Trends in chemometrics and meat products

Abstract

Abstract Chemometrics is a set of mathematical and statistical methods that are used to detect food fraud, predict microbial growth, and optimize design of experiments, while extracting useful information from large and complex datasets. Complex datasets quite often have numerous sources of variations, with one or more dependent variables assessed against the two or more dependent variables, hence the need to employ some type of multivariate statistics. It is critical to decrease the chances of type I error, by comparing (calculating) all the effects of independent variables in a single multivariate test. The most common types of multivariate tests include multivariate analysis of variance (MANOVA), various forms of factor analysis (such as principal component analysis, PCA), and mathematical modeling. Bioactive compounds of plant origin possess desirable health benefits and hence are interesting for functional meat processing. The extraction and processing of bioactive compounds mostly revolve around the central problems of thermal (in)stability and environmental issues that are relevant for industry. Here, multivariate statistics can offer the best mathematical solutions for optimal industrial production or can devise various indexes that are able to follow changes of the entire chemical footprint during the extraction of target compounds. For instance, multivariate statistics is useful to determine optimal extraction parameters for antioxidants, while simultaneously evaluating the effects and interactions of extraction parameters.