The research on the traceability of the origin of rice in certain regions of China using ED-XRF technology combined with chemometrics

Abstract

Rice, as the staple food for more than half of the world’s population, exhibits significant differences in quality due to the influence of rice varieties, geographical environments, and cultivation methods. Unfortunately, some unscrupulous merchants engage in fraudulent activities by substituting inferior goods for high-quality ones driven by their own interests, making it crucial to establish a rapid and convenient method for tracing the origin of rice. This study utilized Energy Dispersive X-ray Fluorescence Spectrometry (ED-XRF) technology to analyze and measure the mineral elements in rice. Analysis of Variance (ANOVA) was employed to identify eight mineral elements with significant differences: P, S, K, Cl, Mn, Fe, Cu, and Zn. By utilizing the characteristics of these mineral elements, a model for tracing the origin of rice was established using chemometrics. The chemometric analysis indicates that Principal Component Linear Discriminant Analysis (PCA-LDA) is the optimal method, achieving a classification accuracy of 96.6% for rice from different origins, with a leave-one-out cross-validation accuracy of 90.8%. The classification accuracies for Linear Discriminant Analysis (LDA) and Random Forest algorithms are 94.3% and 89.7%, respectively, with leave-one-out cross-validation accuracies of 86.2% and 85.1%. This research provides a new method for tracing the origin of rice and combating counterfeit and inferior rice.