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In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties

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In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties

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dc.contributor.author Cortes-Lopez, Victoria es_ES
dc.contributor.author Cubero-García, Sergio es_ES
dc.contributor.author BLASCO IVARS, JOSE es_ES
dc.contributor.author Aleixos Borrás, María Nuria es_ES
dc.contributor.author Talens Oliag, Pau es_ES
dc.date.accessioned 2020-01-30T21:02:02Z
dc.date.available 2020-01-30T21:02:02Z
dc.date.issued 2019 es_ES
dc.identifier.issn 1935-5130 es_ES
dc.identifier.uri http://hdl.handle.net/10251/136099
dc.description.abstract [EN] One of the most studied techniques for the non-destructive determination of the internal quality of fruits has been visible and nearinfrared (VIS-NIR) reflectance spectroscopy. This work evaluates a new non-destructive in-line VIS-NIR spectroscopy prototype for in-line identification of five apple varieties, with the advantage that it allows the spectra to be captured with the probe at the same distance from all the fruits regardless of their size. The prototype was tested using varieties with a similar appearance by acquiring the diffuse reflectance spectrum of the fruits travelling on the conveyor belt at a speed of 0.81 m/s which is nearly 1 fruit/s. Principal component analysis (PCA) was used to determine the variables that explain the most variance in the spectra. Seven principal components were then used to perform linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). QDA was found to be the best in-line classification method, achieving 98% and 85% success rates for red and yellow apple varieties, respectively. The results indicated that the in-line application of VIS-NIR spectroscopy that was developed is potentially feasible for the detection of apple varieties with an accuracy that is similar to or better than a laboratory system. es_ES
dc.description.sponsorship This work was partially funded by the Generalitat Valenciana through project AICO/2015/122 and by INIA and FEDER funds through project RTA2015-00078-00-00. Victoria Cortes Lopez thanks the Spanish Ministry of Education, Culture and Sports for FPU grant (FPU13/04202). es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Food and Bioprocess Technology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Apple es_ES
dc.subject In-line es_ES
dc.subject Varietal discrimination es_ES
dc.subject Visible-near-infrared spectroscopy es_ES
dc.subject Non-destructive es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.subject.classification TECNOLOGIA DE ALIMENTOS es_ES
dc.title In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11947-019-02268-0 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU13%2F04202/ES/FPU13%2F04202/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//AICO%2F2015%2F122/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//RTA2015-00078-00-00/ES/Sistemas no destructivos para la determinación automática de la calidad interna de frutas en línea utilizando métodos ópticos e información espectral/ 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. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària es_ES
dc.description.bibliographicCitation Cortes-Lopez, V.; Cubero-García, S.; Blasco Ivars, J.; Aleixos Borrás, MN.; Talens Oliag, P. (2019). In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties. Food and Bioprocess Technology. 12(6):1021-1030. https://doi.org/10.1007/s11947-019-02268-0 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s11947-019-02268-0 es_ES
dc.description.upvformatpinicio 1021 es_ES
dc.description.upvformatpfin 1030 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 6 es_ES
dc.relation.pasarela S\385868 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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