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ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Plant Physiology and Genetics Research » Research » Research Project #435645

Research Project: Analysis and Quantification of G x E x M Interactions for Sustainable Crop Production

Location: Plant Physiology and Genetics Research

2021 Annual Report


Accomplishments
1. Effects of elevated carbon dioxide (CO2) on global agriculture food production. Essential information is required to accurately assess the impacts of climate uncertainty on global agricultural food production. An ARS scientist and a retired ARS collaborator, from Maricopa, Arizona, in cooperation with scientists from 23 other domestic and international research centers determined that it is possible to narrow the uncertainties in CO2-induced crop responses so that climate change impact simulations omitting CO2 effects – known as the ‘without CO2-fertilization effects’ scenario – can now be conducted. This proposed approach will improve and streamline future investigations on climate uncertainty effects on global food security.

2. Improved temperature-yield response of irrigated United States wheat by normalizing for phenology and growing season length. High temperature and drought have detrimental effects on growth and phenology that result in yield reductions in agricultural crops. Nevertheless, homeostatic ranges of tolerance exist. An ARS scientist from Maricopa, Arizona, and two German scientists applied a binned temperature exposure statistical yield model on experimental and simulated data. They determined that accounting for phenological development (phenological effect), and rescaling (normalizing) the absolute seasonal length in the temperature counts to a maximum season length, resulted in more realistic yield predictions. This improved statistical modeling approach will enable more accurate assessment of climate uncertainty on global food security.

3. Energy balance routine improves popular Decision Support System for Agrotechnology Transfer (DSSAT) - Cropping System Model (CSM) - Crop Growth (CROPGRO) model. Crop growth models that simulate effects of weather, soils, and management practices on crop growth and yield are valuable tools for assisting today’s farmers in their management decisions, as well as for developing strategies to cope with future global change. However, most “grow” their crops at air temperature rather than at the crop’s vegetation temperature, which can differ from air temperature by several degrees, especially for irrigated agriculture. A retired ARS collaborator from Maricopa, Arizona, along with other researchers from Brazil and Universities of Florida, Nebraska, and Washington, improved the energy balance code in the popular DSSAT-CSM-CROPGRO model. The improved model performed well as compared against data collected for soybean at Mead, Nebraska. The improved CROPGRO model shows promise for helping to improve present and future crop management practices.

4. Late sowing date is a global warming adaptive strategy for bean production on the Mexican high plateau. On the Mexican high plateau, major crops of beans and corn are currently limited by late spring hailstorms and October frosts. A potential adaption under current climate uncertainty would be to delay planting to later in the season to avoid the spring hailstorms, while taking advantage of warmer fall temperatures. A retired ARS researcher, in collaboration with scientists from Mexico, grew beans at current and delayed sowing dates and with a rainout shelter apparatus to restrict rainfall. Also, an infrared heater system was used to simulate future global warming. Results demonstrated that the reduced water supply had little effect, whereas the warming with later planting produced substantial increases in bean yield. The delayed planting strategy shows promise for increasing bean yields in this high plateau region of Mexico.


Review Publications
Toreti, A., Deryng, D., Muller, C., Kimball, B.A., Moser, G., Boote, K., Asseng, S., Pugh, T., Vanuytrecht, E., Pleijel, H., Webber, H., Durand, J.L., Dentener, F., Ceglar, A., Wang, X., Badeck, F., Lecerf, R., Wall, G.W., Van Den Berg, M., Hoegy, P., Lopez-Lozano, R., Zampieri, M., Galmarini, S., Rosenzweig, C. 2020. Narrowing uncertainties in the effects of elevated CO2 on crops. Nature Food. 1:775-782. https://doi.org/10.1038/s43016-020-00195-4.
Wechsung, F., Ritter, M., Wall, G.W. 2021. The upper homeostatic range for the temperature-yield response of irrigated US wheat down revised from a theoretical and experimental perspective. Agricultural and Forest Meteorology. 307. Article 108478. https://doi.org/10.1016/j.agrformet.2021.108478.
Arrendondo, T., Delgado, B.J., Kimball, B., Luna, L.M., Yepez, G.E., Huber, S.E., Garcia, M.E., Garatuza, P.J. 2020. Late sowing date as an adaptive strategy for rainfed bean production under warming and reduced precipitation in the Mexican Altiplano?. Field Crops Research. 255. Article 107903. https://doi.org/10.1016/j.fcr.2020.107903.
MacQueen, A., White, J.W., Lee, R., Osorno, J., Schmutz, J., Miklas, P., Myers, J.R., McClean, P., Juenger, T. 2020. Genetic associations in four decades of multienvironment trials reveal agronomic trait evolution in common bean. Genetics. 215(1):267-284. https://doi.org/10.1534/genetics.120.303038.
Cuadra, S.V., Kimball, B.A., Boote, K.J., Suyker, A.E., Pickering, N. 2021. Energy balance in the dssat-csm-cropgro model. Agricultural and Forest Meteorology. 297. Article 108241. https://doi.org/10.1016/j.agrformet.2020.108241.