Dryland maize yield potentials and constraints: A case study in western Kansas. (26th September 2021) - Sun, Shuang
Abstract: Water‐limited environments account for half of the earth's land surface, and dryland agriculture acreage is projected to expand due to climate changes. Examining typical dryland yield potentials and yield improvement measures is crucial for developing future dryland crop production systems. This case study used crop modeling to analyze dryland maize yield potential ( YPd ), farmers' yield potential ( YPf ), and actual farm yields ( Ya ) from 1990 to 2015 in three counties in western Kansas (i.e., Thomas, Greeley, and Finney in the U.S. Great Plains region). The calibrated APSIM‐Maize model along with actual yields was used to estimate yield gaps attributed to: (a) agronomic factors ( YG 1 = YPd − YPf ) and (b) socioeconomic constraints ( YG 2 = YPf − Ya ). Observed climate conditions during maize‐growing seasons showed warming, brightening, and drying trends for all three counties in western Kansas from 1990 to 2015. Our results showed that the current actual farm yields ( Ya ) in western Kansas represented only 34%, 32%, and 28% of YPd in Thomas, Greeley, and Finney counties, respectively, indicating significant exploitable yield gaps. Agronomic factors ( YG 1 ) contributed the greatest to the yield gap in Greeley and Finney counties, whereas socioeconomic constraints ( YG 2 ) offered the greatest opportunity for improvement in Thomas county. Our analysis suggested that improving agronomic management could be a greater priority for further yield improvement in Greeley county, but selecting an appropriate hybrid was a greater priority in Finney county. Abstract : This case study used crop modeling to analyze dryland maize yield potential, farmers' yield potential, and actual farm yields from 1990 to 2015 in three counties in western Kansas (i.e., Thomas, Greeley, and Finney in the U.S. Great Plains region). The calibrated APSIM‐Maize model along with actual yields was used to estimate yield gaps attributed to the agronomic factors.