Although the technological and scientific advances, the climate is still the most important variable for crops productions (CALDANA et al., 2019; CALDANA et al., 2021). The researchers Caramori et al. (2008) and Ferreira et al. (2020) pointed out that 80 % of yield variability come from the climate, in this context, the rainfall exhibits remarkable relevance for variability on the crops productions (FERREIRA et al., 2020). Agrometeorological models for crop growth, known as crop modeling simulations, can help the farmer for decision-making and for agricultural planning, such as crop adaptation, chose the best cultivar for a given local, best time to sowing/planting, crop monitoring, forecasting and even for control the pest and disease incidences. These models have a great importance to help the decision-making of the farmer (MORAES et al., 1998; SENTELHAS et al., 2015; TEIXEIRA et al., 2018).