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Preliminary crop coefficients for late planted short‐season soybean: Texas High Plains

Gary W. Marek, Steven R. Evett, Paul D. Colaizzi, David K. Brauer
Agrosystems, geosciences & environment 2021 v.4 no.2 pp. e20177
Agricultural Research Service, corn, cotton, crop coefficient, environment, evapotranspiration, germination, groundwater, heat, lysimeters, microirrigation, semiarid zones, soybeans, summer, weather, Texas
Having similar profit potential but roughly half of the water requirements of corn (Zea mays L.), cotton (Gossypium hirsutum L.) has become an attractive crop in the Southern High Plains (SHP) where groundwater levels and well capacities continue to decline. However, unpredictable and erratic precipitation often results in conditions either too wet or too dry for ideal germination. Coupled with a relatively short planting window for adequate heat unit accumulation and the threat of severe weather events, cotton crops can fail, leaving limited options for producers wanting to plant a second summer crop. One option is short‐season soybean [Glycine max (L.) Merr.]. However, limited data on crop water use (evapotranspiration, ET), crop coefficient (Kc), and yield exist for late‐planted soybean in the semiarid SHP. After unseasonably wet conditions in May 2019, a short‐season soybean variety was planted on 13 June in irrigated weighing lysimeter fields at the USDA‐ARS Conservation and Production Research Laboratory at Bushland, TX. Results showed profitable yields (4,786–4,996 kg ha–¹), and although maximum daily Kc values were not different than published values, season length was 24–29 d shorter than for soybean planted in mid‐May. Seasonal water use was less than that of archived data using earlier planting dates in 2 of 3 yr, although those studies used different varieties. Crop coefficient functions using both short and tall standardized reference ET values are presented for sprinkler and subsurface drip irrigation systems. Although these data are useful to producers in the SHP, additional data are needed to develop Kc functions that better characterize interannual variations in weather.