An Updated Review of Meat Authenticity Methods and Applications

Abstract

Adulteration of foods is a serious economic problem concerning most foodstuffs, and in particular meat products. Since high-priced meat demand premium prices, producers of meat-based products might be tempted to blend these products with lower cost meat. Moreover, the labeled meat contents may not be met. Both types of adulteration are difficult to detect and lead to deterioration of product quality. For the consumer, it is of outmost importance to guarantee both authenticity and compliance with product labeling. The purpose of this article is to review the state of the art of meat authenticity with analytical and immunochemical methods with the focus on the issue of geographic origin and sensory characteristics. This review is also intended to provide an overview of the various currently applied statistical analyses (multivariate analysis (MAV), such as principal component analysis, discriminant analysis, cluster analysis, etc.) and their effectiveness for meat authenticity.

Keywords: Authenticity; meat; multivariate analysis; quality control.