Stable Isotope and Elemental Characteristics for Origin Identification of Rice from China and Thailand

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 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.