Ricerc@Sapienza

The dairy industry is continuously developing new strategies to obtain healthier dairy products preserving expected properties. However, when modifying a food process, the reassessment of each parameters and their interaction should be considered as highly influencing the final quality. Among others, rennet process features are fundamental for both sensory properties and typical characteristics of a cheese. In this contest, the research addresses the development of a FT-NIR spectroscopic method, coupled with chemometrics, for the study of the effect of process variables on milk renneting. The effects of temperature (30 °C, 35 °C, 40 °C), milk fat concentration (0.1, 2.55, 5 g/100 mL), and pH (6.3, 6.5, 6.7) were investigated by means of a Box-Behnken experimental design. FT-NIR data collected along the 17 trials were explored by interval-PCA (i-PCA) and ANOVA-simultaneous component analysis (ASCA). i-PCA revealed differences in the occurrence and trends of coagulation phases, related to the three considered factors. ASCA allowed the characterization of renneting evolution and the assessment of the factor role, demonstrating that main and interaction effects are significant for the process progress. The proposed approach demonstrated that i-PCA and ASCA on FT-NIR data, highlighting the effects of the operating factors, allow a rapid and accurate analysis of process modifications in cheese manufacturing.