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Development of a Near-infrared Spectroscopy Calibration Model to Predict Methionine Content in Whole Soybeans

Soybean is an important source of high-quality protein for humans and livestock. However, the content of methionine, a sulfur-containing essential amino acid, is deficient and inadequate for consumer needs. Amino acid evaluation can be performed by conventional wet chemical techniques like high-performance liquid chromatography (HPLC). To ease out the need for complex laboratory infrastructure and highly skilled experts often required by these procedures, HPLC datasets can be paired with data obtained from Near-infrared (NIR) reflectance spectroscopy. Through this approach, spectral data can be used to develop calibration models that could predict chemical properties for a fast and reliable soybean feed evaluation. In this study, NIR spectra data were acquired from 594 whole soybean samples from the USDA Soybean Germplasm Collection in a wavelength range from 950 to 1650 nm. Methionine content (g/kg dry weight and g/kg protein) was measured after spectral data collection using HPLC and predictive calibration models were developed using two different regression algorithms, namely partial least square regression (PLSR) and support vector machine (SVM). For model optimization, different spectra pre-processing, and wavelength selection methods were tested. PLSR models outperformed SVM models, with the best performing model having a coefficient of determination of calibration R2Cal = 0.39, the coefficient of determination of validation R2Val = 0.31, root mean squared error of calibration RMSEC = 0.75, and root mean squared error of validation RMSEP = 0.68 for g methionine / kg dry weight. To predict g methionine / kg protein, the obtained statistics were R2Cal = 0.25, and R2Val = 0.17 for which a more accurate alternative prediction method should be further investigated. The obtained calibration model to predict methionine concentration with respect to the dry weight can be potentially used for the accurate selection of breeding lines in the high-methionine concentration range.