentials as a result of synergistic nutrient interactions. iii. Help in enabling the plant to resist the damage from pests and diseases and to tolerate relatively dry moisture conditions. iv. A favorable influence on crop quality and biochemical constituents of the produce (protein, oil, fatty acids, nitrate, etc.). v. Minimizing the amount of fertilizer nutrients left in the soil after harvest, thus reducing the potential for negative environmental impacts through leaching of nutrients and emission of greenhouse gases. Research conducted in different countries during the last few decades has reduced uncertainty in the estimates of usefulness and losses from fertilizer N vis-a`-vis other inputs in field crops and has evaluated the impact and cost– benefit ratio of their uses and resultant interactions for food production. However, we are still a ways off from a satisfactory comprehension of this phenomenon, especially when looking at the interactive relationships of different inputs together. Therefore, in consideration of the aforementioned discussion, we see the following research needs. 1. Data relating fertilizer nutrient rates and soil test indices to grain yield under intensive water management are needed to maximize fertilizer use efficiency. 2. Delineation of areas and situations where N and other inputs are overor underused. 3. Attempts should be made to work out the N requirements of various crops more closely and accurately avoiding yield limitations due to other nutrients and water, which may be helpful in deciding the optimum rate of N on one hand and synergy with different nutrients and growth factors on the other. Once the intertwined effects of N interaction with other nutrients are reasonably predictable in a particular region, these should be utilized to obtain the potential maximum economical yield. 4. Crop and location-specific fertilizer recommendations should be made available to farmers. This would help in increasing high quality crop

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5.

6.

7.

8.

9.

10.

393

produce, resulting in high economic benefits, keeping agricultural production sustainable, and decreasing pollution. In soils that contain abundant K, the response to K can be expected for the most K-demanding crops only and a separate strategy will have to be evolved. In India and China, however, where almost 50% of the global N fertilizer is used, a K=N ratio of 0.12 is far below the K=N ratio removed by the crops (0.15–0.84 in grain and 1.05–3.57 in straw). Thus, in regions where crop residues are not returned to the field and=or have degraded soils, deficiencies in P and K may limit the production and quality of crops in the future. Because the majority of landmass in temperate and humid regions is covered by acidic soils, a thorough understanding of interactions of N with Ca and Mg is essential for developing balanced fertilizer application strategies and avoiding crop losses due to antagonistic effects, e.g., of Ca
Mg, K
Ca, and K
Mg interactions. Considering the enormous variety in physiology and morphology of the different field crops and their cultivars, the impact of different traits is of utmost importance for devising efficient nutrient use strategies. Thus, improving the knowledge on such plant traits that determine the nature (synergistic or antagonistic) and extent of interactions would expand our ability to effectively manage balanced and optimum crop nutrition. Based on differences among cultivars, it should be feasible to select and breed high yielding crop cultivars having an extensive root system with a high capability to respond to synergistic nutrient interactions. The potential for imbalance of P and K fertilization may present problems for food production in the future. As N-driven crop production is hardly sustainable, identification and exploitation of factors and technologies for assuring positive interactions of N with other nutrients and water would hold the key for increasing returns from applied N in terms of crop yield and quality, nutrient use efficiency, and minimizing negative environmental effects. The development of packages of management involving several nutrients together, as the situation demands, can effectively enhance their use efficiency in a socioeconomically acceptable fashion. Improvements in the spatial resolution of nutrient interactions are needed to distinguish responsive and nonresponsive locations, regions, or countries for multinutrient strategies. This should be followed by the development of decision support systems to find out the “best-fit multinutrient management” that considers site-specific settings of natural and socioeconomic factors. As excessive N results in vigorous vegetative growth, leading to greater water loss via transpiration, there is a need to work out the rates of N according to the availability of soil moisture.

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ACKNOWLEDGMENTS The authors are grateful to Drs. Arvin Mosier (USDA-ARS) and Adrian Johnston (PPIC) for useful comments on the manuscript.

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Advisory Board John S. Boyer University of Delaware

Paul M. Bertsch University of Georgia

Ronald L. Phillips University of Minnesota

Kate M. Scow University of California, Davis

Larry P. Wilding Texas A&M University

Emeritus Advisory Board Members Kenneth J. Frey Iowa State University

Eugene J. Kamprath North Carolina State University

Martin Alexander Cornell University

Prepared in cooperation with the American Society of Agronomy Monographs Committee David D. Baltensperger, Chair Lisa K. Al-Almoodi John M. Baker Kenneth A. Barbarick David M. Burner

Warren A. Dick L. Richard Drees Jeffrey E. Herrick Bingru Huang

Michel D. Ransom Craig A. Roberts David L. Wright

Contributors Numbers in parentheses indicate the pages on which the authors’ contributions begin.

D. C. Adriano (1), Savannah River Ecology Laboratory, The University of Georgia, Aiken, South Carolina 29802 Milkha S. Aulakh (341), Department of Soils, Punjab Agricultural University, Ludhiana 141004, Punjab, India N. S. Bolan (1), Institute of Natural Resources, Massey University, Palmerston North, New Zealand Donald N. Duvick (83), Iowa State University, Ames, Iowa 50011 Reza Ghorbani (191), Ecological Farming Group, School of Agriculture, Food and Rural Development, University of Newcastle, NaVerton Farm, Stocksfields, Newcastle upon Tyne, NE43 7XD, United Kingdom Alfred E. Hartemink (227), ISRI–World Soil Information, 6700 AJ, Wageningen, The Netherlands Carlo Leifert (191), Ecological Farming Group, School of Agriculture, Food and Rural Development, University of Newcastle, NaVerton Farm, Stocksfields, Newcastle upon Tyne, NE43 7XD, United Kingdom S. Mahimairaja* (1), Institute of Natural Resources, Massey University, Palmerston North, New Zealand Sukhdev S. Malhi (341), Agriculture and Agri-Food Canada, Research Farm, Melfort, Saskatchewan, Canada S0E 1A0 Brian McGonigle (147), Crop Genetics, E.I. du Pont de Nemours and Company, Wilmington, Delaware 19880 Rajendra Prasad (255), Division of Agronomy, Indian Agricultural Research Institute, New Delhi, India B. Robinson (1), HortResearch, Palmerston North, New Zealand Wendy Seel (191), Plant and Soil Science, School of Biological Sciences, University of Aberdeen, St. Machar Drive, Aberdeen, AB24 3UU, United Kingdom Oliver Yu (147), Donald Danforth Plant Science Center, St. Louis, Missouri 63132

