Scholarlink

<p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 发表日期：

    2025年1月10日

查看全文
  • Baiyao Ding,
  • Yan Shi,
  • Lei Wang,
  • ZhiQiang Liu,
  • Shan Wang,
  • Hongtao Zhao

摘要

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.