Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging
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 ana...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Food Quality |
| Online Access: | http://dx.doi.org/10.1155/2021/6642220 |
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| _version_ | 1832564881724801024 |
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| author | Wei Liu Xue Xu Changhong Liu Lei Zheng |
| author_facet | Wei Liu Xue Xu Changhong Liu Lei Zheng |
| author_sort | Wei Liu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-4606f898e5a8451fbcf236d62afe2a75 |
| institution | Kabale University |
| issn | 0146-9428 1745-4557 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Food Quality |
| spelling | doaj-art-4606f898e5a8451fbcf236d62afe2a752025-02-03T01:09:55ZengWileyJournal of Food Quality0146-94281745-45572021-01-01202110.1155/2021/66422206642220Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral ImagingWei Liu0Xue Xu1Changhong Liu2Lei Zheng3School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, ChinaRice Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, ChinaSchool of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, ChinaSchool of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, ChinaThe 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.http://dx.doi.org/10.1155/2021/6642220 |
| spellingShingle | Wei Liu Xue Xu Changhong Liu Lei Zheng Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging Journal of Food Quality |
| title | Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging |
| title_full | Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging |
| title_fullStr | Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging |
| title_full_unstemmed | Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging |
| title_short | Nondestructive Detection of Authenticity of Thai Jasmine Rice Using Multispectral Imaging |
| title_sort | nondestructive detection of authenticity of thai jasmine rice using multispectral imaging |
| url | http://dx.doi.org/10.1155/2021/6642220 |
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