Rapid prediction of Apparent Amylose, total starch, and crude protein by near-infrared reflectance spectroscopy for foxtail millet (Setaria italica)

Background and objectives The aim of this study was to construct near-infrared reflectance spectroscopy (NIRS) models to test the contents of apparent amylose, total starch, and crude protein for both foxtail millet grain and dehusked millet grain. The construction of models is based on chemical values and optimized spectral data of 111 core foxtail millet germplasm materials after analyzation of partial least square (PLS) method with cross-validation. Findings Model calibration showed that there was better fitting degree of dehusked millet grain than that of foxtail millet. The coefficient determination for calibration (Rc(2)) of former is >0.843, while that of latter is >0.823. The coefficient determination of prediction (Rp(2)) of each component ranged from 0.794 to 0.888 for foxtail millet grain and 0.833 to 0.970 for dehusked millet grain. Conclusions The constructed NIRS models of both samples can be used to rapidly test foxtail millet quality, and the nondestructive nature of foxtail millet grain-based test (which maintains seed vigor) better meets the requirements of the breeding, although the accuracy needs to be further improved. Significance and novelty This study developed a rapid method to detect the main nutritional quality for foxtail millet using two different samples, which can be used in germplasm resource innovation and contribute to the acceleration of cereal breeding.