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Multivariate statistical analysis combined with e-nose and e-tongue assays simplifies the tracing of geographical origins of Lycium ruthenicum Murray grown in China

Author:
Wang, Zi-Chao, Yan, Yuzhen, Nisar, Tanzeela, Sun, Lijun, Zeng, Yang, Guo, Yurong, Wang, Huichun, Fang, Zhongxiang
Source:
Food control 2019 v.98 pp. 457-464
ISSN:
0956-7135
Subject:
Lycium ruthenicum, discriminant analysis, electronic nose, electronic tongue, multivariate analysis, prediction, principal component analysis, provenance, sensory evaluation, China
Abstract:
This study aims to develop a fast and simple method to trace the geographical origins, harvest years and varieties of Lycium ruthenicum Murray (LRM) grown in China by employing e-nose and e-tongue assays and their combination. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied for qualitative classification and quantitative prediction. The results showed that e-nose and e-tongue assays and their combination failed to recognize harvest years and varieties of LRM, but achieved reliable results for tracing LRM geographical origins with a total classification ability of 86.4%, 86.8% and 92.6% respectively. In addition, the analysis procedure required shorter time and less chemical reagents as compared to high-end instrumental analysis or traditional methods like chemical analytical methods and sensory evaluation. This study demonstrated that the multivariate statistical analysis combined with e-nose and e-tongue assays could be a reliable and simplified method of tracing the geographical origins of LRM.
Agid:
6265789