Scientists propose new crop sequencing strategies to adapt to variable climate
Around the world, extreme climatic conditions are forcing farmers to rethink current cropping system strategies. To maximize crop production in the face of variable temperatures and precipitation, scientists say farmers may want to adopt a system in which crop sequencing decisions are based upon weather patterns and management goals each year. However, before making the change to a more adaptable cropping systems strategy, researchers say it's important to understand how short-term crop sequencing decisions affect key agronomic and environmental attributes.
From 2002-2005, a team of researchers at the USDA-ARS Northern Great Plains Research Laboratory in Mandan, North Dakota, investigated crop sequencing effects of 10 crops in a region known for its variable climate. The researchers report their findings as a series of six papers in the July-August 2007 issue of Agronomy Journal (overview and presentation).
The motivation for the research are the multiple challenges faced by global agriculture in the future:
energy :: biomass :: bioenergy :: biofuels :: agriculture :: agronomy :: crop sequence :: crop rotation :: sustainability ::
Crop sequence effects on diseases
Crop sequence is an important management practice that may lower the risk for leaf spot diseases of spring wheat. Field research was conducted near Mandan, to determine the impact of crop sequences on leaf spot diseases of hard red spring wheat early in the growing season. Spring wheat was evaluated for disease severity following crop sequence combinations of 10 crops: buckwheat, canola, chickpea, corn, dry pea, grain sorghum, lentil, oil seed sunflower, proso millet, and hard red spring wheat.
The frequency of isolation following alternative crops was generally lower compared with spring wheat following wheat. Leaf spot diseases on spring wheat were impacted by crop sequencing. Spring wheat following crop sequences with alternative crops for 1 or 2 yr had lower levels of disease severity compared with a continuous spring wheat treatment early in the growing season. Disease severity was apparently not related to the percentage of crop residue coverage on the soil surface associated with various crop sequence combinations. New alternative crops preceding spring wheat reduce levels of leaf spot diseases.
Crop residue coverage of soils in no-till systems
Field research was conducted to determine the influence of crop and crop sequencing on crop residue coverage of soil with 10 crops: buckwheat, canola, chickpea, corn, dry pea, grain sorghum, lentil, oil seed sunflower, proso millet, and hard red spring wheat. Crop residue coverage of the soil surface was measured with a transect technique at the time of seeding spring wheat.
Crop residue coverage varied and was more clearly associated with the second-year crop than with the first-year crop of a 2-yr crop sequence. Crop sequences composed of spring wheat, proso millet, and grain sorghum had higher crop residue coverage compared with sequences composed of the other crops. When these three crops and three crops that provide lower crop residue coverage of soil the subsequent year (lentil, chickpea, and sunflower) were analyzed as a subset to compare various sequences of crops providing a range of residue coverage, for example, lower (first yr)/lower (second yr), the surface residue coverage ranged from 65% for the lower/lower combination to 93% for the higher/higher combination in 2004 and from 56 to 94% in 2005, respectively.
A producer operating on more fragile soil and concerned about reducing soil erosion hazards would be advised to grow crops that provide higher residue coverage in the year before crops that provide lower residue coverage.
Soil water depletion and recharge under dynamic cropping systems
Dynamic cropping systems principles require that farmers consider climatic, market, and ecological factors on an annual basis in making crop choices. Objectives of this research were to determine variability of seasonal soil water depletion (SWD) and spring soil water recharge (SWR) among crops and to apply results to dynamic cropping systems practice.
A 10-species crop sequence project was conducted under no-tillage on silt loam Haplustoll soils in North Dakota. Mid-May to mid-September SWD and following April SWR were determined from 2002 to 2005 by neutron moisture meter to the 1.8-m depth.
Crops studied and average SWD amounts (centimeters) were: sunflower, 13.5; corn, 12.6; sorghum, 11.0; spring wheat, 10.6; canola, 10.0; millet, 9.6; buckwheat, 9.4; chickpea , 8.5; lentil, 8.1; and dry pea, 5.0, with highest and lowest being 29 and 11% of average May soil water, 46 cm.
Because the period of the experiment was relatively dry, recharge was less than depletion. Spring soil water was 10 cm greater following pea than following sunflower. Ranking of crops for water storage roughly followed reverse SWD rank, with several exceptions, notably wheat, which had greater water from snow capture. Lower soil water following crops such as sunflower and corn was linked to negative crop sequential effects in this project.
Choosing to seed a lower water-using crop in the spring after the occurrence of below-average SWR on land that had a higher water-using crop the previous season illustrates an application of information reported along with the principles of dynamic cropping systems.
Crop sequences and sustainability
Producers need to know how to sequence crops to develop sustainable dynamic cropping systems that take advantage of inherent internal resources, such as crop synergism, nutrient cycling, and soil water, and capitalize on external resources, such as weather, markets, and government programs.
