Mathematical equations representing the impacts of climatic factors on soybean productivity in the 2018/2019 crop season in the Parana State, Brazil

Resumo

In the 2018/19 crop season, throughout Parana State, water distribution was below that initially expected. In addition, air temperatures were above historical averages. Many soybean fields were affected in flowering and grain formation. As a consequence, there was a significant drop in crop productivity relative to the previous crop season of 2017/18. This work aimed to study the climatic and environmental variables that interfered with soybean productivity through mathematical regression models. Climate data from 19 INMET (2019) meteorological stations, distributed throughout Paraná, and soybean production, obtained from the Paraná Department of Agriculture, were used. Regression equations were generated using the linear, multiple linear, and stepwise regression methods, and making combinations of the independent variables (altitude, latitude, rainfall, and average air temperature) with the dependent variable being productivity. The equation that best represented the climatic and environmental conditions that occurred in the 2018/19 crop season in Parana was established by stepwise linear regression, involving altitude and latitude. The altitude presented a greater significance. Latitude showed less significance, being important, but not having the same importance as altitude in the soybean productivity process in the 2018/2019 crop season.