Predictive microbiology is based on the assumption of repeatability of the microbial population response to the given environmental factors of a food product. Based on empirical data from the microbiological experience, predictive models are developed as online available computer software. The objective of the research study was to develop a database of predictive models of potentially probiotic, saprophytic and pathogenic bacteria in the form of a tool useful for the end customer and installed on the SGGW server under the name of “ProgBaz SGGW”. The study material consisted of mathematical models of growth and survival of saprophytic bacteria (psychrotrophs, Pseudomonas spp., yeasts and moulds), pathogenic bacteria: Salmonella spp., S. aureus, L. monocytogenes (disadvantageous micro-flora) and potentially probiotic strains of Lactobacillus genus (advantageous micro-flora). The models were developed in the Department of Hygiene and Food Quality Management at the Faculty of Human Nutrition and Consumption Sciences at the Warsaw University of Life Sciences in 1997 – 2008. ProgBaz is available on the main website of SGGW (Warsaw University of Life Sciences referred to as SGGW) in Warsaw, Economy tab and on the website of the Faculty of Human Nutrition and Consumer Sciences, SGGW, Science and Services tab. The user can estimate the growth or survival of microorganisms over time and affected by environmental factors (temperature, NaCl level, NaNO2 level, and inulin additive) in the following products: model product made of minced meat, in dairy, meat and vegetable marketable products. In addition, it is possible to acquire information on the characteristics of the population (λ, μ, GT, N) and the quality of predictive value in the case of a validated model. This is the information that makes it possible to estimate the safety of the product and its shelf life. ProgBaz can be used to assess the microbiological risk of food, to develop food safety plans, to reduce food waste, to design new products, and to provide an educational and training tool.
food, predictive microbiology, predictive models, predictive database, ProgBaz