Abstract
Principal component analysis (PCA) is currently one of the most used multivariate data analysis techniques for evaluating information from food analysis. In this review, a brief introduction to the theoretical principles that underlie PCA will be given, in addition to presenting the most commonly used computer programs. An example from the literature was discussed to illustrate the use of this chemometric tool and interpretation of graphs and parameters obtained. A list of recently published articles will also be presented, in order to show the applicability and potential of the technique in the food analysis field.
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Source: Adapted from Hair et al. (2009)
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Acknowledgements
The authors would like to acknowledge the financial support of the Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq. Grant Number 310949/2021-1) and Financiadora de Estudos e Projetos (FINEP).
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Souza, A.S., Bezerra, M.A., Cerqueira, U.M.F.M. et al. An introductory review on the application of principal component analysis in the data exploration of the chemical analysis of food samples. Food Sci Biotechnol 33, 1323–1336 (2024). https://doi.org/10.1007/s10068-023-01509-5
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DOI: https://doi.org/10.1007/s10068-023-01509-5