Multivariate data analysis strategy to monitor Trentingrana cheese real-scale production through volatile organic compounds profiling

Abstract

Volatile organic compounds (VOCs) in cheese, as result of the chemical, physical and microbiological properties of the raw milk, are related to its sensory properties and consumer's acceptability. Measurement of VOCs can be related to the quality of the production process, highlighting changes in the raw materials or the process conditions. In the present study, we tested the suitability of ANOVA-Simultaneous Component Analysis (ASCA) to extract useful information from volatile organic compound data measured over two years of production of Trentingrana cheese in a real production context where several confounding factors are present.A total of 317 cheese wheels were collected from the 15 cooperative dairy factories every two months. The ASCA analysis indicates that the milk collection affects the VOC profiles. To deeper investigate this factor, an Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) model was developed to estimate the associations between VOCs and process characteristics of the dairy factory. Results showed that the milk collection procedure affects the content of organic acids, esters, and ketones of the cheeses.