Abstract

The Brazilian national growing of dry bean (Phaseolus vulgaris) currently comes in three annual harvests, which are the wet season, sowing between October and December, the Dry Season, sowing between February and May, and finally the Winter Season, sowing in June to August. The objective of this study was to determine the optimal sowing date for each of the three different sowing seasons wet, dry and winter of dry bean to the Tangará da Serrá region using a crop simulation software called Decision Support System for Agrotechnology Transfer (DSSAT). The DSSAT is comprised of crop simulation models, in which the CROPGRO-Drybean model was used to simulate the dry bean growth, development, and yield. The model was calibrated using the dry bean cultivar ‘BRS Esplendor’, planted on 15 December 2011 in Tangará da Serra, located in the Mato Grosso state of Brazil. The weather variables (maximum and minimum temperature, solar radiation and precipitation), phenological and soil variables were recorded during the season and used in the model calibration to ensure a satisfactory simulation. Following the calibration, simulations were performed for six sowing dates in each of the three seasons. Of the three growing seasons simulated, the wet season had the best grain yields for the dry bean ‘BRS Esplendor’, the sowing date of December 1^st had the highest yields of 3.3 t ha^-1. The dry season had the second high simulated yields, and the highest yield into this growing season was 3.0 t ha^-1. In the dry season, grain yield decreased as late sowing date occurred, and the lowest simulated yield was 0.1 t ha^-1. Finally, the winter season had the lowest simulated yields among the three growing season, with a maximum yield of 0.5 t ha^-1. The CROPGRO-Drybean model had a high sensitivity to rainfall events, and drought periods during the reproductive stage of dry bean was the weather parameter that most affected grain yield. The winter season had lower yields than the wet and dry season in consequence of low rainfall events during the simulated crop cycles, the soil moisture was highly affected by precipitation, which directly affected the leaf area index and crop yield in all sowing dates.

Key words: CROPGRO-dry bean, yield, water stress, precipitation, soil moisture