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...

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Autores principales: Cubero, Sergio, Lee, Won Suk, Aleixos, Nuria, Albert, Francisco, Blasco, José
Formato: Artículo
Lenguaje:Inglés
Publicado: Springer 2021
Materias:
Acceso en línea:http://hdl.handle.net/20.500.11939/6960
https://link.springer.com/article/10.1007/s11947-016-1767-1
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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.
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spelling ReDivia69602025-04-25T14:48:00Z 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 color index Citrus canker Citrus decay Citrus huanglongbing Citrus postharvest N01 Agricultural engineering Q01 Food science and technology 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. 2021-01-12T08:18:04Z 2021-01-12T08:18:04Z 2016 article publishedVersion 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. 1935-5130 1935-5149 (eISSN) http://hdl.handle.net/20.500.11939/6960 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/ closedAccess Springer electronico
spellingShingle Citrus sorting
Quality inspection
Hyperspectral imaging
Citrus color index
Citrus canker
Citrus decay
Citrus huanglongbing
Citrus postharvest
N01 Agricultural engineering
Q01 Food science and technology
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 color index
Citrus canker
Citrus decay
Citrus huanglongbing
Citrus postharvest
N01 Agricultural engineering
Q01 Food science and technology
url http://hdl.handle.net/20.500.11939/6960
https://link.springer.com/article/10.1007/s11947-016-1767-1
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