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Título : Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis
Autor : Quelal Vásconez, Maribel Alexandra.
Lerma García, María Jesús.
Pérez Esteve, Édgar.
Arnau Bonachera, Alberto.
Barat Baviera, José Manuel.
Talens Oliag, Pau.
Materias: Alimentos - Control de calidad.Food - Quality.Cocoa.Cacao.Food - Analysis.Alimentos - Análisis.
Fecha de publicación : 1-may-2019
Editorial : Elsevier.
Citación : Quelal-Vásconez, MA., Lerma-García, MJ., Pérez Esteve, E., Arnau-Bonachera, A., Barat, JM. & Talens, P. (2019). Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis. Food Control, vol. 99 (may.), pp. 68-72. DOI: https://doi.org/10.1016/j.foodcont.2018.12.028
Resumen : 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.
Descripción : Este artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.sciencedirect.com/science/article/abs/pii/S0956713518306285
Este es el pre-print del siguiente artículo: Quelal-Vásconez, MA., Lerma-García, MJ., Pérez Esteve, E., Arnau-Bonachera, A., Barat, JM. & Talens, P. (2019). Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis. Food Control, vol. 99 (may.), pp. 68-72, que se ha publicado de forma definitiva en https://doi.org/10.1016/j.foodcont.2018.12.028
This is the pre-peer reviewed version of the following article: Quelal-Vásconez, MA., Lerma-García, MJ., Pérez Esteve, E., Arnau-Bonachera, A., Barat, JM. & Talens, P. (2019). Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis. Food Control, vol. 99 (may.), pp. 68-72, which has been published in final form at https://doi.org/10.1016/j.foodcont.2018.12.028
URI : http://hdl.handle.net/10637/11649
Derechos: http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
ISSN : 0956-7135
Aparece en las colecciones: Dpto. Producción y Sanidad Animal, Salud Pública Veterinaria y Ciencia y Tecnología de los Alimentos

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