Determination of geographical origin of Hovenia dulcis found in Korea and China via inorganic element analysis using inductively coupled plasma spectroscopy and multivariate statistical analysis
- Authors
- Jeong, Jimin; Baek, Kyoung Hye; Jeon, Hwang-Ju; Kim, Hyoyoung; Kim, Yong-kyoung; Kim, Hojin
- Issue Date
- Dec-2025
- Publisher
- Elsevier BV
- Keywords
- geographical origin; Hovenia dulcis; inductively coupled plasma-mass spectrometry; inductively coupled plasma-optical emission spectroscopy; linear discriminant analysis; orthogonal partial least squares-discriminant analysis; Shapley additive explanation value
- Citation
- Food Chemistry, v.496, pp 146708
- Indexed
- SCIE
SCOPUS
- Journal Title
- Food Chemistry
- Volume
- 496
- Start Page
- 146708
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/81438
- DOI
- 10.1016/j.foodchem.2025.146708
- ISSN
- 0308-8146
1873-7072
- Abstract
- The fruit of Hovenia dulcis, a popular Korean hangover remedy, is marketed as Korean and Chinese products. To protect domestic producers, ensure accurate labeling, and safeguard consumers, this study discriminated origin through inorganic element analysis using inductively coupled plasma-optical emission spectroscopy and mass spectrometry. Orthogonal partial least squares-discriminant analysis showed high model quality (R2 = 0.956, Q2 = 0.883). Twenty-five elements had variable importance in projection (VIP) values ≥1, and receiver operating characteristic analysis confirmed 100 % accuracy. Coefficient plots revealed Ca (-0.453081), 103Rh (-0.222397), 175Lu (-0.2084) significant for Chinese, while 11B (0.137669) and 88Sr (0.0954821) were significant for Korean. Linear discriminant analysis showed intergroup distance of 19, indicating strong discrimination. Findings highlight ICP-based elemental profiling with chemometrics and machine learning as a robust tool for authenticating H. dulcis origin, offering advantages over traditional visual methods and supporting regulatory monitoring, labeling accuracy, and consumer protection. © © 2025 Elsevier Ltd. All rights reserved.
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