Scientific Publication

Adoption Trend of Climate-Resilient Rice Varieties in Bangladesh

Abstract

Rice is a major crop in Bangladesh that supports both food security and livelihoods. However, a need remains for improved productivity and adaptation to the risks associated with climate change. To accomplish this, the increased adoption of climate-resilient and high-yielding rice varieties can be beneficial. Therefore, we conducted a study in Bangladesh over three consecutive years: 2016, 2017, and 2018. The scope of the study included the major cropping season (wet), Aman. The yield advantages of climate-resilient rice varieties were evaluated and compared with those of the varieties popular with farmers. We included new stress-tolerant varieties, such as submergencetolerant rice (BRRI dhan51 and BRRI dhan52) and drought-tolerant rice (BRRI dhan56 and BRRI dhan71), along with farmer-chosen controls, in the study. We conducted the evaluation through on-farm trials to compare the varieties in both submergence- and drought-affected environments. The seasonal trials provided measured results of yield advantages. The participating farmers were also studied over the three-year-period to capture their varietal adoption rates. We calculated both the location estimated yield advantages (LEYA) and the location observed yield advantages (LOYA). The results revealed that, under non-stress conditions, the grain yields of climate-resilient varieties were either statistically similar to or higher than those of the farmer-chosen controls. Our study also revealed a year-to-year progressive adoption rate for the introduced varieties. The study suggests that the widescale introduction and popularization of climate-resilient varieties can ensure higher productivity and climate risk adaptation. The close similarity between LOYA and LEYA indicated that the observational and experiential conclusions of the host farmers were similar to the scientific performance of the varieties. We also found that comparison performed through on-farm trials was a critical method for enhancing experiential learning and obtaining an accurate estimation of yield advantages.