Multivariate statistics: considerations and confidences in food authenticity problems

Abstract:
An overview of multivariate statistics for food authentication applications. The advantages of a multivariate strategy compared with univariate assessments with a detailed look at selected techniques such as the data compression methods of principal component analysis. Predictive approaches suitable for authentication applications: discriminant and classification strategies, and class-modelling techniques. Critical to the proper application of multivariate techniques is the concept of validation. Recommondations on experimental design, such as the importance of representative sampling. Illustrations are drawn from real-world examples of food authenticity problems.
PubYear:
2019
Keywords:
non-targeted, classification models, pca
FundingBody:
EU Food Integrity Programme
Contractor:
ProjCode:
Associated:
Type:
Good Practice Guidance
OpenAccess:
No
URL:
https://www.sciencedirect.com/science/article/abs/pii/S0956713519302294?via%3Dihub
Comments:
NA