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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Classification and compositional characterization of different varieties of cocoa beans by near infrared spectroscopy and multivariate statistical analyses

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Barbin, Douglas Fernandes [1] ; Maciel, Leonardo Fonseca [2, 3] ; Vidigal Bazoni, Carlos Henrique [2] ; Ribeiro, Margareth da Silva [3] ; Sales Carvalho, Rosemary Duarte [3] ; Bispo, Eliete da Silva [3] ; Spinola Miranda, Maria da Pureza [3] ; Hirooka, Elisa Yoko [2]
Total Authors: 8
[1] Univ Estadual Campinas, Dept Food Engn, Rua Monteiro Lobato 80, Cidade Univ, BR-13083860 Campinas, SP - Brazil
[2] Univ Estadual Londrina, Dept Food Sci & Technol, Rodovia Celso Garcia Cid, PR 445 Km 380, BR-86055900 Londrina, PR - Brazil
[3] Univ Fed Bahia, Coll Pharm, Salvador, BA - Brazil
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE; v. 55, n. 7, p. 2457-2466, JUL 2018.
Web of Science Citations: 0

Effective and fast methods are important for distinguishing cocoa varieties in the field and in the processing industry. This work proposes the application of NIR spectroscopy as a potential analytical method to classify different varieties and predict the chemical composition of cocoa. Chemical composition and colour features were determined by traditional methods and then related with the spectral information by partial least-squares regression. Several mathematical pre-processing methods including first and second derivatives, standard normal variate and multiplicative scatter correction were applied to study the influence of spectral variations. The results of chemical composition analysis and colourimetric measurements show significant differences between varieties. NIR spectra of samples exhibited characteristic profiles for each variety and principal component analysis showed different varieties in according to spectral features. (AU)

FAPESP's process: 15/24351-2 - Applications of image analyses and NIR spectroscopy for quality assessment and authentication of food products
Grantee:Douglas Fernandes Barbin
Support type: Research Grants - Young Investigators Grants