Geographical Origin and Nutrient Analysis of Plants Using Stable Isotopes and Chemometrics

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Nutrition".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 112

Special Issue Editors


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Guest Editor
Key Laboratory of Information Traceability for Agricultural Products, Ministry of Agriculture and Rural Affairs of China, Institute of Agro-Products Safety and Nutrition, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
Interests: stable isotopes; food authenticity; tea; rice
Institute for Agro-Food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
Interests: traceability and authenticity identification of agricultural product
School of Food Science and Technology, Shihezi University, Shihezi 832000, China
Interests: quality and traceability of featured foods
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Special Issue Information

Dear Colleagues,

Stable isotope analyses are popular tools for plant origin discrimination. It has been applied to geographical origin verification of plants such as crops, fruit, and tea. Stable isotope combined with chemometrics can effectively reveal the geographical origin and nutritional composition of plants, as well as the influence by environmental factors, providing a key scientific basis for agriculture, ecology, and food science fields. This Special Issue aims to gather the latest advances in the use of stable isotopes and chemometrics to study plant geographical origin and nutrient composition.

The theme covers, but is not limited to, the following directions:

  1. Application of stable isotopes in plant geographic origin and/or nutritional analysis, including authenticity identification of plant-based foods;
  2. The relationship between plant stable isotopes and/or nutrients and environmental factors;
  3. Application and optimization of chemometrics in plant geographic origin and/or nutritional analysis.

We welcome you to actively submit a manuscript!

Dr. Chunlin Li
Dr. Xing Liu
Dr. Feifei Gao
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Plants is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • authenticity
  • geographical origin
  • stable isotope
  • nutrient analysis
  • chemometrics
  • plant
  • environmental factors

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Published Papers (1 paper)

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Research

17 pages, 2529 KB  
Article
Stable Isotope and Elemental Characteristics for Origin Identification of Rice from China and Thailand
by Xiaofan Xing, Fengmei Sun, Weigui Zhang, Weixing Zhang, Yongzhi Zhang, Karyne M. Rogers, Chunlin Li and Yuwei Yuan
Plants 2026, 15(1), 42; https://doi.org/10.3390/plants15010042 - 23 Dec 2025
Abstract
China, as the primary importer of Thailand’s high-quality rice (Oryza sativa L.), has an urgent need for effective origin discrimination methods between premium aromatic rice from China and Thailand to prevent origin mislabeling issues. In this study, stable isotope and elemental multivariate [...] Read more.
China, as the primary importer of Thailand’s high-quality rice (Oryza sativa L.), has an urgent need for effective origin discrimination methods between premium aromatic rice from China and Thailand to prevent origin mislabeling issues. In this study, stable isotope and elemental multivariate analysis combined with partial least squares discriminant analysis (PLS-DA) were used to build an origin traceability model for Chinese and Thai rice from different production areas. Multivariate analysis of variance revealed that Thai rice exhibited significantly higher δ13C (−26.4 ± 0.4‰) and δ18O (25.9 ± 1.1‰) values, but a significantly lower δ15N value (3.5 ± 0.8‰) compared to the three major producing regions of China. These differences are directly related to geographical and climatic factors such as latitude, precipitation, and temperature. A PLS-DA model demonstrated high performance in the classification of different Chinese indica rice and Thailand rice origins. Through cross-validation, the classification accuracy for the training set reached 97.3%. For the independent testing set, the classification accuracy was recorded to be 95.0%. Furthermore, external blind sample verification was conducted, and the classification accuracy achieved was 100%. Ca, K, Na, δ18O, Zn and δ2H were found to be important variables to discriminate between Chinese indica rice and Thai rice. Finally, for country of origin labelling claims, this rice study provides the basis for a suitable regulatory method to detect mislabeled Thai origin rice and prevent fraud. Full article
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