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United States Department of Agriculture

Agricultural Research Service

Title: Gpfarm Plant Model Parameters: Complications of Varieties and the Genotype X Environment Interaction in Wheat

Authors
item MCMASTER, GREGORY
item ASCOUGH, JAMES
item Shaffer, Marvin
item Deer Ascough, Lois
item Byrne, Pat - CSU-FORT COLLINS
item NIELSEN, DAVID
item Haley, Scott - CSU-FORT COLLINS
item Andales, Allan - VISITING SCIENTIST ARS
item Dunn, Gale

Submitted to: Transactions of the ASAE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 1, 2003
Publication Date: December 1, 2003
Citation: MCMASTER, G.S., ASCOUGH II, J.C., SHAFFER, M.J., DEER ASCOUGH, L.A., BYRNE, P.F., NIELSEN, D.C., HALEY, S.D., ANDALES, A.A., DUNN, G.H. GPFARM PLANT MODEL PARAMETERS: COMPLICATIONS OF VARIETIES AND THE GENOTYPE X ENVIRONMENT INTERACTION IN WHEAT. TRANSACTIONS OF THE AMERICAN SOCIETY OF AGRICULTURAL ENGINEERS. 2003.

Interpretive Summary: The USDA-ARS Great Plains Framework for Agricultural Resource Management (GPFARM) decision support system was developed to assist Great Plains producers in strategic planning for whole farm and ranch systems so that they are economically viable and environmentally sound. A major user requirement for GPFARM is to supply the default plant parameters required to simulate crop growth. Developing this plant parameter database is difficult because of varietal differences, uncertainty in the variability of most parameters, and the genotype by environment interaction (G x E). This paper examines different sets of plant parameters for simulating winter wheat (Triticum aestivum L.) yield responses, explores the significance of the G x E interaction on simulating varietal grain yield, and investigates whether simple adjustments to a species-based plant parameter database can improve the simulation of varietal differences. Simulating yield had mixed results depending on the location. Varietal yield response to environmental conditions (irrigated or dryland) was not always adequately simulated due to the diverse G x E interactions. Making simple adjustments to a few critical plant parameters based on whether dryland or irrigated conditions were simulated improved the species-based plant parameter approach used in GPFARM. However, until a better mechanistic representation of the G x E interaction is incorporated into existing plant growth models, opportunities for improving yield responses to environmental conditions and management will be limited.

Technical Abstract: The USDA-ARS Great Plains Framework for Agricultural Resource Management (GPFARM) decision support system was developed to assist Great Plains producers in strategic planning for whole farm and ranch systems so that they are economically viable and environmentally sound. A major user requirement for GPFARM is to supply the default plant parameters required to simulate crop growth. Developing this plant parameter database is difficult because of varietal differences, uncertainty in the variability of most parameters, and the genotype by environment interaction (G x E). This paper examines three species-based sets of plant parameters for simulating winter wheat (Triticum aestivum L.) yield responses, explores the significance of the G x E interaction on simulating varietal grain yield, and investigates whether simple adjustments to a species-based plant parameter database can improve the simulation of varietal differences. Three plant parameter sets were evaluated against observed yield data for six locations in eastern Colorado: 1) the default parameter set used best estimates from plant parameter databases provided by the EPIC, ALMANAC, WEPP, and SWAT models; 2) the Dryland Agroecosystems Project (DAP) parameter set further calibrated a few critical plant parameters influencing yield in the default parameter set against observed yield data for Colorado; and 3) the theoretical parameter set modified critical DAP parameters based on whether irrigated or dryland conditions were simulated. Simulating yield when pooling all varieties using any of the plant parameter sets had mixed results depending on the location, with the theoretical parameter set providing the most accurate yield simulations. Varietal yield response to environmental conditions (irrigated or dryland) was not always adequately simulated due to the diverse G x E interactions. The theoretical parameter set best simulated the wheat variety TAM 107 across locations, with little bias for either irrigated or dryland conditions. Making simple adjustments to a few critical plant parameters based on whether dryland or irrigated conditions were simulated improved the species-based plant parameter approach used in GPFARM. However, until a better mechanistic representation of the G x E interaction is incorporated into existing plant growth models, opportunities for improving yield responses to environmental conditions and management will be limited.

Last Modified: 9/10/2014