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The computational models that simulate yield of agricultural crops are important to planning activities. The objective of this study was to verify the performance of AquaCrop model to simulate soybean and maize yield in Campos Gerais region, in different soil types. The AquaCrop was used to estimate yield, requiring climate, soil, crop and soil management input data. In the analysis were used data from 21 and 32 experiments with maize and soybeans, respectively, carried out in the ABC Foundation, from years harvest between 2006 and 2014. For soybean crop, the highest absolute and relative errors of productivity simulations occurred in less productive crops, due to the lack of rain during sowing, water deficit in the harvest or high temperatures in the first weeks after the plants emergence. The highest absolute and relative errors verified in the simulations with maize crop experiments did not allow defined pattern identification. The AquaCrop achieved “very good” and “excellent” performances in the simulations of soybean and maize yield it the analyzed locations. The soil type affected the results from the analyzes of the two crops, and the Latossolos provided better performance and higher correlation compared to other soil types.

Simulation and performance yield of soybean and maize crops by AquaCrop, in Campos Gerais, Paraná State