Source: AgriLife Today
Grain sorghum production is highly susceptible to changes in climatic conditions, more so than to different irrigation regiments a producer might implement on the crop, according to a Texas A&M AgriLife Research modeling study.
Dr. Srinivasulu Ale, an AgriLife Research geospatial hydrologist in Vernon, completed the study with Kritika Kothari, a doctoral student, and Dr. Clyde Munster, senior professor, both in the Texas A&M department of biological and agricultural engineering, College Station.
Other collaborators were Jim Bordovsky, AgriLife Research at Halfway; Dr. Dana Porter, Texas A&M AgriLife Extension Service in Lubbock; and Kelly Thorp, U.S. Department of Agriculture Arid Land Agricultural Research Center, Arizona.
Ale said efficient use of irrigation water is critical for the sustainability of agriculture in the Texas High Plains. Grain sorghum is one of the major crops grown in the region, and it is known for its drought tolerance and lower water requirement compared to other cereal crops.
The differences in grain sorghum yield and water-use efficiency were greater across climate variability classes than between irrigation scenarios, suggesting that grain sorghum production is highly susceptible to changes in climatic conditions.
The evaluated CERES-Sorghum model was then used to identify: optimum soil moisture at planting, soil moisture threshold to start irrigation, soil moisture threshold to terminate irrigation, and a deficit or excess irrigation strategy for production based on simulated sorghum yield, irrigation water-use and water-use efficiency.
The results from long-term simulations indicated weather conditions played a key role in selecting appropriate irrigation management strategies. Simulated water-use efficiency was consistently higher in cold, dry years. This indicates the most efficient use of applied irrigation water was achieved under conditions associated with less evapotranspiration and smaller amounts of excess water.
Ale said the recommendations on irrigation management made in this study were based on the magnitude and distribution of seasonal rainfall and temperature during the simulation period. The effects of days with extreme hot or cold temperatures were not investigated.
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