Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis. (May 2019)

• Record Type: Journal Article
• Authors: Quelal-Vásconez, Maribel Alexandra; Lerma-García, María Jesús; Pérez-Esteve, Édgar; Arnau-Bonachera, Alberto; Barat, José Manuel; Talens, Pau
• Is Part Of: Food control. Volume 99(2019)
• Page Start: 68
• Page End: 72
• Publication Date: 2019-05
• Subjects: Cocoa powder -- Cocoa shell -- NIR -- PLS -- PLS-DA; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2018.12.028
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: 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. Highlights: The detection of cocoa shell in cocoa powder can be done by near infrared spectroscopy. PLS-DA distinguishes cocoa shell which contains over 5% powders from those with less content. The detection methods are fast, and have good sensitivity, specificity for quality cacao powder analysis. PLS analysis has the potential to quantify the percentage of cocoa shell in cocoa powder.