4.6 Article

Combining multielement analysis and chemometrics to trace the geographical origin of Thelephora ganbajun

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出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jfca.2020.103699

关键词

Wild edible mushroom; Mineral elements; Multivariate data analysis; Classification; Traceability

资金

  1. Research on Key Technology of New Type Screening and Detection of High Value Agricultural Products with Characteristic [2017YFF0211300]
  2. Research on the Technology of Identity Precision Screening and Authenticity Screening of High Value Agricultural Products with Characteristic [2017YFF0211301]

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Geographical traceability of the highly valued wild edible mushroom T. ganbajun was examined using multielement analysis and multivariate statistics methods in Yunnan province, China. Thirteen elements were analyzed and used as chemical indicators to determine geographical origins, with successful results in distinguishing different origins of T. ganbajun.
Geographical traceability is essential to the highly valued wild edible mushroom Thelephora ganbajun (T. ganbajun). This work examined the possibility of using the combination of multielement together with multivariate statistics methods, to identify the origins of 40 T. ganbajun from four sites of Yunnan province, China. Multielement analysis of thirteen elements (Mg, K, Ca, Al, Cr, Zn, As, Se, Cd, Pb, Fe, Mn, and P) were investigated by inductively coupled plasma mass spectroscopy (ICP-MS). Pearson correlation analysis was performed to check for the potential relationship between elements. Concentrations were used as chemical indicators to determine the geographical origins of T. ganbajun samples by utilizing multivariate data analysis, including principal component analysis (PCA), hierarchical cluster analysis (HCA), and linear discriminant analysis (LDA). Thirteen elements in T. ganbajun from different regions showed significant differences (p < 0.05), which proved that the elemental composition was an effective tool for distinguishing different origins of T. ganbajun. Classification of T. ganbajun using PCA gave satisfactory results, which permitted the reduction of 13 variables to three principal components explaining 92.84 % of the total variance. The HCA showed four clusters corresponding to the four origins of T. ganbajun. The LDA gave an overall correct classification rate of 100 % with an independent external sample set. These results revealed that multielement analysis combined with chemometrics is a useful tool for distinguishing T. ganbajun geographical origin.

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