Comprehensive use of two types of linear discriminant methods, principal component analysis (pca) and fisher criterion, to conduct pattern recognition and clustering research on the inorganic element components and organic components (amino acids, fats, starches, proteins, etc.) in Guangdong Zengcheng Silk Rice National Geographical Indication Products , and use the fisher linear discrimination method to establish a classification model between landmark products and non-landmark products. The results show that fisher linear discrimination is simple and fast for classifying and identifying rice geographical indication products. When the analyzed data is relatively complex, a classification model can be quickly established and the identification and identification of geographical indication products and non-geographic indication samples can be achieved.

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Original research was done by Ruan Guihua, Du Fuyou, Huang Xiaolong, He Xiaoqing, Zheng Yanjie, Yang Guowu

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