Authentication of apples from the Loess Plateau in China based on interannual element fingerprints and multidimensional modelling

文献类型： 外文期刊

第一作者： Zhang, Jianyi

作者： Zhang, Jianyi;Shen, Youming;Xu, Guofeng;Ma, Ning

作者机构：

关键词： Apple; Multielement; Geographical verification; Linear and nonlinear discriminant analysis; Random forest

期刊名称：FOOD CHEMISTRY-X （ 影响因子：6.1； 五年影响因子：6.4 ）

ISSN： 2590-1575

年卷期： 2023 年 20 卷

页码：

收录情况： SCI

摘要： Apple is an important fruit, and fruit authentication is significant for quality and safety control. The Loess Plateau (LP) in China is an important apple-producing region. However, the geographic authentication of LP apples has not been well studied. In this study, we discriminated LP apples based on multielement analysis. We analysed the differences in 29 elements of 522 samples collected from LP and others in 2018-2020 and constructed discriminant models for LP apple authentication. Linear discriminant analysis, partial least square-discriminant analysis, back-propagation artificial neural networks, and random forest (RF) showed different rates in training and validation accuracy. RF showed better tolerance to the removal of the less-important elements in model optimization. The final RF was optimized on 11 elements, which obtained 95.30% training accuracy for the 2018-2019 samples and 97.29% validation accuracy for the 2020 samples. The multielement-based authenti-cation of LP apples could aid further studies of geographical origins.

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