Agrometeorological conditions in western Pará compared to agricultural production variables using principal component analysis

Abstract

Description of the subject. Since the beginning of the twenty-first century, soybean cultivation areas have been expanding in the Legal Amazon. Among the factors that contribute to the process of expansion of cultivation of grains in the Amazon, favorable climate conditions are one of the most important, and these include high rainfall indices and good thermal regimes during the cultivation period. Objectives. In this context, the objective of this study was to describe responses of soybean production as a function of climate variables, considering data from an important grain production center in the Amazon. Method. Principal Component Analysis (PCA) was used including the following response variables: rainfall (R), air temperature (T), real evapotranspiration, water stress (WST) and surplus, soybean area harvested (HVA), quantity produced (PD), occurrence of El Niño and La Niña (LAN). Results. Production variables were negatively correlated with precipitation and water surplus. There was also a negative correlation between El Niño, temperature and water stress. The variables that had greater weight in component 1 were R, T and WST. Considering component 2, the variables that most contributed to the variation were HVA, PD and LAN. Conclusions. The strong or severe occurrence of La Niña influences the soybean production in the region of Belterra-PA, due to the high rainfall index causing excess water in the soil, leading the plants to stress. The moderate occurrence of La Niña positively influences soybean production in the region to maintain the water supply at adequate levels for the plants. These results show the importance of monitoring climate variables for agriculture in the region.