Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopy
Abstract Apple moldy core is a fungus-infested disease that is extremely insidious, usually occurring inside the fruit, making it very difficult to distinguish from the exterior with the naked eye. Using VIS/NIR transmission spectroscopy, this study successfully detected moldy core apples. By combin...
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| Aineistotyyppi: | Artikkeli |
| Kieli: | English |
| Julkaistu: |
SpringerOpen
2024-04-01
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| Sarja: | Chemical and Biological Technologies in Agriculture |
| Aiheet: | |
| Linkit: | https://doi.org/10.1186/s40538-024-00588-8 |
| _version_ | 1827259667549519872 |
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| author | Xiaogang Jiang Kang Ge Zhi Liu Nan Chen Aiguo Ouyang Yande Liu Yuyang Huang Jinghu Li Mingmao Hu |
| author_facet | Xiaogang Jiang Kang Ge Zhi Liu Nan Chen Aiguo Ouyang Yande Liu Yuyang Huang Jinghu Li Mingmao Hu |
| author_sort | Xiaogang Jiang |
| collection | DOAJ |
| description | Abstract Apple moldy core is a fungus-infested disease that is extremely insidious, usually occurring inside the fruit, making it very difficult to distinguish from the exterior with the naked eye. Using VIS/NIR transmission spectroscopy, this study successfully detected moldy core apples. By combining four wavelength selection algorithms (CARS, CARS-SPA, MC-UVE, and MC-UVE-SPA) with four classifiers (SVM, ELM, KNN, and LDA-KNN), discrimination models were established for two-class and three-class classifications. MC-UVE-SPA-LDA-KNN achieved an AUC of 0.99 and an accuracy of 98.82% for two-class classification, while MC-UVE-SPA achieved an AUC of 0.99 and an accuracy of 97.64% for three-class classification. This confirms MC-UVE-SPA as an effective tool for selecting wavelengths specific to moldy core apples, facilitating precise identification and differentiation of apple states. This study advances dynamic online detection of early-stage moldy core conditions in apples, reducing post-harvest disease occurrence and preserving fruit quality effectively. Graphical Abstract |
| first_indexed | 2025-03-22T02:30:14Z |
| format | Article |
| id | doaj.art-f2038c3de5f24b7e87d38b6bb8d971b1 |
| institution | Directory Open Access Journal |
| issn | 2196-5641 |
| language | English |
| last_indexed | 2025-03-22T02:30:14Z |
| publishDate | 2024-04-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Chemical and Biological Technologies in Agriculture |
| spelling | doaj.art-f2038c3de5f24b7e87d38b6bb8d971b12024-05-05T11:09:33ZengSpringerOpenChemical and Biological Technologies in Agriculture2196-56412024-04-0111111210.1186/s40538-024-00588-8Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopyXiaogang Jiang0Kang Ge1Zhi Liu2Nan Chen3Aiguo Ouyang4Yande Liu5Yuyang Huang6Jinghu Li7Mingmao Hu8School of Mechatronics & Vehicle Engineering East, China Jiaotong UniversitySchool of Mechatronics & Vehicle Engineering East, China Jiaotong UniversitySchool of Mechatronics & Vehicle Engineering East, China Jiaotong UniversitySchool of Mechatronics & Vehicle Engineering East, China Jiaotong UniversitySchool of Mechatronics & Vehicle Engineering East, China Jiaotong UniversitySchool of Mechatronics & Vehicle Engineering East, China Jiaotong UniversitySuzhou Suna Optoelectronics Company LimitedXiamen Yixinyuan Semiconductor Technology Company LimitedSchool of Mechanical Engineering, Hubei University of Automotive TechnologyAbstract Apple moldy core is a fungus-infested disease that is extremely insidious, usually occurring inside the fruit, making it very difficult to distinguish from the exterior with the naked eye. Using VIS/NIR transmission spectroscopy, this study successfully detected moldy core apples. By combining four wavelength selection algorithms (CARS, CARS-SPA, MC-UVE, and MC-UVE-SPA) with four classifiers (SVM, ELM, KNN, and LDA-KNN), discrimination models were established for two-class and three-class classifications. MC-UVE-SPA-LDA-KNN achieved an AUC of 0.99 and an accuracy of 98.82% for two-class classification, while MC-UVE-SPA achieved an AUC of 0.99 and an accuracy of 97.64% for three-class classification. This confirms MC-UVE-SPA as an effective tool for selecting wavelengths specific to moldy core apples, facilitating precise identification and differentiation of apple states. This study advances dynamic online detection of early-stage moldy core conditions in apples, reducing post-harvest disease occurrence and preserving fruit quality effectively. Graphical Abstracthttps://doi.org/10.1186/s40538-024-00588-8Moldy coreTransmission spectroscopyOnline detectionWavelength selection |
| spellingShingle | Xiaogang Jiang Kang Ge Zhi Liu Nan Chen Aiguo Ouyang Yande Liu Yuyang Huang Jinghu Li Mingmao Hu Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopy Chemical and Biological Technologies in Agriculture Moldy core Transmission spectroscopy Online detection Wavelength selection |
| title | Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopy |
| title_full | Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopy |
| title_fullStr | Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopy |
| title_full_unstemmed | Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopy |
| title_short | Non-destructive online detection of early moldy core apples based on Vis/NIR transmission spectroscopy |
| title_sort | non destructive online detection of early moldy core apples based on vis nir transmission spectroscopy |
| topic | Moldy core Transmission spectroscopy Online detection Wavelength selection |
| url | https://doi.org/10.1186/s40538-024-00588-8 |
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