The objective of this research was to determine influences of previous crop and crop residues (crop sequence) on relative seed and residue yield and precipitation-use efficiency (PUE) for the no-till production of buckwheat, canola, chickpea, corn, dry pea, grain sorghum, lentil, proso millet, sunflower, and spring wheat grown in the northern Great Plains.
Relative seed yield in 2003 for eight of the 10 crops resulted in synergistic effects when the previous crop was dry pea or lentil, compared with each crop grown on its own residue. Buckwheat, corn, and sunflower residues were antagonistic to chickpea relative seed yield. In 2004, highest relative seed yield for eight of the 10 crops occurred when dry pea was the previous crop. Relative residue yield followed a pattern similar to relative seed yield.
The PUE overall means fluctuated for seven of the 10 crops both years, but those of dry pea, sunflower, and spring wheat remained somewhat constant, suggesting these crops may have mechanisms for consistent PUE and were not as dependent on growing season precipitation distribution as the other seven crops.
Sustainable cropping systems in the northern Great Plains will approach an optimal scheme of crop sequencing by taking advantage of synergisms and avoiding antagonisms that occur among crops and previous crop residues.
These short-term research efforts can help identify crop sequence 'synergisms' and 'antagonisms' thereby providing the necessary foundation for developing strategies to sequence crops over a longer period of time, the researchers write.
The research team at the USDA-ARS Northern Great Plains Research Laboratory is now actively working to translate their research findings for use by agriculturists through an update of the Crop Sequence Calculator, an interactive computer program designed to assess crop sequencing options for optimizing economic, agronomic, and environmental goals within dryland cropping systems.
Photo: satellite image of circular crop fields and crop rotations in Haskell County, Kansas in late June 2001. Healthy, growing crops are green. Corn would be growing into leafy stalks by then. Sorghum, which resembles corn, grows more slowly and would smaller at that time and therefore, paler. Wheat is a brilliant gold as harvest occurs in June. Fields of brown have been recently harvested and plowed under or lie fallow for the year.
References:
J. D. Hansona, M. A. Liebiga, S. D. Merrilla, D. L. Tanakaa, J. M. Krupinskya and D. E. Stott, "Dynamic Cropping Systems. Increasing Adaptability Amid an Uncertain Future", Agron J, 99:939-943 (2007); DOI: 10.2134/agronj2006.0133
Joseph M. Krupinskya, Steven D. Merrilla, Donald L. Tanakaa, Mark A. Liebiga, Michael T. Laresb and Jonathan D. Hansona, "Crop Residue Coverage of Soil Influenced by Crop Sequence in a No-Till System", Agron J, 99:921-930 (2007); DOI: 10.2134/agronj2006.0129
M. A. Liebig, D. L. Tanaka, J. M. Krupinsky, S. D. Merrill and J. D. Hanson, "Dynamic Cropping Systems. Contributions to Improve Agroecosystem Sustainability", Agron J, 99:899-903 (2007); DOI: 10.2134/agronj2006.0131
Joseph M. Krupinskya, Donald L. Tanakaa, Steven D. Merrilla, Mark A. Liebiga, Michael T. Laresb and Jonathan D. Hanson, "Crop Sequence Effects on Leaf Spot Diseases of No-Till Spring Wheat", Agron J, 99:912-920 (2007); DOI: 10.2134/agronj2006.0130
Stephen D. Merrill, Donald L. Tanaka, Joseph M. Krupinsky, Mark A. Liebig and Jonathan D. Hanson, "Soil Water Depletion and Recharge under Ten Crop Species and Applications to the Principles of Dynamic Cropping Systems", Agron J, 99:931-938 (2007); DOI: 10.2134/agronj2006.0134
D. L. Tanaka, J. M. Krupinsky, S. D. Merrill, M. A. Liebig and J. D. Hanson, "Dynamic Cropping Systems for Sustainable Crop Production in the Northern Great Plains", Agron J, 99:904-911 (2007); DOI: 10.2134/agronj2006.0132
Eurekalert: Wild weather forces farmers to adapt - July 28, 2007.
From 2002-2005, a team of researchers at the USDA-ARS Northern Great Plains Research Laboratory in Mandan, North Dakota, investigated crop sequencing effects of 10 crops in a region known for its variable climate. The researchers report their findings as a series of six papers in the July-August 2007 issue of Agronomy Journal (overview and presentation).
The motivation for the research are the multiple challenges faced by global agriculture in the future:
Future trends in population growth, energy use, climate change, and globalization will challenge agriculturists to develop innovative production systems that are highly productive and environmentally sound. Furthermore, future agricultural production systems must possess an inherent capacity to adapt to change to be sustainable. Given this context, adoption of dynamic cropping systems is proposed to meet multiple agronomic and environmental objectives through the enhancement of management adaptability to externalities.Because crop performance is greatly influenced by the sequence in which crops are grown, USDA researchers set out to explore the short-term effects of sequencing a variety of different crops grown throughout the Great Plains.
