Modelagem espectro-agrometeorológica para estimativa da produtividade da soja no estado do Mato Grosso

Abstract

Precise estimation of soybean yield before harvest on a local or regional scale provides valuable information. The monitoring of the crop in order to monitor the phenological development and to estimate the productivity has been carried out using conventional methods, such as meteorological station data and field visits. These results, often subjective, are not always accurate. Recent studies demonstrate the applicability of data obtained by satellites in the analysis of the soil, plant and atmosphere system for the purpose of acquiring accurate information of large areas and at lower costs. In this sense, the main objective of the present work was to estimate the productivity and to analyze the phenological development of the soybean, in the state of Mato Grosso, using spectral data. Data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and products derived from the Geostationary Operational Environmental Satellite (GOES IMAGER) integrated with the spectral agrometeorological model for soybean grain estimation were used. After validation of the usability of the spectral data, MERRA-2 temperature data, and actual and potential evapotranspiration data, precipitation, hours of solar brightness and vegetation indexes derived from satellite images were used to estimate soybean yield [Glycine max (L.) Merrill] with the methodology of Doorenbos and Kassam (1979), developing a spectral agrometeorological model. Productivity estimates were generated for 10 farms distributed in 10 farms located in agglomerates producing soybeans in the State of Mato Grosso, for the 2012/2013 harvest. The main results obtained were that the MERGE-3B42RT products of the TRMM satellite presented high correlation (with R² ranging from 0.80 to 0.87) for estimation of the precipitation data and the Merra-2 reanalysis values provided good results for estimation temperature and relative humidity. The spectral agrometeorological model showed, for productivity, correlation and determination coefficients of 0.84 and 0.72, respectively, with a concordance index between 0.96 and 0.99.