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Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis

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Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis

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dc.contributor.author Quelal-Vásconez, Maribel Alexandra es_ES
dc.contributor.author Lerma-García, María Jesús es_ES
dc.contributor.author Pérez-Esteve, Édgar es_ES
dc.contributor.author Arnau-Bonachera, Alberto es_ES
dc.contributor.author Barat Baviera, José Manuel es_ES
dc.contributor.author Talens Oliag, Pau es_ES
dc.date.accessioned 2020-06-06T03:33:13Z
dc.date.available 2020-06-06T03:33:13Z
dc.date.issued 2019-05 es_ES
dc.identifier.issn 0956-7135 es_ES
dc.identifier.uri http://hdl.handle.net/10251/145563
dc.description.abstract [EN] Cocoa shell must be removed from the cocoa bean before or after the roasting process. In the case of a low efficient peeling process or the intentional addition of cocoa shell to cocoa products (i.e. cocoa powders) to increase the economic benefit, quality of the final product could be unpleasantly affected. In this scenario, the Codex Alimentarius on cocoa and chocolate has established that cocoa cake must not contain more than 5% of cocoa shell and germ (based on fat-free dry matter). Traditional analysis of cocoa shell is very laborious. Thus, the aim of this work is to develop a methodology based on near infrared (NIR) spectroscopy and multivariate analysis for the fast detection of cocoa shell in cocoa powders. For this aim, binary mixtures of cocoa powder and cocoa shell containing increasing proportions of cocoa shell (up to ca. 40% w/w based on fat-free dried matter) have been prepared. After acquiring NIR spectra (1100-2500 nm) of pure samples (cocoa powder and cocoa shell) and mixtures, qualitative and quantitative analysis were done. The qualitative analysis was performed by using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), finding that the model was able to correctly classify all samples containing less than 5% of cocoa shell. The quantitative analysis was performed by using a partial least squares (PLS) regression. The best PLS model was the one constructed using extended multiple signal correction plus orthogonal signal correction pre-treatment using the 6 main wavelengths selected according to the Variable Importance in Projection (VIP) scores. Determination coefficient of prediction and root mean square error of prediction values of 0.967 and 2.43, respectively, confirmed the goodness of the model. According to these results it is possible to conclude that NIR technology in combination with multivariate analysis is a good and fast tool to determine if a cocoa powder contains a cocoa shell content out of Codex Alimentarius specifications. es_ES
dc.description.sponsorship The authors wish to acknowledge the financial assistance provided the Spanish Government and European Regional Development Fund (Project RTC-2016-5241-2). M. A. Quelal thanks the Ministry of Higher Education, Science, Technology and Innovation (SENESCYT) of the Republic of Ecuador for her PhD grant. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Food Control es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Cocoa powder es_ES
dc.subject Cocoa shell es_ES
dc.subject NIR es_ES
dc.subject PLS es_ES
dc.subject PLS-DA es_ES
dc.subject.classification TECNOLOGIA DE ALIMENTOS es_ES
dc.subject.classification PRODUCCION ANIMAL es_ES
dc.title Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.foodcont.2018.12.028 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//RTC-2016-5241-2/ES/Estudio de la relación entre variables de procesado y cambios en la composición nutricional y perfil funcional del cacao en polvo. Desarrollo de una metodología predictiva aplicada al procesamiento/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ciencia Animal - Departament de Ciència Animal es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments es_ES
dc.description.bibliographicCitation Quelal-Vásconez, MA.; Lerma-García, MJ.; Pérez-Esteve, É.; Arnau-Bonachera, A.; Barat Baviera, JM.; Talens Oliag, P. (2019). Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis. Food Control. 99:68-72. https://doi.org/10.1016/j.foodcont.2018.12.028 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.foodcont.2018.12.028 es_ES
dc.description.upvformatpinicio 68 es_ES
dc.description.upvformatpfin 72 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 99 es_ES
dc.relation.pasarela S\374652 es_ES
dc.contributor.funder Secretaría de Educación Superior, Ciencia, Tecnología e Innovación, Ecuador es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES


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