*Current Address: Department of Environmental Sciences, Tamil Nadu Agricultural University, Coimbatore 641003, India xi

Preface It is indeed a pleasure to announce that in the latest Journal Citation Reports, Advances in Agronomy is rated #1 among Agronomy journals and serials. Volume 86 continues the tradition of past volumes in that it contains seven first-rate reviews that will be of interest to plant and soil scientists. Chapter 1 is an outstanding and comprehensive review of arsenic in soil and water environments, including aspects of risk assessment, remediation, and human health. Chapter 2 is a definitive treatise on the role of breeding in advancing maize yields. It is written by one of our most distinguished agronomists, Donald N. Duvick. Chapter 3 is a timely review on isoflavones, which are phenolic secondary metabolites found primarily in legumes. The authors discuss health benefits of isoflavones, biological functions in plants, targets of isoflavone biosynthesis key enzymes involved in isoflavone biosynthesis, and metabolic engineering of isoflavone accumulation in legumes and non-legumes. Chapter 4 deals with advances in methods for biocontrol of weeds, including the link between environmental factors and plant infection development, and the use of formulation technology. Chapter 5 reviews nutrient stocks, nutrient cycling, and soil changes in cocoa ecosystems. Chapter 6 is a detailed review of rice-wheat cropping systems including discussions on climate and soil, agronomic management, genetic manipulation, sustainability of rice-wheat cropping systems, and socio-economic and policy factors. Chapter 7 is a comprehensive review of nitrogen use efficiency as influenced by interactions of nitrogen with other nutrients, nutrient cycles, and water. Donald L. Sparks

xiii

Index aquatic plants for stripping of, from water 57 bioavailability and toxicity of 30–8 biochemical reactions of 21–2 biochemistry of, in soil 19–26 biogenic redistribution of 12–13 biogeochemistry of, in aquatic environments 28–30 biological methods of removal of, from aquatic environments 56–9 biological remediation of soil contaminated with 44–52 biomethylation of 58–9 biosorption of 58–9 biotransformation of 28–30 chemical form of 15–19 chemical remediation of soil contaminated with 40–3 chemical speciation of 17, 18 conceptual integrated approach for remediation of 62 contamination of 3 controlling 3–4 defined 2–3 dietary intake sources of 34 distribution of, in aquatic environments 14–15 distribution of, in soil 13–14 dynamics of, in soil and aquatic systems 20 eVects of soil treatments 43 filtration of 52–3 geogenic sources of 5–11 geothermal sources of 10 hyperkeratosis from poisoning 37 immobilization of 41 industrial uses for 11 leaching 27 manufacturing of 11–12 methylation of 45 microbial community and 33 microbial removal of 58–9 microorganisms capable of methylation of 47 mobility of, in groundwater 6–7

A Abiotic stress tolerance to, in hybrids 98–106 trait changes increasing 127 unspecified 103–6 Adjuvants 212 Adsorption of arsenic 20–5 of arsenic in aquatic environments 28, 54–5 Agriculture defined 192 history of 192 Alfisols 244 Alternaria alternata 199 Amaranthus retroflexus growth stage of 199 AN11 169 Anthesis 94 Anthesis-silking interval (ASI) 94–5 Aquatic media adsorption of arsenic in 54–5 aquatic plants for stripping arsenic in 57 Arsenic contamination in 8, 9 biogeochemistry of arsenic in 28 dynamics of Arsenic in 20 phytoremediation of arsenic in 56–8 precipitation of arsenic in 55–6 references on removal of arsenic from 53 removal of arsenic from 52–62 Arabidopsis 175, 178 Arable land available 257 in RWCS countries 294 Argentina genetic yield gains in 90 Armyworms 309 Arsenic (As) adsorption of 20–5 adsorption of, in aquatic environments 28, 54–5 anthropogenic sources of 11–12

411

412

INDEX

Arsenic (As) (cont. ) mobilization of, by phosphate compounds 51 multiscalar-integrated risk management of 59–62 physical remediation of soil contaminated with 38–40 physicochemical methods of removing, from aquatic environments 52–6 physiochemical properties of 11 potential risks of, to terrestrial biota 31, 32 precipitation of, in aquatic environments 55–6 redox reactions of 25–6 references on concentrations of 7 references on contamination of in aquatic media 8, 9 references on eVects of, on human health 36, 37 references on phytoremediation and 50 references on sources of 6 references on stripping, from water 53 removal of, from aquatic environments 52–62 risk management of 38–62 risk of, to humans and animals 34–8 in soil 4 speciation of 15–19 stable states of 28 surface compexation of 20–5 teratogenic eVects of 35 tests for 15 toxicity of, to plants and microorganisms 30–4 viable remediation technologies for 39 water-extractable 43 Arsenic contamination geogenic sources of 5–11 in soil and aquatic systems 5 sources of 4 Arsenic trioxide (As2O3) 11 Arsentopyrites (FeAsS) 6 As(III) 6 maximum adsorption of 24 spread of 16 As(V) maximum adsorption of 24

As. See Arsenic ASI. See Anthesis-silking interval

B Balanced NPK fertilization response to 283 in RWCS 282–3 Benthic microbes 29 Bioaccumulation 44–5 Biocontrol agents in biotic environment 197–8 Biogenic redistribution 12–13 Bioherbicides 217 specific uses of 218 Biological control agents foliar applications 213–5 formulation of 211–7 host range of 217–8 markets for 217 soil applications 215–7 Biological N fixation (BNF) 342, 349 Biological weed control bioherbicide 195–6 biotic environment and 197–200 classical 194–5 conservation and augmentation 196 defined 193 delayed dew period and 204–5 dew period and 203–4 dew temperature and 205–6 eYcacy of 196–211 light and 207–8 limitations of 217–9 moisture and 202–3 physical environment and 200–8 soil microorganisms and 210–11 soil nutrients and 208–9 soil reaction and 210 temperature and 201–2 wind and 207 Biomass production 30–1 Biomethylation of arsenic 26–7, 58–9 microorganisms capable of, of arsenic 47 Bioremediation engineered 44 intrinsic 44 of soil 44–6

