Modeling the Growth of Natural Microbiota in Cook-In Sliced Cooked Ham for Predictive Shelf-Life Validation
Predictive microbiology, cooked ham, meat products, MicroLab_ShelfLife.
This study aims to model the growth of the natural microbiota in sliced cooked ham to establish a database for validating shelf life through durability studies supported by predictive methods. Samples will be obtained from two meat industries located at the states of Minas Gerais and Santa Catarina, Brazil. The experiment will be carried out using in-line products from the industries, which will be incubated in the laboratory at controlled conditions at 4 °C, 12 °C, 24 °C, and 36 °C. During the incubation, the samples will be periodically assessed for microbial loads, potential of hydrogen, texture profile, off-flavors, and color. Microbial growth will be mathematically described using the Gompertz’s model, enabling the determination of growth-phase durations and their correlation with sensory rejection thresholds. The findings are expected to highlight the intrinsic relationship between microbial growth and changes in the original properties of the product matrix. These data can then be integrated into predictive methods, as MicroLab_SheflLife, to speed up test for shelf life of sliced cooked ham. Ultimately contributing to reduced food waste, minimized economic losses, and protection of the brand.