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Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging

文献类型： 外文期刊

作者： Liu, Wei 1 ; Xu, Xue 3 ; Liu, Changhong 1 ; Zheng, Lei 1 ;

作者机构： 1.Hefei Univ Technol, Sch Food & Biol Engn, Hefei 230009, Peoples R China

2.Hefei Univ, Intelligent Control & Compute Vis Lab, Hefei 230601, Peoples R China

3.Anhui Acad Agr Sci, Rice Res Inst, Hefei 230031, Peoples R China

期刊名称：JOURNAL OF FOOD QUALITY （ 影响因子：2.45； 五年影响因子：2.679 ）

ISSN： 0146-9428

年卷期： 2021 年 2021 卷

页码：

收录情况： SCI

摘要： The detection of authenticity is essential to the development and management of Thai jasmine rice industry. In this study, the multispectral imaging system (405-970 nm) was used for the detection of adulteration in Thai jasmine rice combined with chemometric methods including principal component analysis (PCA), partial least squares (PLS), least squares-support vector machines (LS-SVM), and backpropagation neural network (BPNN). Three varieties of rice that were similar to Thai jasmine rice in appearance were selected to perform the classification and quantitative prediction experiments by multispectral images. For the classification experiment, four varieties of rice samples could be easily classified with accuracy achieved to 92% by the BPNN model. For the quantitative prediction of adulteration proportion experiments, the results showed that, among the different chemometric methods, LS-SVM achieved the best prediction performance comparing the results of coefficient of determination, root-mean-square error (RMSEP), bias, and residual predictive deviation (RPD). It can be concluded that multispectral imaging technology with chemometric methods can be applied in the rapid and nondestructive detection of authenticity of Thai jasmine rice.

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