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An overview of multivariate qualitative methods for food fraud detection

Author:
Callao, M. Pilar, Ruisánchez, Itziar
Source:
Food control 2018 v.86 pp. 283-293
ISSN:
0956-7135
Subject:
adulterants, adulterated products, data collection, fraud, qualitative analysis
Abstract:
Multivariate qualitative methods are an analytical strategy for addressing problems related to food fraud that cannot be solved with just one variable. Some examples are sample authentication since the required response is complex in nature and sample adulteration, when knowing the concentration of adulterant is not looked for. Establishing a multivariate qualitative method involves several steps: data collection, pre-treatment, exploration techniques, classification techniques, and method validation. When more than one data source is available, data fusion can be apply to improve the results of a single technique.This review describes the state of the art of multivariate qualitative analysis for determining food fraud, and differentiates between authentication and adulteration. All the mentioned steps are discussed and, as example, recently published papers are commented.
Agid:
5937168