Chemometric tools for food fraud detection: The role of target class in non-targeted analysis.
Food Chem
; 317: 126448, 2020 Jul 01.
Article
em En
| MEDLINE
| ID: mdl-32114274
ABSTRACT
The chemometric issues related to the application of non-targeted analysis for the detection of food frauds were analyzed employing discriminant analysis and a one-class classifier. The similarities and differences between the two methods were investigated. The results of classification are characterized by a set of indices called figures of merit. They comprehensively characterized the quality and reliability of classification. The principle is illustrated using an actual example of Oregano herbs adulteration. The informative region 9000-4000â¯cm-1 of near-Infrared spectroscopy is used as analytical means. The results of the application of each method for Oregano data collection are presented. It is shown that the discriminant method is only partially appropriate for solving the authentication problem. One class classifier is a powerful and devoted for non-targeted analysis. The step by step analysis introduced in the paper can also be successfully utilized in apply for revealing of forgeries of various food products.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Contaminação de Alimentos
/
Origanum
/
Análise de Alimentos
/
Fraude
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article