Infrared spectroscopy and chemometrics for the starch and protein prediction in irradiated rice

Infrared spectroscopy was investigated to predict components of starch and protein in rice treated with different irradiation doses based on sensitive wavelengths (SWs). Near infrared and mid-infrared regions were compared to determine which one produces the best prediction of components in rice after irradiation. Partial least-squares (PLS) analysis and least-squares-support vector machine (LS-SVM) were implemented for calibration models. The best PLS models were achieved with NIR region for starch and MIR region for protein. Moreover, independent component analysis (ICA) was executed to select several SWs based on loading weights, and the optimal LS-SVM model was achieved with SWs of 1210–1222, 1315–1330, 1575–1625, 1889–1909 and 2333–2356 nm for starch and SWs of 962–1091, 1232–1298, 1480–1497, 1584–1625 and 2373–2398 cm⁻¹ for protein. It indicated that IR spectroscopy combined with LS-SVM could be applied as a high precision way for the determination of starch and protein in rice after irradiation.