Dynamic cropping systems are a form of agricultural production that relies on an annual strategy to optimize the outcome of (i) production, (ii) economic, and (iii) resource conservation goals using ecologically-based management principles. Dynamic cropping systems are inherently complex, possessing larger crop portfolios and greater crop diversity and sequencing flexibility as compared with monoculture and fixed-sequence cropping systems. Greater crop diversity and sequencing flexibility within dynamic cropping systems may result in reduced weed and disease infestations, greater nutrient- and precipitation-use efficiency, decreased requirements of exogenous inputs, and lower production risk.Over a three-year period, the scientists used a unique crop by crop-residue matrix design to evaluate the effects of 100 crop sequences on crop production, plant diseases, soil residue coverage, and soil water depletion. The six symposium papers presented by the USDA researchers highlight interesting findings on the following issues:
- crops and crop sequences that optimize precipitation-use efficiency for maximum productivity
- ways to decrease production risks from plant diseases in diverse cropping systems
- how to maintain an amount of crop residue under no-till to optimize agronomic benefits while minimizing negative effects
- how to most effectively sequence crops in semiarid environments while maximizing use of available soil water
- the value of understanding crop sequencing effects for achieving agroecosystem sustainability
energy :: biomass :: bioenergy :: biofuels :: agriculture :: agronomy :: crop sequence :: crop rotation :: sustainability ::
Crop sequence effects on diseases
Crop sequence is an important management practice that may lower the risk for leaf spot diseases of spring wheat. Field research was conducted near Mandan, to determine the impact of crop sequences on leaf spot diseases of hard red spring wheat early in the growing season. Spring wheat was evaluated for disease severity following crop sequence combinations of 10 crops: buckwheat, canola, chickpea, corn, dry pea, grain sorghum, lentil, oil seed sunflower, proso millet, and hard red spring wheat.
The frequency of isolation following alternative crops was generally lower compared with spring wheat following wheat. Leaf spot diseases on spring wheat were impacted by crop sequencing. Spring wheat following crop sequences with alternative crops for 1 or 2 yr had lower levels of disease severity compared with a continuous spring wheat treatment early in the growing season. Disease severity was apparently not related to the percentage of crop residue coverage on the soil surface associated with various crop sequence combinations. New alternative crops preceding spring wheat reduce levels of leaf spot diseases.
Crop residue coverage of soils in no-till systems
Field research was conducted to determine the influence of crop and crop sequencing on crop residue coverage of soil with 10 crops: buckwheat, canola, chickpea, corn, dry pea, grain sorghum, lentil, oil seed sunflower, proso millet, and hard red spring wheat. Crop residue coverage of the soil surface was measured with a transect technique at the time of seeding spring wheat.
Crop residue coverage varied and was more clearly associated with the second-year crop than with the first-year crop of a 2-yr crop sequence. Crop sequences composed of spring wheat, proso millet, and grain sorghum had higher crop residue coverage compared with sequences composed of the other crops. When these three crops and three crops that provide lower crop residue coverage of soil the subsequent year (lentil, chickpea, and sunflower) were analyzed as a subset to compare various sequences of crops providing a range of residue coverage, for example, lower (first yr)/lower (second yr), the surface residue coverage ranged from 65% for the lower/lower combination to 93% for the higher/higher combination in 2004 and from 56 to 94% in 2005, respectively.
A producer operating on more fragile soil and concerned about reducing soil erosion hazards would be advised to grow crops that provide higher residue coverage in the year before crops that provide lower residue coverage.
Soil water depletion and recharge under dynamic cropping systems
Dynamic cropping systems principles require that farmers consider climatic, market, and ecological factors on an annual basis in making crop choices. Objectives of this research were to determine variability of seasonal soil water depletion (SWD) and spring soil water recharge (SWR) among crops and to apply results to dynamic cropping systems practice.
A 10-species crop sequence project was conducted under no-tillage on silt loam Haplustoll soils in North Dakota. Mid-May to mid-September SWD and following April SWR were determined from 2002 to 2005 by neutron moisture meter to the 1.8-m depth.
Crops studied and average SWD amounts (centimeters) were: sunflower, 13.5; corn, 12.6; sorghum, 11.0; spring wheat, 10.6; canola, 10.0; millet, 9.6; buckwheat, 9.4; chickpea , 8.5; lentil, 8.1; and dry pea, 5.0, with highest and lowest being 29 and 11% of average May soil water, 46 cm.
