Targeting management practices for rice yield gains in stress-prone environments of Myanmar

•Integrated approach using modeling was used to target best management options in rice growing ecosystems in Myanmar.•Spatial variability of rice crop climatic yield potential was quantified for Myanmar.•Changes in sowing date and to improved variety provided yield gains up to 53% above the actual yield in stress prone areas. Rice in Myanmar is grown in diverse environments, including inland dry zone and salt-affected coastal deltas. This study evaluated management options that could improve productivity and reduce risks of rice crop in stress-prone areas of the country. We selected four sites from two regions in the central dry zone (Wundwin) and the Ayeyarwady delta (Labutta, Bogale and Mawlamyinegyun). We used experimental and survey datasets on farmers’ practices and rice yields from 2012 to 2014 to run the ORYZA model to simulate the climatic yield potential (YP; yield without stress) and the attainable yield under rainfed conditions (YW; yield limited by water), saline conditions (YS; yield limited by salinity), and under conditions of current farmers’ practices (YF; yield in farmers’ practices). Simulated yield responses to different management practices showed spatial variability within and among the selected sites. YP ranged from 5.4 to 11.1 t ha−1, YW ranged from 0.5 to 7.5 t ha−1, and YF ranged from 2.2 to 4.2 t ha−1. In salt-affected areas, average YS ranged from less than 0.1 t ha-1 to 5.6 t ha−1. Yield gains with the choice of an improved variety and adjusted sowing date were estimated at up to 53% above YF. Changing the time of sowing and using improved rice varieties provided the greatest yield gains in salt-affected and drought-prone areas where YF was the least. In areas where YF was greater, the improvement of nitrogen management provided larger benefits than in areas with lower YF. We conclude that an integrated approach using remote-sensing technologies, crop modeling, and a geographic information system is valuable for targeting the best management options to close the yield gap in unfavorable rice environments in Asia.