Comparison of Secondary Models for Modelling the Growth of Salmonella in Leafy Greens

This study evaluated the performance of three mathematical models—the Ratkowsky square-root, Arrhenius-type, and Cardinal models—in describing the temperature-dependent growth of Salmonella in leafy greens. Therefore, data on the maximum growth rate (μmax) of Salmonella enterica in leafy greens under different temperature conditions were collected from peer-reviewed scientific publications available in databases. The Integrated Pathogen Modeling Program (IPMP) software was then used for modelling and analysis. The results indicated that the sub-optimal Ratkowsky model most accurately captured growth rates below the organism’s optimum temperature, with parameters a=0.02 and Tmin=7.3°C estimated with high precision. In contrast, the model’s supra-optimal parameters were weakly constrained due to limited high-temperature data. Despite achieving strong explanatory power (R2=0.90), the Arrhenius-type and Cardinal models had significant parameter uncertainty over the whole temperature range, which limited their usefulness. These findings support the use of simpler, empirically grounded models in predictive microbiology when thermal data are incomplete. Future research should prioritize gathering data at higher temperatures to better characterize growth decline in the supra-optimal range.