Establishment of near-infrared rapid prediction model and comprehensive evaluation model for foxtail millet quality

文献类型： 外文期刊

第一作者： Bai, Yu

作者： Bai, Yu;Zhang, Zhuo;Qiao, Jiawei;Liu, Xiaolong;Guo, Shengyuan;Zhang, Guohua;Ren, Guixing;Zhang, Lizhen;Wang, Genping;Zhang, Ting;Ren, Guixing

作者机构：

关键词： Foxtail millet; Quality analysis; Near infrared spectroscopy; Partial least squares regression; Rapid evaluation model; Comprehensive evaluation

期刊名称：JOURNAL OF FOOD COMPOSITION AND ANALYSIS （ 影响因子：4.6； 五年影响因子：4.6 ）

ISSN： 0889-1575

年卷期： 2024 年 136 卷

页码：

收录情况： SCI

摘要： Foxtail millet (Setaria italica) is one of the earliest cereal crops in the world and is still an important food crop in Asia, Europe and Africa. However, there are few reports on rapid and comprehensive evaluations of foxtail millet quality. In this study, color, nutrient content, cooking quality and sensory quality of 45 varieties of foxtail millet from the main production areas of the country were determined. Near infrared spectroscopy (NIRS) combined with partial least squares regression (PLSR) was developed for rapid and nondestructive detection of foxtail millet quality, where NIRS models for ash, amylopectin, protein, and VB1 and VB2 were desirable. In addition, correlation analysis, principal component analysis and cluster analysis were used for comprehensive evaluation of millet quality. The results showed that foxtail millet with low ash, protein, fat and fiber content and high amylopectin and carotenoid content has good cooking quality and was more preferred. This research will contribute to the quality evaluation and further processing of foxtail millet.

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