The application of UV-VIS-NIR spectroscopy combined with multivariate analysis for the classification and identification of buckwheat groats was analyzed. Samples of buckwheat groats differing in harvest time, kernel size, roasting method, and storage time were divided into groups using a cluster analysis method. The principal components method revealed absorption bands in UV-VIS-NIR spectra corresponding to functional groups of the composition components and contributing most to differentiation of the samples into buckwheat quality categories. Discriminant analysis confirmed a hypothesis on dividing the buckwheat samples into groups and formulating a classification function to identify and sort buckwheat groats.

分析了紫外-可见-近红外光谱结合多元分析在荞麦碎粒分类鉴定中的应用。使用聚类分析方法将收获时间、籽粒大小、烘烤方法和储存时间不同的荞麦碎粒样品分成几组。主成分方法揭示了 UV-VIS-NIR 光谱中的吸收带，对应于组合物成分的官能团，并且最有助于将样品区分为荞麦质量类别。判别分析证实了将荞麦样品分组并制定分类函数来识别和分类荞麦碎粒的假设。