Search

Maize-legume intercropping is a sustainable strategy to improve maize production for smallholder farmers. Maize is a staple food crop in Bhutan and integration of legumes with maize has been considered as an alternative option towards enhancing maize production in the country. Here, we conducted two studies in eastern Bhutan: first study (2021) to identify suitable legumes for intercropping with maize and second study (2022) to evaluate the effects of different maize-soybean intercropping patterns on grain yield, land use efficiency, and economic benefits. The maize-soybean intercropping system showed better productivity and economic viability than the kidney bean and groundnut systems in both the sites. Row intercropping and strip intercropping with 2 rows of maize alternating with 2 rows of soybean (2 M:2S) spaced 0.3 × 0.3 m showed stable and consistently higher grain yield at Lingmethang and Wengkhar (LING = 6.05 t ha−1; WENG = 8.37 t ha−1). The land equivalent ratio (LING = 1.78; WENG = 1.73) and net return (0.16 million Nu. ha−1 for LING and 0.21 million Nu. ha−1 for WENG) were notably higher for these intercropping methods. Our results suggest that the integration of legumes between conventional maize planting density, row intercropping and strip intercropping (2 M:2S) spaced at 0.3 × 0.3 m would be beneficial for achieving higher productivity for smallholder farmers in eastern Bhutan.

Maize is the staple food crop in Bhutan, which has not achieved national food self-sufficiency. On-farm assessment of yield variability would provide insights into the priorities for Bhutan's maize development program. Here, we conducted three studies in Bhutan: a household survey, on-station experiment, and on-farm monitoring. First, we interviewed 100 households and collected information on maize crop management options and farming characteristics. Second, we evaluated maize growth at two research stations in different elevation zones (640 and 1,700 ​m a.s.l.). Third, we harvested maize from 25 farm fields at low and high elevations. The gaps between potential yield (with the best management practices at the research stations) and average farm yield and between the best and average farm yields were 53% and 23%, respectively, at the low elevation, and 23% and 20%, respectively, at the high elevation. The classification and regression tree (CART) model showed that field location (distance from the farmer's home), seed source (certified vs. self-produced), and the number of household members involved in farming were the key farming characteristics that affected yield variability, and the manure application regime, urea application, sowing method, and weeding frequency were key management practices. Our results suggest that future research should clarify the most suitable sowing methods and nutrient and weed management regimes, and identify optimal cultivars for each elevation zone, with the goal of developing crop management guidelines for smallholder farmers in Bhutan.