INDEX Biosorption 58–9 Biotechnology 134, 135–6 aid of 136 Biotic environment biocontrol agents in 197–8 biological weed control and 197–200 virulence in 197 weed growth stage in 198–9 Biotic stress hybrid tolerance to 106–8 trait changes increasing 127 Biotoxicity of Arsenic to plants 30–4 Biotransformation of Arsenic in aquatic environments 28 Black Mexican Sweet (BMS) maize 176 Black rust 309 Blast 309 BMS maize. See Black Mexican Sweet maize BNF. See Biological N fixation Boron nitrogen interactions with 369–70 in RWCS 289 BPH. See Brown plant hopper Brazil genetic yield gains in 90 Breeding total yield gains and 91–2 Broad-spectrum pathogens 219 Brown plant hopper (BPH) 309 Brown rust 309 Bt transgenes 136–7 Bundling 298

C C4H. See Cinnamic acid 4-hydroxylase CaVeoyl 170 Cancer 151 Canopy gas exchange 112–13 Carbon storage fertilization in 391 nitrogen and 377–83 soil changes and 380 in temperate regions 377–80 in tropical regions 380–3 CCA. See Copper-chromium-arsenate CCA sites 27

413

Cereals N
K interactions in 352–5 N
P interactions in 345–7 N
S interactions in 362–3 CHA. See Chemical hybridization agents Chalcone isomerase (CHI) 157, 159 in isoflavone biosynthesis 165–6 metabolic channeling and 178–9 reaction scheme of 165 Chalcone reductase (CHR) 159 in isoflavone biosynthesis 166–8 Chalcone synthase (CHS) 157, 171 metabolic channeling and 178–9 Chemical hybridization agents (CHA) 306–7 Chemical speciation 17, 18 CHI. See Chalcone isomerase China climate and soil in 263 crop calendar for RWCS in 259 hybrid rice in 306 record yields in 272 RWCS in 257, 261 wheat yields in 266 Cholesterol 151 CHR. See Chalcone reductase CHS. See Chalcone synthase Cinnamic acid 4-hydroxylase (C4H) 157 Climate cocoa production and 230–1 RWCS and 263–4 summary of, in cocoa ecosystem 232 CMS. See Cytoplasmic male sterile Cobalt nitrogen interactions with 369–70 Cocoa climate and 230–1 countries producing 229 factors in ecosystem of 232 leaching losses in production of 238 litter fall in ecosystems of 240 nitrogen in ecosystem of 233 nutrient addition in production of 239 nutrient balances in 242–4 nutrient concentration in 241 nutrient cycling diagram in ecosystem of 236 nutrient cycling in production of 234–42 nutrient removal in dry 237 nutrient stocks in ecosystem of 235

414

INDEX

Cocoa (cont. ) nutrient transfer in production of 239–40 potassium in ecosystem of 233–4 production of 228–9 soil changes under 244–6 soil chemical properties under 245, 247, 248–9 soil conditions and 230–1 Compaction 297 Conventional tillage (CT) 265 economics of 269 zero tillage v., in grain yields in India 268 zero tillage v., in wheat after rice 267 Copper nitrogen interactions with 368 Copper-chromium-arsenate (CCA) 11 Corn Belt Dent 87 Coronary heart disease 151 4-coumarate:coenzyme A ligase (4CL) 157 Coumestrols 160 CRC gene 171–2 under oleosin promoter 176 overexpression of 173 phenotypes from soybeans transformed by 172 CRI. See Crown root initiation Critical growth stages 298 Crop diversification 303 Crop residue management eVect of, on soil fertility 271 in RWCS 270–1, 319 Crown root initiation (CRI) 300 CT. See Conventional tillage Cultural practices maize yields and 85–6 CYP93 family 164 Cytochrome P450 160 Cytoplasmic male sterile (CMS) 306

D Daidzein 149 attributes of 155 precursors to 173 Deep ploughing 39 Delayed dew period biological weed control and 204–5 Demethylation

of methylarsenicals 26–7 Dew period biological weed control and 203–4 disease development and 206 Dew temperature biological weed control and 205–6 disease development and 206 DFR. See Dihydroflavonol reductase 7,20 -dihydroxy- 40 -methyloxyisoflavanol dehydratase (DMID) 160 Dihydroflavonol reductase (DFR) 158 Dihydrofuran ring 160 Dimethylarsine 46 Disease resistance biotechnology and 134 dew period and 206 dew temperature and 206 genistein in soybean 160 humidity and 205 in hybrids 107–8 DM. See Dry matter DMA 29 DMID. See 7,20 -dihydroxy-40 methyloxyisoflavanol dehydratase Drainage systems for RWCS 302 Drought hybrid resistance to 99–101 Dry matter (DM) 231 Dryland environments nitrogen
water interactions in 371–3

E Early duration in RWCS 307–9 Encapsulation methods 217

F F3H. See Flavanone 3-hydroxylase F6H. See Flavanone 6-hydroxylase Factor productivity in RWCS 313–15 trends in, in RWCS 315 Farmer breeding maize yields and 86–8

INDEX FeOOH. See Iron Oxyhydroxides Ferrous salt 42 Fertilizers 11–12 applied 385–9 in carbon storage 391 consumption of 383–9 countries consuming 387 N, P, and K 384, 385 synthetic nitrogen 85 Feruloyl esters 170 Filtration of arsenic 52–3 FIRB. See Furrow irrigated raised bed Flavanone 3-hydroxylase (F3H) 157, 174 Flavanone 6-hydroxylase (F6H) 159 FNSII. See Maize flavone synthase Foliar application formulation for 213–15 Food demand global population and 255–7 in India 256 Food security RWCS and 262–3 4CL. See 4-coumarate:coenzyme A ligase Fungal strains 198 Furanocoumarin 160 Furrow irrigated raised bed (FIRB) 268

