Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10953/2119
Título: Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision
Autoría: Navarro Soto, Javiera
Satorres Martínez, Silvia
Martínez Gila, Diego Manuel
Gómez Ortega, Juan
Gámez García, Javier
Resumen: 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.
Palabras clave: olive
fruit
olive oil
computer vision
olive oil production process
Fecha: 5-nov-2018
Patrocinador: DPI2016-78290-R.
Editorial: MDPI
Citación: Soto, J. N., Martínez, S. S., Gila, D. M., Ortega, J. G., García, J. G., Navarro Soto, J., Satorres Martínez, S., Martínez Gila, D., Gómez Ortega, J., & Gámez García, J. (2018). Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision. Sensors 2018, Vol. 18, Page 3826, 18(11), 3826. https://doi.org/10.3390/S18113826
Aparece en las colecciones: DIEA-Artículos

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