Hierarchical geographical origin discrimination and adulteration detection of white tea using UV-vis and NIR spectra

Chen Q 1 , Shao R 2 , Zaini NAM 3 , Daud NM 3 , Lim SJ 3 , Rogers KM 4 Show all authors , Song W 5 , Liu X 6

Affiliations 

  • 1 Institute for Agri-food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, 201403 Shanghai, China; Department of Food Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
  • 2 Institute for Agri-food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, 201403 Shanghai, China
  • 3 Department of Food Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
  • 4 Department of Soil and Physical Sciences, Lincoln University, Lincoln 7647, New Zealand
  • 5 Institute for Agri-food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, 201403 Shanghai, China. Electronic address: songweiguo@saas.sh.cn
  • 6 Institute for Agri-food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, 201403 Shanghai, China. Electronic address: liuxinglyg@126.com
Food Chem, 2026 Oct 29;532(Pt 4):151829.
PMID: 42956600 DOI: 10.1016/j.foodchem.2026.151829

Abstract

Fuding white tea, particularly premium silver needle, is a high-value Geographical Indication product increasingly vulnerable to cross-regional mislabeling, substitution, and blending. This study developed a dual-modal ultraviolet-visible diffuse reflectance and near-infrared spectroscopic strategy combined with chemometrics for hierarchical authentication. At the macro-geographical level, optimized UV-Vis and NIR PLS-DA models achieved accuracies of 100% and 97.54%, respectively, and correctly classified external Fujian and Yunnan samples. At the town scale within Fuding city, UV-Vis outperformed NIR in predictive ability (Q2 = 0.70 vs. 0.37), indicating greater sensitivity to subtle local origin variation. Earlier-year Panxi samples were also correctly assigned, suggesting preliminary temporal transferability for town-scale authentication. Colorimetric analysis showed limited visual separability between authentic Fuding and non-Fuding silver needle samples, whereas spectroscopic models correctly identified all blended samples. Variable importance in projection analysis revealed complementary contributions from UV-Vis chromophore-related features and NIR matrix-related information, while low-level UV-Vis-NIR fusion further improved blending detection.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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