The use of predictive modeling software may markedly contribute to the better understanding of the
microbial behavior in foods. In this paper, the development and validation of a tertiary model, which
provides predictions of microbial growth in foods under dynamic or static temperature conditions, is
presented. In particular, the UGPM (Unified Growth Prediction Model) software applies the Baranyi and
Roberts (1994) primary model, coupled to a secondary temperature model, in order to simulate growth
of a given microorganism during storage of a specific food or food category. The software, intended to be
used by both expert and non-expert users, may be a valuable decision support tool for the food industry,
by assisting in the management of foods based on their actual shelf-life and microbial safety, thereby
limiting the deterministic “best-by” practice for the determination of shelf-life. The latter is commonly
based solely on empirical observations and has high uncertainty. This in turn, may result in the rejection
of large quantities of unspoiled or safe foods, or even in the distribution of spoiled and unsafe foods, due
to ignorance of the effect of temperature abuse on the microbial spoilage and safety of products
The use of predictive modeling software may markedly contribute to the better understanding of the
microbial behavior in foods. In this paper, the development and validation of a tertiary model, which
provides predictions of microbial growth in foods under dynamic or static temperature conditions, is
presented. In particular, the UGPM (Unified Growth Prediction Model) software applies the Baranyi and
Roberts (1994) primary model, coupled to a secondary temperature model, in order to simulate growth
of a given microorganism during storage of a specific food or food category. The software, intended to be
used by both expert and non-expert users, may be a valuable decision support tool for the food industry,
by assisting in the management of foods based on their actual shelf-life and microbial safety, thereby
limiting the deterministic “best-by” practice for the determination of shelf-life. The latter is commonly
based solely on empirical observations and has high uncertainty. This in turn, may result in the rejection
of large quantities of unspoiled or safe foods, or even in the distribution of spoiled and unsafe foods, due
to ignorance of the effect of temperature abuse on the microbial spoilage and safety of products
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