Abstract
The objective of this study was to assess the variability of annual and monthly precipitation under current and future climate conditions, and to characterize its effects on soybean grain yield in the municipality of Tangará da Serra, Mato Grosso state, Brazil, using future climate projections from General Circulation Models (GCMs) and the Decision Support System for Agrotechnology Transfer (DSSAT), employing the CROPGRO-Soybean module. Model calibration was based on climate, soil, and management data, as well as genetic coefficients and field observations from the 2015/2016 growing season, considering cultivars with different maturity groups. Simulations were performed for six different sowing dates. Results indicated both positive and negative monthly fluctuations in precipitation under the current scenario. Among these, significant reductions were observed in September, October, and December, along with a general decreasing trend in annual precipitation for the region. Future scenarios (RCPs 4.5 and 8.5) showed both positive and negative variations, though not statistically significant. Earlyand intermediate-maturing cultivars exhibited lower yields and greater variability, whereas the late-maturing cultivar showed superior yield across all scenarios and sowing dates. Early sowings (September 20 to October 20) resulted in the lowest yields, while late sowings (November 1 and 10) were more favorable. Annual average precipitation was 1711 mm (current), 1494 mm (RCP 4.5), and 1515 mm (RCP 8.5). It is concluded that climate variability significantly affects soybean grain yield, with late-maturing cultivars and delayed sowings being recommended to enhance adaptation under future climate conditions.
Funding Information
  • Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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