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Evaluating and improving the DSSAT/CROPGRO for water and nitrogen processes for tropical soybean in Brazil

Grant number: 19/18303-6
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): February 10, 2020
Effective date (End): February 09, 2021
Field of knowledge:Agronomical Sciences - Agronomy - Agricultural Meteorology
Principal researcher:Fabio Ricardo Marin
Grantee:Evandro Henrique Figueiredo Moura da Silva
Supervisor abroad: Kenneth Jay Boote
Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Research place: University of Florida, Gainesville (UF), United States  
Associated to the scholarship:17/23468-9 - Quantification of the potential of sustainable intensification of Brazilian soybeans: potential productivity and efficiency of agricultural production, BP.DR


Soybean is a crop of major social and economic importance for Brazil. In order to meet the increasing demand for feed protein, soybean areas have been expanding strongly over the last decade reaching areas with adverse soil and climatic conditions. The expansion of food and feed demand together with the scarcity of available new arable land for production increase raise the importance of agricultural intensification by increasing the crop yields. To evaluate the potential for yield increase in a given region, process-based crop modelling has been considered a useful tool for estimating the potential yield of crops. The tropical region of Brazil currently producing the soybean crop has been assumed as a key place for supplying the world future demand for protein at reasonable prices. Tropical soybean in Brazil is grown under rainfed conditions and processes related to water use and drought stresses are the key ones for models to accurately simulate crop growth and development. Recent publications have shown the effect of supplementary nitrogen on soybean yield potential under temperate conditions. However, while soybean models have been well tested under temperate and sub-tropical conditions, little has been published dealing with both water and nitrogen processes with data collected from well-designed experiments under tropical conditions. This proposal aims to evaluate the DSSAT/CROPGRO-Soybean model with data collected from 7 experiments at four sites in Brazil : (i) Cruz Alta, RS (2018/19; (ii) Sorriso, MT (2018/19); (iii) Piracicaba, SP (2016-2019); and (iv) Teresina, PI (2019) designed to evaluate the nitrogen and/or water effects on tropical soybean potential yield. Based on this evaluation, we expect to document the model reliability under these conditions and suggest possible improvements to the related algorithms for reducing the model uncertainty and improving its accuracy in prediction. (AU)

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