APPLICATION OF SPECTROSCOPIC METHODS FOR THE AUTHENTICATION OF AGRICULTURAL PRODUCTS OF VIETNAM: A STUDY OF ST25 RICE=APPLICATION OF SPECTROSCOPIC METHODS FOR THE AUTHENTICATION OF AGRICULTURAL PRODUCTS OF VIETNAM: A STUDY OF ST25 RICE

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Tác giả: Thu Thuy Bui, Quynh Hoa Nguyen, Thi Mai Huong To

Ngôn ngữ: eng

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Thông tin xuất bản: Tạp chí Khoa học - Trường Đại học Sư phạm Hà Nội: Khoa học Tự nhiên, 2024

Mô tả vật lý: tr.154

Bộ sưu tập: Metadata

ID: 246700

Food fraud, particularly in staple commodities like rice, poses significantrisks to trademark protection as well as economic challenges. In this study, weexplored the efficacy of Raman spectroscopy in differentiating authentic ST25rice—a premium variety of Vietnam from other rice types, amidst concerns ofadulteration. By utilizing both backscattering and transmission Raman spectroscopy,a total of 125 rice samples consisting of both commercial rice and Vietnameselandrace rice varieties were analyzed. All samples were categorized into two maingroups namely ST25 and Non-ST25 for the construction of the classification model.Through principal component analysis (PCA) and k-nearest neighbors (kNN)classification method, we achieved classification accuracies of 81.58% forbackscattering data and up to 97.37% for transmission data at elevated temperatures.Our findings highlight the efficacy of Raman spectroscopy for rice authenticityverification, nevertheless, modification in spectral measurement schemes isnecessary to obtain better method reproducibility as well as to maintain highdiscriminatory accuracy of the classification model.Food fraud, particularly in staple commodities like rice, poses significantrisks to trademark protection as well as economic challenges. In this study, weexplored the efficacy of Raman spectroscopy in differentiating authentic ST25rice—a premium variety of Vietnam from other rice types, amidst concerns ofadulteration. By utilizing both backscattering and transmission Raman spectroscopy,a total of 125 rice samples consisting of both commercial rice and Vietnameselandrace rice varieties were analyzed. All samples were categorized into two maingroups namely ST25 and Non-ST25 for the construction of the classification model.Through principal component analysis (PCA) and k-nearest neighbors (kNN)classification method, we achieved classification accuracies of 81.58% forbackscattering data and up to 97.37% for transmission data at elevated temperatures.Our findings highlight the efficacy of Raman spectroscopy for rice authenticityverification, nevertheless, modification in spectral measurement schemes isnecessary to obtain better method reproducibility as well as to maintain highdiscriminatory accuracy of the classification model.
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