G Gastrointestinal test 15 Genetic diversity of hybrids 113–14 Genetic manipulation in RWCS 305–20 Genetic yield gains in Argentina 90 in Brazil 90 changes accompanying, in hybrids 92–121 in future 131–3 from population improvement 121–6 population improvement v. hybrids 121–4 possible reasons for 126–31 predictions regarding 132–8 previously reported 89–90 in United States 91 Genistein 149 attributes of 155 in disease resistance 160 Glabrous1 170

415

Global population food demand and 255–7 Glyceollins 153 Glycitein 149 Glyphosate eVect of, on wheat yields 304 GM. See Green manuring Grain protein percentage 96 Grain quality in RWCS 310–11 Grain starch percentage 96 Grain yields CT v. ZT in India 268 declining, in RWCS 312–13 eVect of Sulfur on RWCS 284 genetic gains in 89–121 growth of, in RWCS states 313, 314 growth stages of wheat and 300 heterosis for 115 integrated nutrient management and, of rice and wheat 291 irrigation and rice 298 mean, of hybrids 105 of OPCs 101 per hybrid 99, 110 previously reported gains in 89–90 in RWCS from diVerent durations 308 trait changes increasing 127 trait stabilities and 129 of wheat aVected by tillage 267 Grain-filling period 95 Granular formations 216 Grasses N
S interactions in 363–5 Green leaf hopper 309 Green manuring (GM) in RWCS 292 Growth stages wheat grain yields and 300 Gujhia weevils 309

H H2PO4-uptake mechanisms 49 Harvest Index (HI) 96–7 increasing 130–1 HDL. See High-density lipoproteins Herbicides 11–12 in RWCS 303–4 tolerance of, in hybrids 110–12

416

INDEX

Heterosis absolute 115–16 absolute v. relative 116 for grain yield 115 for other traits 120–1 plant density and changes in 119 relative 119–20 in two seasons 118 HI. See Harvest Index High temperatures resistance to, in hybrids 98 High-density lipoproteins (HDL) 151 High-yielding varieties (HYV) 258 micronutrients in 286 RWCS and 305–7 HPLC 175 Human health references on eVects of arsenic on 36, 37 Humic acids 24 Humidity disease development and 205 Hybrids abiotic stress tolerance in 98–106 anthesis in 94 ASI in 94–5 biotic stress tolerance of 106–8 canopy gas exchange of 112–13 disease resistance of 107–8 drought resistance in 99–101 ears per plant in 95 genetic diversity of 113–14 genetic yield gains and changes in 92–121 grain protein percentage in 96 grain starch percentage in 96 grain yields per 99 grain-filling period in 95 Harvest Index (HI) of 96–7 herbicide tolerance in 110–12 inbreds v. 115–21 insect tolerance of 106–7 kernal weight in 96 leaf angle in 92–3 leaf number in 93 leaf rolling in 93–4 maize yields and 88 mean grain yields of 105 molecular markers in 114–15 nitrogen deficiency resistance in 102–3 photosynthesis in 112 plant and ear height in 92

plant density and 108–10 population improvement and 121–4 recurrent selection v. 123–4 root lodging resistance in 97 silk emergence in 94 soil moisture resistance of 102 stalk lodging resistance in 97–8 staygreen in 94 tassel size in 93 temperature resistance in 98–9 tillers in 94 unspecified abiotic stress resistance in 103–6 Hydrolyzation 274 Hydrophilic polymers 214 Hyperaccumulators 48–9 Hyperkeratosis 35 at various stages 37 HYV. See High-yielding varieties

I IFR. See Isoflavone reductase IFS. See Isoflavone synthase Immobilization of arsenic 41 Inbred performance hybrid performance and 115–21 India CT v. ZT in grain yields in 268 food demand in 256 wheat and rice yields under various conditions in 295 Indo-Gangetic Plains climate and soil in 263 contribution of RWCS in 262 estimated RWCS area in 261 RWCS belt of 260 Insects biotechnology and 134 hybrid tolerance to 106–7 in RWCS 319–20 Integrated nutrient management grain yield of rice and wheat and 291 in RWCS 289–93 Invert emulsions 214 IOMT. See Isoflavone O-methyltransferase Iron nitrogen interactions with 369–70 in RWCS 289

INDEX Iron Oxyhydroxides (FeOOH) dissolution of 10 Irrigation nitrogen
water interactions and 373–7 rice grain yields eVected by 298 in RWCS 293–301 timing of 301 Isoflavone biosynthesis CHI in 165–6 CHR in 166–8 outline of 158 pathway to 157–61 Isoflavone engineering advantages of 156 in legumes 171–4 metabolic channeling and 177–80 in nonlegumes 174–7 targets of 155–7 Isoflavone O-methyltransferase (IOMT) 159 Isoflavone reductase (IFR) 159 Isoflavone synthase (IFS) 159, 175 cloned genes 163 discovery of 161–2 mode of action of 162–5 under oleosin promoter 176 promoters of 170 reaction scheme outline 164 Isoflavones antimicrobial eVects of 153 cancer and 151 common, in legumes 150 coronary heart disease and 151 defined 148–9 health benefits of 151–2 lipoproteins and 151 neurobehavioral activities and 151 physiological function of 150 structure of 149 transcriptional regulation of related pathways 168–71 Isoflavonoids biological function of, in plants 153–4 phytoalexins of 160 Isoliquiritigenin 173 Isoproturon eVect of, on wheat yields 304

417 K

K. See Potassium Kamal bunt 309 Kernal weight 96 Kivetone 160 K/N ratios 385, 386 Ku-like transcription factor 169

L Lactose intolerance 152–3 Law of the minimum 343 LDL. See Low-density lipoproteins LDOX. See Leucoanthocyanidin dioxygenase Leaching of Arsenic 27 nutrient removal from 234–5 Leaf angle 92–3 Leaf blight 309 Leaf number 93 Leaf rolling 93–4 Legumes common isoflavones in 150 engineering isoflavone accumulation in 171–4 N
P interactions in 348–50 N
S interactions in 359–62 rhizobia and 154 Less favorable environments (LFE) 264 yields in India under 295 Leucoanthocyanidin dioxygenase (LDOX) 158 LFE. See Less favorable environments Light biological weed control and 207–8 Liming 42 Linolenic acid synthesis of 361 Linseed oil linolenic acid synthesis in 361 Liquiritigenin 164, 173 Litter fall in cocoa ecosystems 240 Loose smut 309 Low temperatures resistance to, in hybrids 98–9 Low-density lipoproteins (LDL) 151 Lysimeter studies 236–7 Lysine 160–1