Because the period of the experiment was relatively dry, recharge was less than depletion. Spring soil water was 10 cm greater following pea than following sunflower. Ranking of crops for water storage roughly followed reverse SWD rank, with several exceptions, notably wheat, which had greater water from snow capture. Lower soil water following crops such as sunflower and corn was linked to negative crop sequential effects in this project.
Choosing to seed a lower water-using crop in the spring after the occurrence of below-average SWR on land that had a higher water-using crop the previous season illustrates an application of information reported along with the principles of dynamic cropping systems.
Crop sequences and sustainability
Producers need to know how to sequence crops to develop sustainable dynamic cropping systems that take advantage of inherent internal resources, such as crop synergism, nutrient cycling, and soil water, and capitalize on external resources, such as weather, markets, and government programs.
The objective of this research was to determine influences of previous crop and crop residues (crop sequence) on relative seed and residue yield and precipitation-use efficiency (PUE) for the no-till production of buckwheat, canola, chickpea, corn, dry pea, grain sorghum, lentil, proso millet, sunflower, and spring wheat grown in the northern Great Plains.
Relative seed yield in 2003 for eight of the 10 crops resulted in synergistic effects when the previous crop was dry pea or lentil, compared with each crop grown on its own residue. Buckwheat, corn, and sunflower residues were antagonistic to chickpea relative seed yield. In 2004, highest relative seed yield for eight of the 10 crops occurred when dry pea was the previous crop. Relative residue yield followed a pattern similar to relative seed yield.
The PUE overall means fluctuated for seven of the 10 crops both years, but those of dry pea, sunflower, and spring wheat remained somewhat constant, suggesting these crops may have mechanisms for consistent PUE and were not as dependent on growing season precipitation distribution as the other seven crops.
Sustainable cropping systems in the northern Great Plains will approach an optimal scheme of crop sequencing by taking advantage of synergisms and avoiding antagonisms that occur among crops and previous crop residues.
These short-term research efforts can help identify crop sequence 'synergisms' and 'antagonisms' thereby providing the necessary foundation for developing strategies to sequence crops over a longer period of time, the researchers write.
The research team at the USDA-ARS Northern Great Plains Research Laboratory is now actively working to translate their research findings for use by agriculturists through an update of the Crop Sequence Calculator, an interactive computer program designed to assess crop sequencing options for optimizing economic, agronomic, and environmental goals within dryland cropping systems.
Photo: satellite image of circular crop fields and crop rotations in Haskell County, Kansas in late June 2001. Healthy, growing crops are green. Corn would be growing into leafy stalks by then. Sorghum, which resembles corn, grows more slowly and would smaller at that time and therefore, paler. Wheat is a brilliant gold as harvest occurs in June. Fields of brown have been recently harvested and plowed under or lie fallow for the year.
References:
J. D. Hansona, M. A. Liebiga, S. D. Merrilla, D. L. Tanakaa, J. M. Krupinskya and D. E. Stott, "Dynamic Cropping Systems. Increasing Adaptability Amid an Uncertain Future", Agron J, 99:939-943 (2007); DOI: 10.2134/agronj2006.0133
Joseph M. Krupinskya, Steven D. Merrilla, Donald L. Tanakaa, Mark A. Liebiga, Michael T. Laresb and Jonathan D. Hansona, "Crop Residue Coverage of Soil Influenced by Crop Sequence in a No-Till System", Agron J, 99:921-930 (2007); DOI: 10.2134/agronj2006.0129
M. A. Liebig, D. L. Tanaka, J. M. Krupinsky, S. D. Merrill and J. D. Hanson, "Dynamic Cropping Systems. Contributions to Improve Agroecosystem Sustainability", Agron J, 99:899-903 (2007); DOI: 10.2134/agronj2006.0131
Joseph M. Krupinskya, Donald L. Tanakaa, Steven D. Merrilla, Mark A. Liebiga, Michael T. Laresb and Jonathan D. Hanson, "Crop Sequence Effects on Leaf Spot Diseases of No-Till Spring Wheat", Agron J, 99:912-920 (2007); DOI: 10.2134/agronj2006.0130
Stephen D. Merrill, Donald L. Tanaka, Joseph M. Krupinsky, Mark A. Liebig and Jonathan D. Hanson, "Soil Water Depletion and Recharge under Ten Crop Species and Applications to the Principles of Dynamic Cropping Systems", Agron J, 99:931-938 (2007); DOI: 10.2134/agronj2006.0134
D. L. Tanaka, J. M. Krupinsky, S. D. Merrill, M. A. Liebig and J. D. Hanson, "Dynamic Cropping Systems for Sustainable Crop Production in the Northern Great Plains", Agron J, 99:904-911 (2007); DOI: 10.2134/agronj2006.0132
Eurekalert: Wild weather forces farmers to adapt - July 28, 2007.
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