Abstract
Portable near-infrared (NIR) spectroscopy combined with multivariate calibration was used to determine the chemical composition of maize and sorghum grains of different genotypes cultivated in Brazil. Partial least squares (PLS) models were built, and the maize models exhibited R2 > 0.90 for all constituents except starch. For sorghum, the R2 was > 0.8 for all componentes. The Residual Prediction to Deviation (RPD) values and the Range Error Ratio (RER) values for all maize and sorghum calibration models exceeded 2.5 and 10, respectively, indicating the models’ reliability for routine laboratory implementation. No significant differences were found between the results obtained by the PLS models and the reference methods for any analyzed constituents in the maize and sorghum grains. These results demonstrate that the MicroNIR instrument is a viable tool for quality control of chemical composition in maize and sorghum grain samples. It offers the advantages of speed, non-destructiveness, and being a green alternative to standard methods.
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