418

INDEX M

Macromolecular complexes in phenylpropanoid pathway 179 Maize flavone synthase (FNSII) 158 Maize yields Black Mexican Sweet 176 cultural practices and 85–6 farmer breeding and 86–8 future markets for 133 hybrids and 88 improved populations and 88–9 trends in, during last century 84–5 trends in selected regions 85 in United States 87 Manganese nitrogen interactions with 368 in RWCS 289 MAP. See Monoammonium phosphate MCP. See Monocalcium phosphate Metabolic channeling isoflavone engineering and 179–80 Metabolons 177 Methylarsenicals demethylation of 26–7 Methylation of arsenic 45 Microbial community arsenic and 33–4 Microbial herbicide granules 216–17 Microbial redox reactions 45 for removal of arsenic in aquatic environments 58–9 Micronutrients. See also Nitrogen
micronutrients interactions removal of 287 in RWCS 286–9, 317 soil deficient in 287 threshold values of 288 Mites 309 MMA 29 Mobilization references on, of arsenic 51 Moisture biological weed control and 202–3 Molecular markers of hybrids 114–15 Molybdenum nitrogen interactions with 369–70 Monoammonium phosphate (MAP) 51, 278 Monocalcium phosphate (MCP) 51

MP. See Parent means Multiscalar-integrated risk management of arsenic 59–62 Mungbean residue incorporation (RI) in RWCS 292 Mustard seed N
S interactions and 360 Myb-like proteins 169

N N. See Nitrogen N
C interactions. See Nitrogen
calcium interactions N
K interactions. See Nitrogen
potassium interactions N
MG interactions. See Nitrogen
magnesium interactions N
P interactions. See Nitrogen
phosphorous interactions 389–390 N
S interactions. See Nitrogen
sulfur interactions Naringenin 164, 174, 175 Neurobehavioral activities isoflavones and 151 Nitrogen (N) boron interactions with 369–70 carbon storage and 377–83 cobalt interactions with 369–70 in cocoa ecosystem 233 copper interactions with 368 future research needs 389–94 historical use of 342 interactions with 390 iron interactions with 369–70 losses of 248, 383–9 low recovery of 273–4 manganese interactions with 368 molybdenum interactions with 369–70 in RWCS 273–5 use eYciency of 274–5 use eYciency of, in RWCS 348 zinc interactions with 366–8 Nitrogen deficiency hybrid resistance to 102–3 Nitrogen use eYciency (NUE) 342 management of 391 in N
P interactions 345

INDEX nitrogen losses and 383–4 in wheat 376 Nitrogen
calcium interactions (N
C interactions) 365–6, 390 Nitrogen
magnesium interactions (N
MG interactions) 365–6, 390 Nitrogen
micronutrients interactions 366–370 Nitrogen
phosphorous interactions (N
P interactions) 389–90 in cereals and millets 345–8 defined 344 eVects of, on nitrogenase activity 349 influence of, on rice yields 353 in nonlegume oilseeds 350–2 NUE in 345 in sorghum 346 in sunflowers 350 Nitrogen
potassium interactions (N
K interactions) 389–90 in cereals 352–5 influence of, on rice yields 353 in plantation crops 356–8 in rice 354 Nitrogen
sulfur interactions (N
S interactions) 358–359, 390 in cereals and plantation crops 362–3 in grasses and perennials 363–5 influence of, on mustard seed 360 influence of, on rapeseed 360 in oilseeds and pulses 359–62 Nitrogen
water interactions 370–1 in dryland environments 371–3 irrigated environments and 373–7 wheat and 375 Nitrogenase activity N
P interaction and 349 Nod factors 154 NUE. See Nitrogen use eYciency Nutrient addition in cocoa production 239 Nutrient balances in cocoa production 242–4 transfer and 243 Nutrient concentration in cocoa ecosystem 241 Nutrient cycling in cocoa ecosystem 234–42 nutrient addition in 239

419

simplified diagram for, in cocoa ecosystem 236 Nutrient management in RWCS 272, 316 Nutrient recycling 228 Nutrient removal by dry cocoa beans 237 leaching 234–5 losses from leaching 238 soil erosion 238–9 yield 234 Nutrient stocks 246 in cocoa ecosystem 231–4, 235 Nutrient transfer 248 in cocoa production 239–40 nutrient balance and 243

O Oilseeds N
P interaction in 350–2 N
S interaction in 359–62 Oleosin promoter 176 OPCs. See Open pollinated cultivators Open pollinated cultivators (OPCs) 86–7, 88 grain yields of 101 yield response of 104 Oxide surfaces 23 Oxisols 230

P PAL. See Phenylalanine ammonia-lyase Parent means (MP) yields of 117 Partial factor productivity (PFF) 313 in RWCS 315 PBET. See Physiologically based extraction test Pedigree breeding population improvement v. 124–5 Pesticides 11–12 PFF. See Partial factor productivity pH arsenic adsorption and 23 Phenylalanine 157 Phenylalanine ammonia-lyase (PAL) 157, 170, 171

420 Phenylpropanoid pathway 156 macromolecular complexes in 179 outline of 158 promoters of 169 structural models for 178 transcriptional regulation of 168 Phlobaphenes 158 Phosphate compounds arsenic mobilization and 51 Phosphate solubilizing organisms (PSO) 293 Phosphorous (P) in RWCS 276–9 soil test value for 277 use eYciency of, in RWCS 348 Photosynthesis in hybrids 112 Physical environment biological weed control and 200–8 Physicochemical methods of removing arsenic from aquatic environments 52–6 Physiologically based extraction test (PBET) 15 Phytoalexins 153 isoflavanoid 160 Phytoextraction 48 Phytoremediation of arsenic with aquatic plants 56–8 conceptual integrated approach for 62 selected references on 50 of soil 46–52 Phytostabilization 46 Plant and ear height 92 Plant breeding maize yields and 86–9 Plant density 86 decadal changes in absolute heterosis and 119 hybrid response to changes in 108–10 Plantation crops N
K interactions in 356–8 N
S interactions in 362–3 Plant-microbe interactions 156 P/N ratios 385, 386 Polyvinyl alcohol (PVA) 215 Polyvinylpyrrolidine (PVP) 215 Population improvement genetic gains from 121–6

