Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats
The ecological habitats of Chinese quince (Chaenomeles speciosa Nakai) fruits affect their phenotype. Currently, limited or no rapid method exists for classifying Chinese quince fruit from different ecosystems. This study developed a partial least squares discriminant analysis (PLS-DA) classificatio...
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Journal of Food Quality |
| Online Access: | http://dx.doi.org/10.1155/2024/6217243 |
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| author | Songfeng Diao Xiaoqian Tang Lin Huang Yanjie Li Xiongfei Fan Wenhao Shao |
| author_facet | Songfeng Diao Xiaoqian Tang Lin Huang Yanjie Li Xiongfei Fan Wenhao Shao |
| author_sort | Songfeng Diao |
| collection | DOAJ |
| description | The ecological habitats of Chinese quince (Chaenomeles speciosa Nakai) fruits affect their phenotype. Currently, limited or no rapid method exists for classifying Chinese quince fruit from different ecosystems. This study developed a partial least squares discriminant analysis (PLS-DA) classification model to effectively and nondestructively classify 663 Chinese quince fruit samples from six environments in 2020. PLS-DA models and other variable selection approaches were used in this study. The near-infrared spectroscopy (NIRs) absorption spectra of raw Chinese quince fruit samples from six habitats showed a similar shape. The spectra of each environment showed little variance. The raw fruit spectra varied significantly among habitat categories after the first derivative preprocessing phase. The uninformative variable elimination (UVE) variable selection approach had greater calibration and validation set specificity of 0.93 and 0.98. This study found the best classification specificity using the UVE variable selection approach compared to other methods including the PLS-DA model without variable selection. The UVE approach improved Yunnan habitat categorization specificity from 86% to 88% when integrated with PLS-DA. Additionally, the validation set for quinces originating from Anhui, Chongqing, Hubei, Shandong, and Zhejiang achieved an ideal classification score of 100%. The findings of the study indicated that PLS-DA can serve as an alternative approach for classifying the habitats of Chinese quince fruits. When used in conjunction with other methods, this technique can assist researchers, scientists, and industry professionals in identifying the main factors responsible for significant variations in the habitats, composition, and quality of Chinese quince fruits. |
| format | Article |
| id | doaj-art-a84df72a97354113abfd6824833bcc6f |
| institution | Kabale University |
| issn | 1745-4557 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Food Quality |
| spelling | doaj-art-a84df72a97354113abfd6824833bcc6f2025-08-20T03:38:54ZengWileyJournal of Food Quality1745-45572024-01-01202410.1155/2024/6217243Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different HabitatsSongfeng Diao0Xiaoqian Tang1Lin Huang2Yanjie Li3Xiongfei Fan4Wenhao Shao5Research Institute of Non-Timber ForestryScience and Technology Management DepartmentResearch Institute of Non-Timber ForestryInstitute of Subtropical Forestry Research of Chinese Academy of ForestryResearch Institute of Non-Timber ForestryInstitute of Subtropical Forestry Research of Chinese Academy of ForestryThe ecological habitats of Chinese quince (Chaenomeles speciosa Nakai) fruits affect their phenotype. Currently, limited or no rapid method exists for classifying Chinese quince fruit from different ecosystems. This study developed a partial least squares discriminant analysis (PLS-DA) classification model to effectively and nondestructively classify 663 Chinese quince fruit samples from six environments in 2020. PLS-DA models and other variable selection approaches were used in this study. The near-infrared spectroscopy (NIRs) absorption spectra of raw Chinese quince fruit samples from six habitats showed a similar shape. The spectra of each environment showed little variance. The raw fruit spectra varied significantly among habitat categories after the first derivative preprocessing phase. The uninformative variable elimination (UVE) variable selection approach had greater calibration and validation set specificity of 0.93 and 0.98. This study found the best classification specificity using the UVE variable selection approach compared to other methods including the PLS-DA model without variable selection. The UVE approach improved Yunnan habitat categorization specificity from 86% to 88% when integrated with PLS-DA. Additionally, the validation set for quinces originating from Anhui, Chongqing, Hubei, Shandong, and Zhejiang achieved an ideal classification score of 100%. The findings of the study indicated that PLS-DA can serve as an alternative approach for classifying the habitats of Chinese quince fruits. When used in conjunction with other methods, this technique can assist researchers, scientists, and industry professionals in identifying the main factors responsible for significant variations in the habitats, composition, and quality of Chinese quince fruits.http://dx.doi.org/10.1155/2024/6217243 |
| spellingShingle | Songfeng Diao Xiaoqian Tang Lin Huang Yanjie Li Xiongfei Fan Wenhao Shao Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats Journal of Food Quality |
| title | Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats |
| title_full | Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats |
| title_fullStr | Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats |
| title_full_unstemmed | Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats |
| title_short | Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats |
| title_sort | application of near infrared spectroscopy to rapidly classify the chinese quince fruits from different habitats |
| url | http://dx.doi.org/10.1155/2024/6217243 |
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