Yield Performance and Response to High Plant Densities of Dry Bean (Phaseolus vulgaris L.) Cultivars under Semi-Arid Conditions

To identify eco-efficient bean cultivars that can be planted at high densities for sustainable bean production under climate change, this study analyzed the performance of ten dry bean (Phaseolus vulgaris L.) cultivars grown at 90,000, 145,000 and 260,000 plants ha(-1) under rainfed semi-arid conditions in Mexico. The study compared the yield and yield components (leaf area index (LAI), pods per plant, and hundred seed weight) of the cultivars. We also analyzed the dry matter distribution (DMD), growth rate (GR), radiation use efficiency (RUE), and harvest index (HI) of the best performing cultivars to determine how they respond to higher densities. The cultivars were established under similar planting and management conditions during two growing seasons. The precipitation for the first and second seasons were 175 and 492 mm, respectively, representing 57% and 160% of the mean precipitation in the area during the July-October growing period. Pinto Saltillo, a drought-tolerant indeterminate semi-prostrate cultivar, and Azufrado 2, a determinate shrub cultivar, performed best at high densities under low-precipitation conditions (175 mm). Both cultivars responded to the highest density (260,000 plants ha(-1)) with increases of 54% to 69% (0.7 to 1.1) in LAI and 21% to 86% (0.32-0.81 Mg ha(-1)) in yield. The two cultivars responded to increasing plant density with a modification in their fraction of DMD over plant parts and a change in their GR from 0.23-0.25 at low density to 0.96-1.74 gr m(-2) day(-1) at high density. The two cultivars had an RUE of 3.8 to 4.4 g MJ(-1) and HI of 0.31 to 0.36 at high planting density. Farmers' use of these commercially available cultivars proven to have high yields and the ability to respond favorably to high densities under rainfed conditions can be a viable short-term strategy to increase dry bean production for sustainable agriculture in semi-arid temperate regions.