INDEX hybrids and 121–4 pedigree breeding v. 124–6 Populations maize yields and 88–9 Postmenopausal symptoms isoflavones and 151 Potassium (K). See also Nitrogen
phosphorous interactions application of 281–2 balance of, in RWCS 280 in cocoa ecosystem 233–4 rice response to 280 in RWCS 279–82 wheat response to 280 Precipitation of arsenic, in aquatic environments 55–6 Psammentic entisol 230 PSO. See Phosphate solubilizing organisms Pterocarpans 160 in soybeans 159–60 Puddling 296–7 eVects of, on rice 297 PVA. See Polyvinyl alcohol PVP. See Polyvinylpyrrolidine

Q QTL. See Quantitative trait locus Quantitative trait locus (QTL) 155

R Rapeseed N
S interactions and 360 Recurrent selection hybrid breeding v. 123–4 Redox reactions of arsenic 25–6 Rhizobia legumes and 154 RI. See Mungbean residue incorporation Rice consumption of 321 CT v. ZT in, before wheat 267 diseases of 309 eVects of puddling on 297

INDEX grain quality characters in 310 growth of yields in, under RWCS 313, 314 integrated nutrient management and grain yield of 291 irrigation practices and grain yield of 298 micronutrient threshold values in 288 N
K interactions in 354 N
P
K interactions in 353, 355 phosphorous and 277 potassium and 280, 281 quality of 310 residue management of 271 soil management practices for 296–9 yields of, under various conditions in India 295 Rice aphid 309 Rice gall midge 309 Rice gundhi bug 309 Rice leaf folder 309 Rice mealy bug 309 Rice swarming caterpillar 309 Rice-rice cropping system sulfur and 285 Rice-wheat cropping systems (RWCS) 257–62 annual growth rates in 313, 314 arable land in 294 balanced NPK fertilization in 282–3 boron in 289 breeding for soil problems in 311 in China 257, 261 climate and 263–4 contribution of, in Indo-Gangetic Plains 262 crop calendar for, in China 259 crop growth in 258 crop residue management in 319 declining yields in 312–13 disease resistance in 309 drainage systems for 302 early duration in 307–9 eVect of sulfur on grain yield of 284 estimated area under, in Indo-Gangetic Plains 261 factor productivity in 313–15 food security and 262–3 future research needs in 321–3 genetic manipulation and 305–20 grain quality in 310–11

421

grain yields from diVerent durations in 308 green manuring in 292 herbicides in 303–4 high yielding abilities and 305–7 history of 257 in Indo-Gangetic Plains 260 insect resistance in 309 integrated nutrient management in 289–93 iron in 289 irrigation and water management in 293–301 manganese in 289 micronutrients in 286–9, 317 mungbean residue incorporation in 292 N and P use eYciency in 348 nitrogen in 273–5 nutrient management and 272, 316 partial factor productivity in 315 pest problems in 319–20 phosphorous in 276–9 potassium in 279–82 potassium in balance under 280 rice tillage in 264–5 socioeconomic and policy factors regarding 320–1 soil and 263–4 soil chemical properties in 315–18 soil physical properties in 318–19 sulfur in 283–6 sustainability of 311–20 water balance in 296 weed management in 301–4 zinc in 288–9 Root lodging resistance to, in hybrids 97 RWCS. See Rice-wheat cropping systems

S S. See Sulfur Safety net theory 236 Seeding of rice 264–5 of wheat 265–70 Shade tree summary of, in cocoa ecosystem 232 Silicate clay minerals 24 Silk emergence 94

422 Simple oil emulsions 213 Simple sequence repeats (SSR) 114 Single crosses (SX) 117 Single super phosphates (SSP) 278 Soil binding into solid mass 40 biochemistry of Arsenic in 19–26 biological remediation of arseniccontaminated 44–52 biological weed control and 208–11 bioremediation of 44–6 chemical properties of, in cocoa 245, 247, 248–9 chemical remediation of arsenic-contaminated 40–3 cocoa production and 230–1 dynamics of Arsenic in 20 eVects of arsenic-reducing treatments for 43 eVects of tillage on 269 micronutrients in 287 nutrient stocks of 231–4 physical remediation of arsenic-contaminated 38–40 phytoremediation of 46–52 RWCS and 263–4 summary of, in cocoa ecosystem 232 Soil additives 41–2 Soil application formulation for 215–17 Soil changes under cocoa 244–6 Soil erosion nutrient removal from 238–9 Soil fertility crop residue management and 271 Soil management for rice 296–9 of wheat 299–301 Soil microorganisms biological weed control and 210–11 Soil moisture hybrid resistance to 102 Soil nutrients biological weed control and 208–9 Soil reaction biological weed control and 210 Soil test value phosphorus and 277 sulfur and 285

INDEX Soil washing 39 Sorghum N
P interactions in 346 Soybeans CRC-transformed 172 genistein in disease resistance of 160 growth of, as product 148 health benefits of 148 history of 148 pterocarpans in 159–60 SSP. See Single super phosphates SSR. See Simple sequence repeats Stalk lodging resistance to, in hybrids 97–8 Staygreen 94 Stilbene synthase 156 Submergence 298 Sulfur (S). See also Nitrogen
sulfur interactions rice-rice cropping system and 285 in RWCS 283–6 RWCS grain yield and 284 soil test value and 285 Sunflowers N
P interactions in 350 Surface compexation of arsenic 20–5 SX. See Single crosses Synthetic nitrogen fertilizers 85

