Article
Olive oil nutritional labeling by using Vis/NIR spectroscopy and compositional statistical methods
Author/s | Cayuela Sánchez, José Antonio
Palarea Albaladejo, Javier García-Martín, Juan Francisco Pérez Camino, Carmen |
Department | Universidad de Sevilla. Departamento de Ingeniería Química |
Publication Date | 2019 |
Deposit Date | 2022-06-13 |
Published in |
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Abstract | Food nutritional labeling is compulsory in the European Union since 13 December 2016. The olive oil fatty acid composition shows high variation depending mainly on the variety. Thus, olive oil nutritional labeling is ... Food nutritional labeling is compulsory in the European Union since 13 December 2016. The olive oil fatty acid composition shows high variation depending mainly on the variety. Thus, olive oil nutritional labeling is problematic for the industry. Besides, the analysis of all batches of olive oil using the official methods is expensive. Therefore, the olive oil industry is seriously concerned about solutions for nutritional labeling. In this study, a new rapid technique to measure the nutrients for the olive oil nutritional labeling, is assessed. A novel partial least squares (PLS) calibration model using log-ratio coordinates has been formulated and successfully tested for predicting the percentages of monounsaturated, saturated, and polyunsaturated fatty acids based on visible and near infrared spectroscopy. The model provided accuracy suitable for labeling, under the rules in force in the European Union. The error was generally much lower than the tolerance. Industrial relevance: The approach here proposed can be a suitable solution for olive oil nutritional labeling, which is a current challenge for the olive oil industry. |
Funding agencies | Consejo Superior de Investigaciones Científicas (CSIC) Ministerio de Economía y Competitividad (MINECO). España |
Project ID. | 20137R065
MTM2015-65016-C2-1(2)-R |
Citation | Cayuela Sánchez, J.A., Palarea Albaladejo, J., García-Martín, J.F. y Pérez Camino, C. (2019). Olive oil nutritional labeling by using Vis/NIR spectroscopy and compositional statistical methods. Innovative Food Science and Emerging Technologies, 51, 139-147. |
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