Predictive model for the growth of Shiga toxin-producing Escherichia coli in Minas Frescal cheese

This study aims to develop and evaluate a predictive model for Shiga toxin-producing Escherichia coli (STEC) growth on Minas Frescal cheese across varied temperature conditions. A pool of five STEC strains (3–4 log CFU/g) was inoculated onto 10 g Minas Frescal cheese portions (%moisture = 68.30 ± 0.47,%fat in dry basis = 26.55 ± 0.37, pH = 6.86 ± 0.02) stored at isothermal conditions (4, 8, 15, 25, 37, and 42 °C). STEC concentrations increased at 8 °C and above, persisting throughout the 504-hour study period at 4 °C, showing minimal cell loss. The growth curves were fitted with the primary model of Baranyi and Roberts using Combase DMFit, showcasing robust alignment between predicted and experimental data (R² ≥ 0.98). Further, the µ_max and λ values were fitted as a function of temperature to modified Ratkowsky equations, resulting in R² of 0.99 and 0.96, and RMSE of 0.03 and 0.08, respectively, for the secondary models. Model validation was performed under isothermal conditions at 20 and 30 °C. The Ratkowsky equations can reliably predict STEC growth rate and lag phase in Minas Frescal cheese at diverse temperatures (8 to 42 °C), evidenced by accuracy and bias factors of 1.06 and 1.06. These findings offer insights into cold chain management for STEC control during Minas Frescal cheese production, distribution, and storage, emphasizing the need for robust post-pasteurization manufacturing practices to prevent STEC survival even at lower temperatures.