An efficient method for tracing the geographic origin of Enshi Yulu fresh tea leaves based on near infrared spectroscopy combined with synergy interval PLS and genetic algorithm

文献类型: 外文期刊

第一作者: Wang, Shengpeng

作者: Wang, Shengpeng;Feng, Lin;Liu, Panpan;Gui, Anhui;Gao, Shiwei;Teng, Jing;Ye, Fei;Wang, Xueping;Xue, Jinjin;Zheng, Pengcheng;Wang, Shengpeng;Feng, Lin;Liu, Panpan;Gui, Anhui;Gao, Shiwei;Teng, Jing;Ye, Fei;Wang, Xueping;Xue, Jinjin;Zheng, Pengcheng;Song, Zhiyu;Jiang, Zixiang

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关键词: Fresh tea leaves; Geographic origin; Near infrared spectroscopy; Partial least squares; Genetic algorithm

期刊名称:LWT-FOOD SCIENCE AND TECHNOLOGY ( 影响因子:6.0; 五年影响因子:6.0 )

ISSN: 0023-6438

年卷期: 2024 年 203 卷

页码:

收录情况: SCI

摘要: This paper applies near-infrared spectroscopy (NIRS) and multiple chemometrics to efficiently distinguish the origins of fresh tea leaves. The key components were obtained using the partial least squares discriminant analysis (PLS-DA) method. PLS, synergy interval PLS (siPLS), principal component analysis (PCA), genetic algorithm (GA), and their combination methods were used to establish NIRS non-destructive discrimination models. Then, the practical application was examined using external samples. The study identified nine key components (variable importance for the projection (VIP) > 1): epigallocatechin, epicatechin, total sugar, water extracts, total catechins, gallocatechin gallate, tea polyphenols, gallocatechin, and epigallocatechin gallate. Of the six NIRS models, the siPLS-GA model that used 37 spectral data points produced the best results (Rp(2) = 0.9706, RMSEP = 0.0772, RPD = 6.59). This model had a prediction accuracy of 96.67% for the prediction set samples and 93.33% for the external samples. It offers a rapid, precise, and non-invasive approach to monitor and regulate the illicit trade of fresh tea leaves, thereby guaranteeing the authenticity of Enshi Yulu products from the processing source and fostering the long-term prosperity and stability of the Enshi Yulu tea industry.

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