Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers
Green mold (Penicillium digitatum) and blue mold (Penicillium italicum) are important sources of postharvest decay affecting the commercialization of mandarins. These fungi infections produce enormous economic losses in mandarin production if early detection is not carried out. Nowadays, this detect...
| Autores principales: | , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2017
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| Acceso en línea: | http://hdl.handle.net/20.500.11939/5313 |
| _version_ | 1855491904304578560 |
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| author | Gómez-Sanchís, Juan Blasco, José Soria-Olivas, Emilio Lorente, Delia Escandell-Montero, P. Martínez-Martínez, José M. Martinez-Sober, Marcelino Aleixos, Nuria |
| author_browse | Aleixos, Nuria Blasco, José Escandell-Montero, P. Gómez-Sanchís, Juan Lorente, Delia Martinez-Sober, Marcelino Martínez-Martínez, José M. Soria-Olivas, Emilio |
| author_facet | Gómez-Sanchís, Juan Blasco, José Soria-Olivas, Emilio Lorente, Delia Escandell-Montero, P. Martínez-Martínez, José M. Martinez-Sober, Marcelino Aleixos, Nuria |
| author_sort | Gómez-Sanchís, Juan |
| collection | ReDivia |
| description | Green mold (Penicillium digitatum) and blue mold (Penicillium italicum) are important sources of postharvest decay affecting the commercialization of mandarins. These fungi infections produce enormous economic losses in mandarin production if early detection is not carried out. Nowadays, this detection is performed manually in dark chambers, where the fruit is illuminated by ultraviolet light to produce fluorescence, which is potentially dangerous for humans. This paper documents a new methodology based on hyperspectral imaging and advanced machine-learning techniques (artificial neural networks and classification and regression trees) for the segmentation and classification of images of citrus free of damage and affected by green mold and blue mold. Feature selection methods are used in order to reduce the dimensionality of the hyperspectral images and determine the 10 most relevant. Neural Networks were used to segment the hyperspectral images. Result's achieved using classifiers based on decision trees show an accuracy of around 93% in the problem of decay classification. |
| format | Artículo |
| id | ReDivia5313 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| record_format | dspace |
| spelling | ReDivia53132025-04-25T14:42:01Z Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers Gómez-Sanchís, Juan Blasco, José Soria-Olivas, Emilio Lorente, Delia Escandell-Montero, P. Martínez-Martínez, José M. Martinez-Sober, Marcelino Aleixos, Nuria Green mold (Penicillium digitatum) and blue mold (Penicillium italicum) are important sources of postharvest decay affecting the commercialization of mandarins. These fungi infections produce enormous economic losses in mandarin production if early detection is not carried out. Nowadays, this detection is performed manually in dark chambers, where the fruit is illuminated by ultraviolet light to produce fluorescence, which is potentially dangerous for humans. This paper documents a new methodology based on hyperspectral imaging and advanced machine-learning techniques (artificial neural networks and classification and regression trees) for the segmentation and classification of images of citrus free of damage and affected by green mold and blue mold. Feature selection methods are used in order to reduce the dimensionality of the hyperspectral images and determine the 10 most relevant. Neural Networks were used to segment the hyperspectral images. Result's achieved using classifiers based on decision trees show an accuracy of around 93% in the problem of decay classification. 2017-06-01T10:12:07Z 2017-06-01T10:12:07Z 2013 AUG 2013 article Gomez-Sanchis, J., Blasco, J., Soria-Olivas, E., Lorente, D., Escandell-Montero, P., Martinez-Martinez, J.M., Martinez-Sober, M., Aleixos, N. (2013). Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers. Postharvest Biology and Technology, 82, 76-86. 0925-5214 http://hdl.handle.net/20.500.11939/5313 10.1016/j.postharvbio.2013.02.011 en openAccess Impreso |
| spellingShingle | Gómez-Sanchís, Juan Blasco, José Soria-Olivas, Emilio Lorente, Delia Escandell-Montero, P. Martínez-Martínez, José M. Martinez-Sober, Marcelino Aleixos, Nuria Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers |
| title | Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers |
| title_full | Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers |
| title_fullStr | Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers |
| title_full_unstemmed | Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers |
| title_short | Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers |
| title_sort | hyperspectral lctf based system for classification of decay in mandarins caused by penicillium digitatum and penicillium italicum using the most relevant bands and non linear classifiers |
| url | http://hdl.handle.net/20.500.11939/5313 |
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