Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest
Citrus fungal infections developing during fruit storage and transportation can cause significant economic losses after harvest. The most important is caused by the fungus Penicillium digitatum, which infects the fruit through rind wounds and causes a rot lesion. The symptoms of decay are difficult...
| Autores principales: | , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/20.500.11939/8714 https://www.sciencedirect.com/science/article/abs/pii/S0925521423002296 |
| _version_ | 1855492545185841152 |
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| author | Munera, Sandra Ancillo, Gema Prieto, Andrés Palou, Lluís Aleixos, Nuria Cubero, Sergio Blasco, José |
| author_browse | Aleixos, Nuria Ancillo, Gema Blasco, José Cubero, Sergio Munera, Sandra Palou, Lluís Prieto, Andrés |
| author_facet | Munera, Sandra Ancillo, Gema Prieto, Andrés Palou, Lluís Aleixos, Nuria Cubero, Sergio Blasco, José |
| author_sort | Munera, Sandra |
| collection | ReDivia |
| description | Citrus fungal infections developing during fruit storage and transportation can cause significant economic losses after harvest. The most important is caused by the fungus Penicillium digitatum, which infects the fruit through rind wounds and causes a rot lesion. The symptoms of decay are difficult to notice by the human eye in the initial stages of decay development because the colour of the lesion is very similar to that of the healthy rind. One method to detect this disease early is to illuminate the fruit with ultraviolet (UV) light since the disease causes visible fluorescence. Manual inspection exposes the workers to UV light, which is dangerous for their skin and eyes. An alternative is to use artificial vision systems. But not all varieties show the same level of fluorescence, and even some do not produce this phenomenon, making it challenging to create effective automatic detection systems based on image analysis. This work has studied and determined the fluorescence level of 104 varieties of oranges and mandarins using hyperspectral and colour imaging. The samples were inoculated with spores of the P. digitatum in controlled conditions. Images were captured exposing the fruit under UV light (380 nm) using a colour camera and a hyperspectral imaging system. The fluorescence level of each variety was measured using three colour coordinates and the hyperspectral images. Best correlations between the spectral and the colour-based systems were achieved using the green (G) colour coordinate of the RGB colour space (R2 =0.85). Navel and common oranges emit the most fluorescence, while 16 varieties (mostly blood oranges and other mandarins) have very low or undetectable fluorescence. |
| format | Artículo |
| id | ReDivia8714 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | ReDivia87142025-04-25T14:49:21Z Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest Munera, Sandra Ancillo, Gema Prieto, Andrés Palou, Lluís Aleixos, Nuria Cubero, Sergio Blasco, José Fruit storage Hyperspectral imaging Colour imaging Detection H20 Plant diseases J10 Handling, transport, storage and protection of agricultural products Q02 Food processing and preservation N20 Agricultural machinery and equipment Citrus Fungal diseases Postharvest diseases Penicillium digitatum Fluorescence Citrus fungal infections developing during fruit storage and transportation can cause significant economic losses after harvest. The most important is caused by the fungus Penicillium digitatum, which infects the fruit through rind wounds and causes a rot lesion. The symptoms of decay are difficult to notice by the human eye in the initial stages of decay development because the colour of the lesion is very similar to that of the healthy rind. One method to detect this disease early is to illuminate the fruit with ultraviolet (UV) light since the disease causes visible fluorescence. Manual inspection exposes the workers to UV light, which is dangerous for their skin and eyes. An alternative is to use artificial vision systems. But not all varieties show the same level of fluorescence, and even some do not produce this phenomenon, making it challenging to create effective automatic detection systems based on image analysis. This work has studied and determined the fluorescence level of 104 varieties of oranges and mandarins using hyperspectral and colour imaging. The samples were inoculated with spores of the P. digitatum in controlled conditions. Images were captured exposing the fruit under UV light (380 nm) using a colour camera and a hyperspectral imaging system. The fluorescence level of each variety was measured using three colour coordinates and the hyperspectral images. Best correlations between the spectral and the colour-based systems were achieved using the green (G) colour coordinate of the RGB colour space (R2 =0.85). Navel and common oranges emit the most fluorescence, while 16 varieties (mostly blood oranges and other mandarins) have very low or undetectable fluorescence. 2023-09-21T07:32:24Z 2023-09-21T07:32:24Z 2023 article publishedVersion Munera, S., Ancillo, G., Prieto, A., Palou, L., Aleixos, N., Cubero, S., & Blasco, J. (2023). Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest. Postharvest Biology and Technology, 204, 112468. 0925-5214 (Print ISSN) 1873-2356 (Online ISSN) https://hdl.handle.net/20.500.11939/8714 10.1016/j.postharvbio.2023.112468 https://www.sciencedirect.com/science/article/abs/pii/S0925521423002296 en This work was partially funded by projects AEI PID2019-107347RR-C31 and C32 with ERDF funds of the GVA 2021–2027, and GVA-PROMETEO CIPROM/2021/014. Andres Prieto thanks INIA for the FPI-INIA grant BES-2017-082419, partially supported by ESF. Sandra Munera thanks the Juan de la Cierva-Formación (FJC2021-047786-I), co-funded by MCIN/AEI/10.13039/501100011033 and NextGenerationEU /PRTR. info:eu-repo/grantAgreement/AEI/Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i/PID2019-107347RR-C31/ES/INSPECCION NO DESTRUCTIVA Y PREDICCION DE LA CALIDAD INTERNA Y PROPIEDADES DE LAS FRUTAS MEDIANTE ESPECTROSCOPIA VIS/NIR Y MODELOS BASADOS EN APRENDIZAJE PROFUNDO info:eu-repo/grantAgreement/AEI/Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i/PID2019-107347RR-C32/ES/INSPECCION Y PREDICCION NO DESTRUCTIVA DE CALIDAD INTERNA Y PROPIEDADES DE FRUTAS UTILIZANDO IMAGEN HIPERESPECTRAL VIS/NIR UTILIZANDO MODELOS BASADOS EN APRENDIZAJE PROFUNDO Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ openAccess Elsevier electronico |
| spellingShingle | Fruit storage Hyperspectral imaging Colour imaging Detection H20 Plant diseases J10 Handling, transport, storage and protection of agricultural products Q02 Food processing and preservation N20 Agricultural machinery and equipment Citrus Fungal diseases Postharvest diseases Penicillium digitatum Fluorescence Munera, Sandra Ancillo, Gema Prieto, Andrés Palou, Lluís Aleixos, Nuria Cubero, Sergio Blasco, José Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest |
| title | Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest |
| title_full | Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest |
| title_fullStr | Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest |
| title_full_unstemmed | Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest |
| title_short | Quantifying the ultraviolet-induced fluorescence intensity in green mould lesions of diverse citrus varieties: Towards automated detection of citrus decay in postharvest |
| title_sort | quantifying the ultraviolet induced fluorescence intensity in green mould lesions of diverse citrus varieties towards automated detection of citrus decay in postharvest |
| topic | Fruit storage Hyperspectral imaging Colour imaging Detection H20 Plant diseases J10 Handling, transport, storage and protection of agricultural products Q02 Food processing and preservation N20 Agricultural machinery and equipment Citrus Fungal diseases Postharvest diseases Penicillium digitatum Fluorescence |
| url | https://hdl.handle.net/20.500.11939/8714 https://www.sciencedirect.com/science/article/abs/pii/S0925521423002296 |
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