Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision
The presence of minor compounds in virgin olive oils has been proven to play multiple positive roles in health protection, encouraging its production. The key factors that influence the oil quality are ripening stages and the state of health of the fruit. For this reason, at the oil mill’s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/18/11/3826 |
| _version_ | 1811299489995030528 |
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| author | Javiera Navarro Soto Silvia Satorres Martínez Diego Martínez Gila Juan Gómez Ortega Javier Gámez García |
| author_facet | Javiera Navarro Soto Silvia Satorres Martínez Diego Martínez Gila Juan Gómez Ortega Javier Gámez García |
| author_sort | Javiera Navarro Soto |
| collection | DOAJ |
| description | The presence of minor compounds in virgin olive oils has been proven to play multiple positive roles in health protection, encouraging its production. The key factors that influence the oil quality are ripening stages and the state of health of the fruit. For this reason, at the oil mill’s reception yard, fruits are visually inspected and separated according to their external appearance. In this way, the process parameters can be better adjusted to improve the quantity and/or quality of olive oil. This paper presents a proposal to automatically determine the oil quality before being produced from a previous inspection of the incoming fruits. Expert assessment of the fruit conditions guided the image processing. The proposal has been validated through the analysis of 74 batches of olives coming from an oil mill. Best correlation results between the image processing and the analytical data were found in the acidity index, peroxide values, ethyl ester, polyphenols, chlorophylls, and carotenoids. |
| first_indexed | 2024-04-13T06:35:41Z |
| format | Article |
| id | doaj.art-8da8aee5d41845d49c41bd258a203e4a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:35:41Z |
| publishDate | 2018-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8da8aee5d41845d49c41bd258a203e4a2022-12-22T02:57:55ZengMDPI AGSensors1424-82202018-11-011811382610.3390/s18113826s18113826Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer VisionJaviera Navarro Soto0Silvia Satorres Martínez1Diego Martínez Gila2Juan Gómez Ortega3Javier Gámez García4Robotics, Automation and Computer Vision Group, Electronic and Automation Engineering Department, University of Jaen, ES-23071 Jaen, SpainRobotics, Automation and Computer Vision Group, Electronic and Automation Engineering Department, University of Jaen, ES-23071 Jaen, SpainRobotics, Automation and Computer Vision Group, Electronic and Automation Engineering Department, University of Jaen, ES-23071 Jaen, SpainRobotics, Automation and Computer Vision Group, Electronic and Automation Engineering Department, University of Jaen, ES-23071 Jaen, SpainRobotics, Automation and Computer Vision Group, Electronic and Automation Engineering Department, University of Jaen, ES-23071 Jaen, SpainThe presence of minor compounds in virgin olive oils has been proven to play multiple positive roles in health protection, encouraging its production. The key factors that influence the oil quality are ripening stages and the state of health of the fruit. For this reason, at the oil mill’s reception yard, fruits are visually inspected and separated according to their external appearance. In this way, the process parameters can be better adjusted to improve the quantity and/or quality of olive oil. This paper presents a proposal to automatically determine the oil quality before being produced from a previous inspection of the incoming fruits. Expert assessment of the fruit conditions guided the image processing. The proposal has been validated through the analysis of 74 batches of olives coming from an oil mill. Best correlation results between the image processing and the analytical data were found in the acidity index, peroxide values, ethyl ester, polyphenols, chlorophylls, and carotenoids.https://www.mdpi.com/1424-8220/18/11/3826olivefruitolive oilcomputer visionolive oil production process |
| spellingShingle | Javiera Navarro Soto Silvia Satorres Martínez Diego Martínez Gila Juan Gómez Ortega Javier Gámez García Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision Sensors olive fruit olive oil computer vision olive oil production process |
| title | Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision |
| title_full | Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision |
| title_fullStr | Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision |
| title_full_unstemmed | Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision |
| title_short | Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision |
| title_sort | fast and reliable determination of virgin olive oil quality by fruit inspection using computer vision |
| topic | olive fruit olive oil computer vision olive oil production process |
| url | https://www.mdpi.com/1424-8220/18/11/3826 |
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