T Tassel size 93 Taupo volcanic zone (TVZ) 56 mean arsenic concentrations in 58 Temperate regions carbon storage in 377–80 Temperature biological weed control and 201–2 Teratogenic eVects of arsenic 35 Termites 309 Terrestrial biota potential risks of arsenic to 31, 32 Test crosses 124 Tillage eVects of, on soil properties 269 planting dates and 266 of rice 264–5

INDEX of wheat 265–70 wheat grain yields and 267 Tillers 94 Tolerance trait changes increasing 127 Total yield gains breeding and 91–2 Trait stabilities intended 129 unintended 129–30 Transgenic tobacco 175 Transplanting of rice 264–5 of wheat 265–70 Trimethylarsine 46 Tropical regions carbon storage in 380–3 TTG1 170 TVZ. See Taupo volcanic zone

U UDPG-flavonoid glucosyl transferase (UFGT) 158 UFGT. See UDPG-flavonoid glucosyl transferase Ultisols 230 United States genetic yield gains in 91 maize yields in 87

V Varietal hybrids 87 Vegetables N
K interactions in 356–8 N
S interactions in 362–3 Vestitone reductase (VTR) 160 Virulence 219 in biotic environment 197 Volcanoes 10–11 VTR. See Vestitone reductase

W WA. See Wild abortive Water-oil-water (WOW) emulsion 214 WBPH. See White-backed plant hopper

423

WD40 170 Weed growth stage in biotic environment 198–9 Weed management biological control 193 cultural practices of 302–3 history of 192 in RWCS 301–4 Wheat Chinese yields of 266 consumption of 321 CT v. ZT in, after rice 267 CT v. ZT in, in India 268 diseases of 309 glyphosate and 304 grain yields of, aVected by tillage 267 growth of yields in, under RWCS 313, 314 growth stages of, and grain yields 300 integrated nutrient management and grain yield of 291 isoproturon and 304 micronutrient threshold values in 288 N
P
K interactions in 355 nitrogen
water interactions and 375 NUE in 376 phosphorous and 277 planting dates and tillage options 266 potassium and 280 quality of 310–11 residue management of 271 soil management of 299–301 tillage of 265–70 yields of, under various conditions in India 295 White-backed plant hopper (WBPH) 309 WHO. See World Health Organization Wild abortive (WA) 306 Wind biological weed control and 207 World Health Organization (WHO) 14 Wound inoculation 212

424

INDEX

WOW emulsion. See Water-oil-water emulsion WRKY transcription factors 170

X X-ray absorption spectroscopy 48

Y Yield response of OPCs 104

Z Zero tillage (ZT) 265 advantages of 269–70 conventional tillage v., in grain yields in India 268 conventional tillage v., in wheat after rice 267 economics of 269 Zinc nitrogen interactions with 366–68 in RWCS 288–9 ZT. See Zero tillage

Contents CONTRIBUTORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xi xiii

ARSENIC CONTAMINATION AND ITS RISK MANAGEMENT IN COMPLEX ENVIRONMENTAL SETTINGS S. Mahimairaja, N. S. Bolan, D. C. Adriano and B. Robinson I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Origin and Sources of Arsenic Contamination . . . . . . . . . . . . . . . . . . A. Geogenic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Anthropogenic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Biogenic Redistribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Distribution and Speciation of Arsenic in the Environment. . . . . . . . A. Distribution in Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Distribution in the Aquatic Environment . . . . . . . . . . . . . . . . . . . C. Chemical Form and Speciation. . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Biogeochemistry of Arsenic in the Environment . . . . . . . . . . . . . . . . A. Biogeochemistry of Arsenic in the Soil . . . . . . . . . . . . . . . . . . . . . B. Biogeochemistry of Arsenic in Aquatic Environments . . . . . . . . . V. Bioavailability and Toxicity of Arsenic to Biota . . . . . . . . . . . . . . . . A. Toxicity to Plants and Microorganisms . . . . . . . . . . . . . . . . . . . . B. Risk to Animals and Humans . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Risk Management of Arsenic in Contaminated Environments. . . . . . A. Remediation of Arsenic-Contaminated Soil . . . . . . . . . . . . . . . . . B. Removal of Arsenic from Aquatic Environments . . . . . . . . . . . . . C. Multiscalar-Integrated Risk Management . . . . . . . . . . . . . . . . . . . VII. Summary and Future Research Needs . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2 4 5 11 12 13 13 14 15 19 19 27 30 30 34 38 38 52 59 62 64 64

THE CONTRIBUTION OF BREEDING TO YIELD ADVANCES IN MAIZE (ZEA MAYS L.) Donald N. Duvick I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Maize Yield Trends During the Past Century. . . . . . . . . . . . . . . . B. Factors Responsible for Upward Yield Trends. . . . . . . . . . . . . . . v

84 84 85

vi

CONTENTS

II. Genetic Gains in Grain Yield of Hybrids . . . . . . . . . . . . . . . . . . . . . A. Previously Reported Genetic Yield Gains. . . . . . . . . . . . . . . . . . . B. Recent Estimates of Genetic Yield Gains . . . . . . . . . . . . . . . . . . . C. Estimates of the Contribution of Breeding to Total Yield Gains. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Changes that Have Accompanied Genetic Yield Gains in Hybrids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Genetic Gains from Population Improvement . . . . . . . . . . . . . . . . . . A. Comparisons with Genetic Gains in Hybrids . . . . . . . . . . . . . . . . B. Relative Contributions of Population Improvement and Pedigree Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Analysis and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Possible Reasons for Genetic Yield Gains . . . . . . . . . . . . . . . . . . B. Potential Helps or Hindrances to Future Gains in Yield . . . . . . . C. Predictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

89 89 90 91 92 121 121 124 126 126 131 132 138

METABOLIC ENGINEERING OF ISOFLAVONE BIOSYNTHESIS Oliver Yu and Brian McGonigle I. II. III. IV. V.

VI.

