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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 #445548
Research Project: Analysis and Quantification of G x E x M Interactions for Sustainable Crop Production

Location: Plant Physiology and Genetics Research

Publications (Clicking on the reprint icon Reprint Icon will take you to the publication reprint.)

Wheat crop models underestimating drought stress in semi-arid and Mediterranean environments Reprint Icon - (Peer Reviewed Journal)
Webber, H., Cooke, D., Wang, C., Asseng, P., Martre, P., Ewert, F., Kimball, B., Hoogenboom, G., Evett, S.R., Chanzy, A., Garrigues, S., Olioso, A., Copeland, K.S., Steiner, J.L., Cammarano, D., Chen, Y., Crépeau, M., Diamantopoulos, E., Ferrise, R., Manceau, L., White, J. 2025. Wheat crop models underestimating drought stress in semi-arid and Mediterranean environments. Field Crops Research. 332. Article 110032. https://doi.org/10.1016/j.fcr.2025.110032.

Metrics of plant response to CO2 enrichment Reprint Icon - (Peer Reviewed Journal)
Allen, L.H., Kimball, B.A., Bunce, J.A., Boote, K.J., White, J.W. 2025. Metrics of plant response to CO2 enrichment. Agricultural and Forest Meteorology. 370. Article 110557. https://doi.org/10.1016/j.agrformet.2025.110557.

MONTPEL: a multi-1 component Penman-Monteith energy balance 2 model Reprint Icon - (Peer Reviewed Journal)
Albasha, R., Manceau, L., Webber, H., Chelle, M., Kimball, B., Martre, P. 2024. MONTPEL: a multi-1 component Penman-Monteith energy balance 2 model. Agricultural and Forest Meteorology. 358. Article 110221. https://doi.org/10.1016/j.agrformet.2024.110221.

Crop type mapping in smallholder agricultural settings using Sentinel-1 SAR imagery and deep learning Reprint Icon - (Book / Chapter)
Polavarapu, S., Irigireddy, I.C., Kulkarni, C.S., Lan, S., Pvnr, K., Bandaru, V. 2025. Crop type mapping in smallholder agricultural settings using Sentinel-1 SAR imagery and deep learning. Book Chapter. p. 283-297. https://doi.org/10.1201/9781003396253-13.

Evaluating the utility of weather generators in crop simulation models for in-season yield forecasting Reprint Icon - (Peer Reviewed Journal)
Nandan, R., Bandaru, V., Meduri, P., Jones, C., Lollato, R. 2024. Evaluating the utility of weather generators in crop simulation models for in-season yield forecasting. Agricultural Systems. 220. Article 104082. https://doi.org/10.1016/j.agsy.2024.104082.