Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods
ABSTRACTThe red jujube quality is closely associated with its place of origin. In order to quickly and easily identify the geographical origin of red jujube, the classification of red jujube samples’ near-infrared reflectance (NIR) spectra was performed using several fuzzy clustering methods in comb...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | International Journal of Food Properties |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10942912.2023.2281883 |
| _version_ | 1797385982140481536 |
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| author | Caiping Hu Hongjia Xu Zhaoming Fu Bin Wu Rui Zhang Chenhong Zhi |
| author_facet | Caiping Hu Hongjia Xu Zhaoming Fu Bin Wu Rui Zhang Chenhong Zhi |
| author_sort | Caiping Hu |
| collection | DOAJ |
| description | ABSTRACTThe red jujube quality is closely associated with its place of origin. In order to quickly and easily identify the geographical origin of red jujube, the classification of red jujube samples’ near-infrared reflectance (NIR) spectra was performed using several fuzzy clustering methods in combination with principal component analysis (PCA) and linear discriminant analysis (LDA). Firstly, a NIR-M-R2 portable near-infrared spectrometer was used to collect four varieties of red jujube samples from four representative producing areas in four provinces: Gansu, Henan, Shanxi and Xinjiang in China. Each variety corresponded to a producing area, and it had 60 samples with a total of 240 samples. Near-infrared spectra of red jujube were acquired using a NIR-M-R2 portable near-infrared spectrometer, and the initial near-infrared spectra were preprocessed by Savitzky-Golay (SG) filtering. Secondly, PCA and LDA were used to further process the NIR data for dimension reduction and feature extraction, respectively. Finally, red jujube samples were classified by fuzzy C-means (FCM) clustering, Gustafson-Kessel (GK) clustering and possibility fuzzy C-means (PFCM) clustering. When GK served as the clustering algorithm, the clustering accuracy was the highest, as the value of 98.8%. Based on the experimental results, it was evident that the GK clustering algorithm played a significant role in identifying the place of origin of red jujube with near-infrared spectroscopy. |
| first_indexed | 2024-03-08T22:03:24Z |
| format | Article |
| id | doaj.art-91ed7fb06edf412496f7ef8c6013d892 |
| institution | Directory Open Access Journal |
| issn | 1094-2912 1532-2386 |
| language | English |
| last_indexed | 2024-03-08T22:03:24Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Food Properties |
| spelling | doaj.art-91ed7fb06edf412496f7ef8c6013d8922023-12-19T10:46:33ZengTaylor & Francis GroupInternational Journal of Food Properties1094-29121532-23862023-12-012623275329010.1080/10942912.2023.2281883Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methodsCaiping Hu0Hongjia Xu1Zhaoming Fu2Bin Wu3Rui Zhang4Chenhong Zhi5School of Computer Engineering, Jinling Institute of Technology, Nanjing, ChinaDepartment of Electrical and Information Engineering, Jingjiang College of Jiangsu University, Zhenjiang, ChinaDepartment of Electrical and Information Engineering, Jingjiang College of Jiangsu University, Zhenjiang, ChinaDepartment of Information Engineering, ChuZhou Polytechnic, Chuzhou, ChinaDepartment of Electrical and Information Engineering, Jingjiang College of Jiangsu University, Zhenjiang, ChinaDepartment of Electrical and Information Engineering, Jingjiang College of Jiangsu University, Zhenjiang, ChinaABSTRACTThe red jujube quality is closely associated with its place of origin. In order to quickly and easily identify the geographical origin of red jujube, the classification of red jujube samples’ near-infrared reflectance (NIR) spectra was performed using several fuzzy clustering methods in combination with principal component analysis (PCA) and linear discriminant analysis (LDA). Firstly, a NIR-M-R2 portable near-infrared spectrometer was used to collect four varieties of red jujube samples from four representative producing areas in four provinces: Gansu, Henan, Shanxi and Xinjiang in China. Each variety corresponded to a producing area, and it had 60 samples with a total of 240 samples. Near-infrared spectra of red jujube were acquired using a NIR-M-R2 portable near-infrared spectrometer, and the initial near-infrared spectra were preprocessed by Savitzky-Golay (SG) filtering. Secondly, PCA and LDA were used to further process the NIR data for dimension reduction and feature extraction, respectively. Finally, red jujube samples were classified by fuzzy C-means (FCM) clustering, Gustafson-Kessel (GK) clustering and possibility fuzzy C-means (PFCM) clustering. When GK served as the clustering algorithm, the clustering accuracy was the highest, as the value of 98.8%. Based on the experimental results, it was evident that the GK clustering algorithm played a significant role in identifying the place of origin of red jujube with near-infrared spectroscopy.https://www.tandfonline.com/doi/10.1080/10942912.2023.2281883red jujubenear-infrared spectroscopylinear discriminant analysisfuzzy C-meansfuzzy clustering algorithmGustafson-kessel |
| spellingShingle | Caiping Hu Hongjia Xu Zhaoming Fu Bin Wu Rui Zhang Chenhong Zhi Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods International Journal of Food Properties red jujube near-infrared spectroscopy linear discriminant analysis fuzzy C-means fuzzy clustering algorithm Gustafson-kessel |
| title | Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods |
| title_full | Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods |
| title_fullStr | Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods |
| title_full_unstemmed | Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods |
| title_short | Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods |
| title_sort | non destructive identification of the geographical origin of red jujube by near infrared spectroscopy and fuzzy clustering methods |
| topic | red jujube near-infrared spectroscopy linear discriminant analysis fuzzy C-means fuzzy clustering algorithm Gustafson-kessel |
| url | https://www.tandfonline.com/doi/10.1080/10942912.2023.2281883 |
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