Abstract
Lentil (Lens culinaris Medik.) is a cool-season pulse grown in winter cropping cycle in South Asia and provides a major source of nutrition for many low-income households. Lentil productivity is perceived to be sensitive to high rainfall, but few studies document spatial and temporal patterns of yield variation across climate, soil, and agronomic gradients. Using farm survey data from Nepal, this study characterizes patterns of lentil productivity and efficiency for two cropping seasons. Additional insights were derived from on-farm trials conducted over a 5-year period that assess agronomic, drainage, and cultivar interventions. To contextualize the inferences derived from farm surveys and trials, the Stempedia model was used to simulate the severity of Stemphylium blight (Stemphylium botryosum) risk-the principal fungal disease in lentil-with 30 years of historical climate data. Although development efforts in Nepal have prioritized pulse intensification, results confirm that lentil remains a risky enterprise highlighting the prevalence of crop failures (16%), modest yields (353 kg ha-1), and low levels of profitability (US$ 33 ha-1) in wet winters. Nevertheless, site factors such as drainage class influence responses with upland sites performing well in wet winters and lowland sites performing well in dry winters. In wet winters, a phenomena perceived to be increasing, 76% of surveyed farmers reported significant disease pressure and simulations with Stempedia predict that conditions favoring Stemphylium occur in >60% of all years. Nevertheless, simulation results also suggest that these risks can be addressed through earlier planting. Based on the combined results, gains in yield, yield stability, and technical efficiency can be enhanced in western Nepal by: 1) ensuring timely lentil planting to mitigate climate-mediated disease risk, 2) evaluating new lentil lines that may provide enhanced resistance to diseases and waterlogging, and 3) encouraging the emergence of mechanization solutions to overcome labor bottlenecks.