VII. VIII. IX. X. XI.

The Health Benefits of Isoflavones in Soybeans . . . . . . . . . . . . . . . . . Biological Functions of Isoflavonoids in Plants . . . . . . . . . . . . . . . . . Targets of Isoflavone Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . The Pathway Leading to Isoflavone Biosynthesis. . . . . . . . . . . . . . . . The Entry Point Enzyme: Isoflavone Synthase. . . . . . . . . . . . . . . . . . A. The Discovery of Isoflavone Synthase . . . . . . . . . . . . . . . . . . . . . B. The Mode of Action of Isoflavone Synthase . . . . . . . . . . . . . . . . Other Key Enzymes in Isoflavone Biosynthesis . . . . . . . . . . . . . . . . . A. Chalcone Isomerase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Chalcone Reductase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Transcriptional and Posttranscriptional Regulation of Related Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Metabolic Engineering of Isoflavone Accumulation in Legumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Metabolic Engineering of Isoflavone Accumulation in Nonlegumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Bottleneck of Isoflavone Pathway Engineering: ‘‘Metabolic Channeling?’’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

148 153 155 157 161 161 162 165 165 166 168 171 174 177 180 181

CONTENTS

vii

BIOLOGICAL CONTROL OF WEEDS WITH ANTAGONISTIC PLANT PATHOGENS Reza Ghorbani, Carlo Leifert and Wendy Seel I. II. III. IV.

V.

VI.

VII. VIII.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biological Control of Weeds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . History of Biological Control Methods . . . . . . . . . . . . . . . . . . . . . . . Strategies of Weed Biological Control . . . . . . . . . . . . . . . . . . . . . . . . A. Classical (Inoculative) Biological Control . . . . . . . . . . . . . . . . . . . B. Bioherbicide (Inundative) Biological Control . . . . . . . . . . . . . . . . C. Conservation and Augmentation Biological Control . . . . . . . . . . Factors AVecting the EYcacy of Pathogens Used in Biological Weed Control. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Biotic Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Physical Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Soil Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Formulation of Biological Control Agents . . . . . . . . . . . . . . . . . . . . . A. Formulation for Foliar Application . . . . . . . . . . . . . . . . . . . . . . . B. Formulation for Soil Application . . . . . . . . . . . . . . . . . . . . . . . . . Limitations and Justifications of Biological Weed Control . . . . . . . . Overall Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

192 193 193 194 194 195 196 196 197 200 208 211 213 215 217 219 220

NUTRIENT STOCKS, NUTRIENT CYCLING, AND SOIL CHANGES IN COCOA ECOSYSTEMS: A REVIEW Alfred E. Hartemink I. II. III. IV.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climatic and Soil Conditions of Study Areas. . . . . . . . . . . . . . . . . . . Nutrient Stocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nutrient Cycling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Nutrient Removal: Yield . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Nutrient Removal: Leaching. . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Nutrient Removal: Soil Erosion . . . . . . . . . . . . . . . . . . . . . . . . . . D. Addition of Nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Transfer of Nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Nutrient Balances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Soil Changes Under Cocoa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

228 230 231 234 234 234 238 239 239 242 244

viii

CONTENTS

VII. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII. Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

246 249 250 250

RICE–WHEAT CROPPING SYSTEMS Rajendra Prasad I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Global Population and Food Demand . . . . . . . . . . . . . . . . . . . . . B. Rice–Wheat Cropping Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Contribution to Food Security . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Climate and Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Agronomic Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Tillage and Transplanting/Seeding . . . . . . . . . . . . . . . . . . . . . . . . B. Crop Residue Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Nutrient Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Irrigation and Water Management . . . . . . . . . . . . . . . . . . . . . . . . E. Weed Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Genetic Manipulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. High Yielding Ability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Early Duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Multiple Resistance to Diseases and Pests . . . . . . . . . . . . . . . . . . D. Grain Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Breeding for Special Soil Problems . . . . . . . . . . . . . . . . . . . . . . . . V. Sustainability of Rice–Wheat Cropping Systems . . . . . . . . . . . . . . . . A. Declining Yields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Factor Productivity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Soil Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Pest Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Socioeconomic and Policy Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Future Research Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

255 255 257 262 263 264 264 270 272 293 301 305 305 307 309 310 311 312 312 314 316 320 321 322 323 323

CONTENTS

ix

INTERACTIONS OF NITROGEN WITH OTHER NUTRIENTS AND WATER: EFFECT ON CROP YIELD AND QUALITY, NUTRIENT USE EFFICIENCY, CARBON SEQUESTRATION, AND ENVIRONMENTAL POLLUTION Milkha S. Aulakh and Sukhdev S. Malhi I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Nitrogen  Phosphorus Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . A. Cereals and Millets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Legumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Nonlegume Oilseeds and Other Crops . . . . . . . . . . . . . . . . . . . . . III. Nitrogen  Potassium Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Cereals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Vegetables, Horticultural, and Plantation Crops . . . . . . . . . . . . . IV. Nitrogen  Sulfur Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Oilseeds and Pulses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Cereals, Millets, Vegetables, and Plantation Crops . . . . . . . . . . . . C. Grasses, Perennials, and Other Forage Crops. . . . . . . . . . . . . . . . V. Nitrogen  Calcium and Nitrogen  Magnesium Interactions . . . . . VI. Nitrogen  Micronutrients Interactions . . . . . . . . . . . . . . . . . . . . . . . A. Zinc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Copper and Manganese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Iron, Boron, Cobalt, and Molybdenum . . . . . . . . . . . . . . . . . . . . VII. Nitrogen  Water Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Dryland Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Fully and Partially Irrigated Environments . . . . . . . . . . . . . . . . . VIII. EVects on Carbon Storage and Sequestration in Soil . . . . . . . . . . . . . A. Temperate Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Tropical and Subtropical Regions . . . . . . . . . . . . . . . . . . . . . . . . IX. Nitrogen Losses and Trends of Fertilizer Consumption . . . . . . . . . . . A. Nitrogen Losses and Use EYciency . . . . . . . . . . . . . . . . . . . . . . . B. Global Consumption of N, P, and K Fertilizers . . . . . . . . . . . . . . C. P/N and K/N Ratios of Crops and Applied Fertilizers . . . . . . . . . X. Conclusions and Future Research Needs . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

342 344 345 348 350 352 352 356 358 359 362 363 365 366 366 368 369 370 371 373 377 377 380 383 383 384 385 389 394 394

INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

411