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Granato D, Putnik P, Kovačević DB, et al. Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing. Compr Rev Food Sci Food Saf. 2018;17(3):663-677doi: 10.1111/1541-4337.12341.
Granato, D., Putnik, P., Kovačević, D. B., Santos, J. S., Calado, V., Rocha, R. S., Cruz, A. G. D., Jarvis, B., Rodionova, O. Y., & Pomerantsev, A. (2018). Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing. Comprehensive reviews in food science and food safety, 17(3), 663-677. https://doi.org/10.1111/1541-4337.12341
Granato, Daniel, et al. "Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing." Comprehensive reviews in food science and food safety vol. 17,3 (2018): 663-677. doi: https://doi.org/10.1111/1541-4337.12341
Granato D, Putnik P, Kovačević DB, Santos JS, Calado V, Rocha RS, Cruz AGD, Jarvis B, Rodionova OY, Pomerantsev A. Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing. Compr Rev Food Sci Food Saf. 2018 May;17(3):663-677. doi: 10.1111/1541-4337.12341. Epub 2018 Mar 30. PMID: 33350122.
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Compr Rev Food Sci Food Saf. 2018 May;17(3):663-677. doi: 10.1111/1541-4337.12341. Epub 2018 Mar 30.

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing.

Comprehensive reviews in food science and food safety

Daniel Granato, Predrag Putnik, Danijela Bursać Kovačević, Jânio Sousa Santos, Verônica Calado, Ramon Silva Rocha, Adriano Gomes Da Cruz, Basil Jarvis, Oxana Ye Rodionova, Alexey Pomerantsev

Affiliations

  1. Dept. of Food Engineering, State Univ. of Ponta Grossa, Av. Carlos Cavalcanti, 4748, 84030-900, Ponta Grossa, Brazil.
  2. Faculty of Food Technology and Biotechnology, Univ. of Zagreb, Pierottijeva 6, 10000, Zagreb, Croatia.
  3. School of Chemistry, Federal Univ. of Rio de Janeiro, Rio de Janeiro, Brazil.
  4. Dept. de Alimentos, Inst. Federal de Educação, Ciência e Tecnologia (IFRJ), 20270-021, Rio de Janeiro, Brazil.
  5. Dept. of Food and Nutrition Sciences, School of Chemistry, Food and Pharmacy, The Univ. of Reading, Whiteknights, Reading, Berkshire RG6 6AP, U.K.
  6. Semenov Inst. of Chemical Physics RAS, Kosygin str. 4, 119991, Moscow, Russia.

PMID: 33350122 DOI: 10.1111/1541-4337.12341

Abstract

In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.

© 2018 Institute of Food Technologists®.

Keywords: classification; food authentication; multivariate statistical techniques; one-class classifiers; pattern recognition

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