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dc.contributor.author | Rodríguez-Ortega, Alejandro | es_ES |
dc.contributor.author | Aleixos Borrás, María Nuria | es_ES |
dc.contributor.author | Blasco, José | es_ES |
dc.contributor.author | Albert Gil, Francisco Eugenio | es_ES |
dc.contributor.author | Munera, Sandra | es_ES |
dc.date.accessioned | 2024-06-26T18:11:53Z | |
dc.date.available | 2024-06-26T18:11:53Z | |
dc.date.issued | 2023-12 | es_ES |
dc.identifier.issn | 0260-8774 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/205515 | |
dc.description.abstract | [EN] Hyperspectral imaging (HSI) is one of the most studied optical techniques to estimate the internal quality of fruits and vegetables. Absorbance and reflectance of the light radiation are specific to each biological tissue and are directly related to its chemical composition and physical characteristics. These properties are influenced by other extrinsic factors, such as the instrumentation or the light source, which can reduce the reproducibility of the experiments. Determining the actual depth of light penetration into tissue could help validate non-contact methods as accurate tools to assess quality properties based on optical properties. In the case of HSI systems, it is crucial to know how far the light penetrates at each wavelength. A non-destructive approach, based on the spatially resolved spectroscopic principle, was proposed to estimate the light penetration depth of a HSI system in a Vis-NIR configuration (in the range 450-1050 nm). This method was applied to measure the light penetration depth in persimmon fruit. The absorption (mu(a)) and scattering (mu'(s)) coefficients from Farrell's diffusion theory were estimated using the backscattered light measured at different distances from the incident point light at each wavelength in hyperspectral images of persimmon fruit. The actual light penetration depth was obtained by measuring the reflectance of cut pieces of persimmon fruit with different thicknesses. Linear regression was used to relate the depth of penetrability obtained by both protocols, the estimated or non-destructive protocol and the actual or destructive protocol, showing a high relationship (R-2 > 0.8 and RPD>2.5) in the range 610-1050 nm. This confirms that this non-destructive approach proposed for estimating the light penetration depth of a Vis-NIR HSI system in persimmon fruit is accurate, so it could be used as a valuable method to evaluate other HSI systems for different fruits. | es_ES |
dc.description.sponsorship | This work was co-funded by the projects AEI PID 2019-107347RRC31 and PID 2019-107347RR-C32, and GVA-PROMETEO CIPROM/2021/014. Sandra Munera thanks the postdoctoral contract Juan de la Cierva-Formacion (FJC2021-047786-I) co-funded by MCIN/AEI/ 10.13039/501100011033 and NextGenerationEU/PRTR. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Journal of Food Engineering | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Light depth penetrability | es_ES |
dc.subject | Fruit | es_ES |
dc.subject | Scattering | es_ES |
dc.subject | Absorption | es_ES |
dc.subject | Optical properties | es_ES |
dc.subject | Hyperspectral imaging | es_ES |
dc.subject.classification | EXPRESION GRAFICA EN LA INGENIERIA | es_ES |
dc.title | Study of light penetration depth of a Vis-NIR hyperspectral imaging system for the assessment of fruit quality. A case study in persimmon fruit | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.jfoodeng.2023.111673 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107347RR-C31/ES/INSPECCION NO DESTRUCTIVA Y PREDICCION DE LA CALIDAD INTERNA Y PROPIEDADES DE LAS FRUTAS MEDIANTE ESPECTROSCOPIA VIS%2FNIR Y MODELOS BASADOS EN APRENDIZAJE PROFUNDO/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107347RR-C32/ES/INSPECCION Y PREDICCION NO DESTRUCTIVA DE CALIDAD INTERNA Y PROPIEDADES DE FRUTAS UTILIZANDO IMAGEN HIPERESPECTRAL VIS%2FNIR UTILIZANDO MODELOS BASADOS EN APRENDIZAJE PROFUNDO/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICIN//FJC2021-047786-I//SISTEMAS ÓPTICOS DE INSPECCIÓN AUTOMÁTICA PARA DETERMINAR LA CALIDAD INTERNA DE FRUTAS EN POSCOSECHA (SPINACH)/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Generalitat Valenciana//CIPROM%2F2021%2F014//Creación de sistemas automáticos y no destructivos de inspección en poscosecha para determinar las propiedades y calidad interna de frutas de especial interés para la Comunitat Valenciana./ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials | es_ES |
dc.description.bibliographicCitation | Rodríguez-Ortega, A.; Aleixos Borrás, MN.; Blasco, J.; Albert Gil, FE.; Munera, S. (2023). Study of light penetration depth of a Vis-NIR hyperspectral imaging system for the assessment of fruit quality. A case study in persimmon fruit. Journal of Food Engineering. 358. https://doi.org/10.1016/j.jfoodeng.2023.111673 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.jfoodeng.2023.111673 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 358 | es_ES |
dc.relation.pasarela | S\498902 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | MINISTERIO DE EDUCACION | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
upv.costeAPC | 0 | es_ES |