Identification of cocoa bean quality by near infrared spectroscopy and multivariate modeling
Cocoa is a commodity responsible for the income of millions of people and the manufacture of several important products for the food, pharmaceutical, and cosmetic industries. Its quality is associated with several factors involved in the processing steps, mainly in fermentation and drying. The objec...
| Authors: | , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2021 |
| Country: | Brasil |
| Institution: | Universidade Federal de Itajubá (UNIFEI) |
| Repository: | Research, Society and Development |
| Language: | English |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/22732 |
| Online Access: | https://rsdjournal.org/index.php/rsd/article/view/22732 |
| Access Level: | Open access |
| Keyword: | Control de calidad Espectroscopia NIR PLS-DA PLS Quimiometria. Controle de qualidade Quality control NIR spectroscopy Chemometry. |
| Summary: | Cocoa is a commodity responsible for the income of millions of people and the manufacture of several important products for the food, pharmaceutical, and cosmetic industries. Its quality is associated with several factors involved in the processing steps, mainly in fermentation and drying. The objective of this study was to evaluate the application of near-infrared spectroscopic data associated with multivariate analysis to classify cocoa beans according to their quality and predict attributes such as pH and total acidity by PLS-DA and PLS, respectively. The pH values (4.4-6.7) and total acidity (6.12-29.9) were determined by conventional methods. The PLS-DA proved to be effective in differentiating the classes of cocoa samples with superior and inferior quality, presenting in the validation 100% and 71.43% correct cocoa bean classification with inferior Quality and Higher Quality, respectively. The models obtained by PLS presented satisfactory parameters, being classified as having moderate practical utility and excellent predictive capacity for pH and moderate practical utility and reasonable predictive capacity for total acidity. Thus, the potential of the NIRS technology associated with chemometrics was found and showed efficiency in the classification and prediction of attributes in cocoa beans. |
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