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dc.contributor.authorNoguera, Miguel
dc.contributor.authorMillán Prior, Borja 
dc.contributor.authorAquino Martín, Arturo 
dc.contributor.authorAndújar Márquez, José Manuel
dc.identifier.citationNoguera, M., Millan, B., Aquino, A., & Andújar, J. M. (2022). Methodology for Olive Fruit Quality Assessment by Means of a Low-Cost Multispectral Device. In Agronomy (Vol. 12, Issue 5, p. 979). MDPI AG.
dc.identifier.issn2073-4395 (electrónico)
dc.description.abstractThe standard methods for determining the quality of olives involve chemical methods that are time-consuming and expensive. These limitations lead growers to homogeneous harvesting based on subjective criteria such as intuition and visual decisions. In recent times, precision agriculture techniques for fruit quality assessment, such as spectroscopy, have been introduced. However, they require expensive equipment, which limit their use to olive mills. This work presents a complete methodology based on a new low-cost multispectral sensor for assessing quality parameters of intact olive fruits. A set of 507 olive samples were analyzed with the proposed device. After data pre-processing, artificial neural network (ANN) models were trained using the 18 reflectance signals acquired by the sensor as input and three olive quality indicators (moisture, acidity, and fat content) as targets. The responses of the ANN models were promising, reaching coefficient-of-determination values of 0.78, 0.86, and 0.62 for fruit moisture, acidity, and fat content, respectively. These results show the suitability of the proposed device for assessing the quality status of intact olive fruits. Its performance, along with its low cost and ease of use, paves the way for the implementation of an olive fruit quality appraisal system that is more affordable for olive growerses_ES
dc.description.sponsorshipThis work was supported by grant PID2020-119217RA-I00 funded by MCIN/AEI/ 10.13039/ 501100011033, and grant IJC2019-040114-I funded by MCIN/AEI/ 10.13039/501100011033, and also by project TIColiVA with grant P18-RTJ-4539 funded by the Regional Government of Andalusia through the “PAIDI, Plan Andaluz de Investigación, Desarrollo e Innovación”. The authors acknowledge Francisco Dominguez Calvo, the Nuestra señora de la oliva manager, for providing the olive samples and reference data on which the study was conducted, as well as Diego Tejada, for his support in the device designes_ES
dc.relation.isversionofPublisher’s version
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.subject.otherRemote sensinges_ES
dc.subject.otherPrecision agriculturees_ES
dc.titleMethodology for Olive Fruit Quality Assessment by Means of a Low-Cost Multispectral Devicees_ES
dc.subject.unesco3307 Tecnología Electrónicaes_ES

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