An introductory review on the application of principal component analysis in the data exploration of the chemical analysis of food samples

被引：9

作者：

Souza, Anderson Santos ^{[1
,4
]}

Bezerra, Marcos Almeida ^{[2
]}

Cerqueira, Uillian Mozart Ferreira Mata ^{[3
]}

Rodrigues, Caiene Jesus Oliveira ^{[1
]}

Santos, Bianca Cotrim ^{[1
]}

Novaes, Cleber Galvao ^{[2
]}

Almeida, Erica Raina Venancio ^{[2
]}

机构：

[1] Univ Fed Bahia, Inst Multidisciplinar Saude, Campus Anisio Teixeira,Rua Hormindo Barros 58, BR-45029094 Vitoria da Conquista, BA, Brazil

[2] Univ Estadual Sudoeste Bahia, Dept Ciencias & Tecnol, Campus Jequie,Rua Jose Moreira Sobrinho, BR-45206190 Jequie, BA, Brazil

[3] Univ Fed Bahia, Inst Quim, Campus Federacao Ondina,Rua Barao Geremoabo, BR-40170115 Salvador, BA, Brazil

[4] Univ Fed Bahia, Inst Nacl Ciencia & Tecnol Energia & Ambiente INCT, BR-40170115 Salvador, BA, Brazil

来源：

FOOD SCIENCE AND BIOTECHNOLOGY | 2024年 / 33卷 / 06期

关键词：

Principal component analysis; Multivariate analysis; Food samples; HIERARCHICAL CLUSTER-ANALYSIS; MINERAL-CONTENT; CLASSIFICATION; SPECTROSCOPY; ACIDS; TEA;

D O I：

10.1007/s10068-023-01509-5

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

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.

引用

页码：1323 / 1336

页数：14

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