Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review
Computer vision systems are becoming a scientific but also a commercial tool for food quality assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used f...
| Autores principales: | , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2020
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/6349 https://link.springer.com/article/10.1007/s11947-016-1767-1 |
| _version_ | 1855492066937667584 |
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| author | Cubero, Sergio Lee, Won Suk Aleixos, Nuria Albert, Francisco Blasco, José |
| author_browse | Albert, Francisco Aleixos, Nuria Blasco, José Cubero, Sergio Lee, Won Suk |
| author_facet | Cubero, Sergio Lee, Won Suk Aleixos, Nuria Albert, Francisco Blasco, José |
| author_sort | Cubero, Sergio |
| collection | ReDivia |
| description | Computer vision systems are becoming a scientific but also a commercial tool for food quality assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used for the automated inspection of the external quality of the fruits and for sorting them into commercial categories at very high speed. More recently, the use of hyperspectral imaging is allowing the detection of not only defects in the skin of the fruits but also their association to certain diseases of particular importance. In the research works that use this technology, wavelengths that play a significant role in detecting some of these dangerous diseases are found, leading to the development of multispectral imaging systems that can be used in industry. This article reviews recent works that use colour and non-standard computer vision systems for the automated inspection of citrus. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of internal and external features of these fruits. Particular attention is paid to inspection for the early detection of some dangerous diseases like citrus canker, black spot, decay or citrus Huanglongbing. |
| format | Artículo |
| id | ReDivia6349 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | ReDivia63492025-04-25T14:46:53Z Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review Cubero, Sergio Lee, Won Suk Aleixos, Nuria Albert, Francisco Blasco, José Citrus sorting Quality inspection Hyperspectral imaging Citrus colour index Citrus canker Citrus decay Citrus Huanglongbing Citrus postharvest H20 Plant diseases Computer vision systems are becoming a scientific but also a commercial tool for food quality assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used for the automated inspection of the external quality of the fruits and for sorting them into commercial categories at very high speed. More recently, the use of hyperspectral imaging is allowing the detection of not only defects in the skin of the fruits but also their association to certain diseases of particular importance. In the research works that use this technology, wavelengths that play a significant role in detecting some of these dangerous diseases are found, leading to the development of multispectral imaging systems that can be used in industry. This article reviews recent works that use colour and non-standard computer vision systems for the automated inspection of citrus. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of internal and external features of these fruits. Particular attention is paid to inspection for the early detection of some dangerous diseases like citrus canker, black spot, decay or citrus Huanglongbing. 2020-03-23T11:22:14Z 2020-03-23T11:22:14Z 2016 article acceptedVersion Cubero, S., Lee, W. S., Aleixos, N., Albert, F., & Blasco, J. (2016). Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest—a review. Food and Bioprocess Technology, 9(10), 1623-1639. 1935-5149 http://hdl.handle.net/20.500.11939/6349 10.1007/s11947-016-1767-1 https://link.springer.com/article/10.1007/s11947-016-1767-1 en Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Springer electronico |
| spellingShingle | Citrus sorting Quality inspection Hyperspectral imaging Citrus colour index Citrus canker Citrus decay Citrus Huanglongbing Citrus postharvest H20 Plant diseases Cubero, Sergio Lee, Won Suk Aleixos, Nuria Albert, Francisco Blasco, José Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review |
| title | Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review |
| title_full | Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review |
| title_fullStr | Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review |
| title_full_unstemmed | Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review |
| title_short | Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review |
| title_sort | automated systems based on machine vision for inspecting citrus fruits from the field to postharvest a review |
| topic | Citrus sorting Quality inspection Hyperspectral imaging Citrus colour index Citrus canker Citrus decay Citrus Huanglongbing Citrus postharvest H20 Plant diseases |
| url | http://hdl.handle.net/20.500.11939/6349 https://link.springer.com/article/10.1007/s11947-016-1767-1 |
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