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Khoa học tự nhiên

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Nguyen Quynh Hoa, Bui Thu Thuy, To Thi Mai Huong; Tô Thị Mai Hương(1); 

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

Tạp chí Khoa học - Trường Đại học Sư phạm Hà Nội: Khoa học Tự nhiên

2024

69

154

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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