Abstract
Grain composition is directly related to maintenance of quality. Chemical analyses have been determined using traditional and laborious methods, which are time-consuming and generate chemical waste. This justifies the development of fast and accurate alternative methodologies to control the grain composition. Near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques associated with chemometric tools have been applied in the development of several analytical methodologies for agricultural products. The aim of this study is to develop and compare these two spectroscopic techniques to determine the parameters of quality, such as moisture, protein, lipid and ash content, in 20 varieties of soybean, which are grown in the cities of Ponta Grossa and Londrina, Brazil, totally 40 samples. It was used near-infrared and mid-infrared spectroscopy, with diffuse reflectance measurements, associated with multivariate calibration methods based on partial least squares algorithm. The determination coefficient (R2) for moisture, ash, protein and lipid content were 0.72, 0.73, 0.88 and 0.81 for NIR and 0.63, 0.87, 0.91 and 0.67 for MIR, respectively, having an RMSECV (root mean square error of cross-validation) < 2.09%. The results show that both infrared (NIR and MIR) techniques have predictive abilities.
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