DEVELOPMENT AND APPLICATION OF PREDICTIVE MODELS FOR FUNGAL GROWTH AS TOOLS TO IMPROVE QUALITY CONTROL IN YOGURT PRODUCTION

摘要

The objective of the present study was to develop yogurt-targeted predictive models for the effect of storage temperature and inoculum size on the mycelium growth kinetics of fungal species isolated from yogurt production environment. Firstly, the effect of storage temperature (0 - ; 40 °C) and inoculum size (10~1 - 10~5 spores) on the mycelium growth kinetics of 12 fungal species on yogurt were monitored. A secondary model was used to describe the effect of temperature on the growth rate (μ) and the lag time (A) of each isolate. Significant differences on the temperature dependence of the mycelium growth between the tested species were observed. Depending on the strain, the estimated minimum, optimum and maximum temperature parameters for μ (T_(min), r_(opt), T_(max)) ranged from -7.6 to 9.6, 19.5 to 37.8 and 29.8 to 46.9, respectively. Only A was found to be affected by the inoculum size and a linear relation between Ln(A) and Log(inoculum size) was revealed. The inoculum level did not influence the values of T_(min), T_(opt) and T_(max) for A. Validation studies showed a good performance of the developed models. The models developed in the present study can be used as the basis for the selection of the appropriate conditions of the challenge tests for fungi detection of presence in yogurt production and lead to effective decision making.