Simultaneous determination of apparent amylose, amylose and amylopectin content and classification of waxy rice using near-infrared spectroscopy (NIRS)
2022
Xie, Li-Hong | Tang, Shao-Qing | Wei, Xing-Jin | Sheng, Zhong-Hua | Shao, Gao-Neng | Jiao, Gui-Ai | Hu, Shi-Kai | Wang, Lin | Hu, Pei-Song
Rice starch properties of apparent amylose content (AAC), amylose content (AC), and amylopectin content (AP) are considered as the most important factors influencing grain quality as they are highly correlated with eating quality. This report is the first effort of predicting AC and AP values in rice flours, and recognizing waxy rice from non-waxy rice using NIRS technique. Calibration models generated by different mathematical, preprocessing treatments and combinations of wavelengths and signals were compared and optimized. The model established by modified partial least squares (MPLS) with “2, 8, 8, 2”/ Inverse MSC and ∼138 wavelengths signals yielded high RSQ of 0.977, 0.928, and 0.912 for AAC, AC and AP, respectively, as simultaneous measurement. MPLS-DA (discriminant analysis) could classify waxy and non-waxy rice with 100% accuracy. This high-throughput technology is valuable for breeding programs, and for the purposes of quality control in the food industry.
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