Classification of Vietnamese Cashew Nut (Anacardium occidentale L.) Products Using Statistical Algorithms Based on ICP/MS Data: A Study of Food Categorization

Author:

Nguyen-Quang Trung1ORCID,Bui-Quang Minh1,Pham-Van Thinh2,Le-Van Nhan1,Nguyen-Hoang Khanh1,Nguyen-Minh Duc3,Phung-Thi Tinh1,Le-Viet Anh1ORCID,Tran-Ha Minh Duc1ORCID,Nguyen-Tien Dat1,Hoang-Le Tuan-Anh1,Truong-Ngoc Minh1ORCID

Affiliation:

1. Center for Research and Technology Transfer (CRETECH), Vietnam Academy of Science and Technology (VAST), 18 Hoang Quoc Viet Road, Hanoi, Vietnam

2. Faculty of Food Science and Technology, Ho Chi Minh University of Food Industry, 140 Le Trong Tan, Tan Phu District, Ho Chi Minh 70000, Vietnam

3. Institute of Genome Research, Vietnam Academy of Science and Technology (VAST), 18 Hoang Quoc Viet Road, Hanoi, Vietnam

Abstract

Fingerprinting techniques, which utilize the unique chemical and physical properties of food samples, have emerged as a promising approach for food authentication and traceability. Recent studies have demonstrated significant advancements in food authentication through the use of fingerprinting methods, such as multivariate statistical analysis techniques applied to trace elements and isotope ratios. However, further research is required to optimize these methods and ensure their validity and reliability in real-world applications. In this study, the inductively coupled plasma mass spectrometry (ICP-MS) analytical method was employed to determine the content of 21 elements in 300 cashew nut (Anacardium occidentale L.) samples from 5 brands. Multivariate statistical methods, such as principal components analysis (PCA), were employed to analyze the data obtained and establish the provenance of the cashew nuts. While cashew nuts are widely marketed in many countries, no universal method has been utilized to differentiate the origin of these nuts. Our study represents the initial step in identifying the geographical origin of commercial cashew nuts marketed in Vietnam. The analysis showed significant differences in the means of 21 of the 40 analyzed elements among the cashew nut samples from the 5 brands, including 7Li, 11B, 24Mg, 27Al, 44Ca, 48Ti, 51V, 52Cr, 55Mn, 57Fe, 60Ni, 63Cu, 66Zn, 93Nb, 98Mo, 111Cd, 115In, 121Sb, 138Ba, 208Pb, and 209Bi. The PCA analysis indicated that the cashew nut samples can be accurately classified according to their original locations. This research serves as a prerequisite for future studies involving the combination of elemental composition analysis with statistical classification methods for the accurate establishment of cashew nut provenance, which involves the identification of key markers for the original discrimination of cashew nuts.

Funder

Vietnam Academy of Science and Technology

Publisher

Hindawi Limited

Subject

Computer Science Applications,Instrumentation,General Chemical Engineering,Analytical Chemistry

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