0000000000089699
AUTHOR
Antonio Panebianco
A new approach to predict the fish fillet shelf-life in presence of natural preservative agents
Three data sets concerning the behaviour of spoilage flora of fillets treated with natural preservative substances (NPS) were used to construct a new kind of mathematical predictive model. This model, unlike other ones, allows expressing the antibacterial effect of the NPS separately from the prediction of the growth rate. This approach, based on the introduction of a parameter into the predictive primary model, produced a good fitting of observed data and allowed characterising quantitatively the increase of shelf-life of fillets.
Modelling Bacterial Dynamics in Food Products: Role of Environmental Noise and Interspecific Competition
In this paper we review some results obtained within the context of the predictive microbiology, which is a specific field of the population dynamics. In particular we discuss three models, which exploit tools of statistical mechanics, for bacterial dynamics in food of animal origin. In the first model, the random fluctuating behaviour, experimentally measured, of the temperature is considered. In the second model stochastic differential equations are introduced to take into account the influence of physical and chemical variables, such as temperature, pH and activity water, subject to deterministic and random variations. The third model, which is an extended version of the second one, negl…
A new approach to modelling the shelf life of Gilthead seabream (Sparus aurata)
Summary A total of 217 Gilthead seabreams were subdivided in four groups, according to four different storage conditions. All fish were evaluated by both Quality Index Method (QIM) and microbiological analysis, sampling skin, gills and flesh, separately. A QIM score predictive system was set by modelling the growth of microflora of skin, gills and flesh and coupling these predictions to each related partial QIM score (QIMSkin, QIMGills, QIMFlesh). The expression of QIM score as a function of bacterial behaviour was carried out by the employment of two coefficients. The predicted mean bacterial concentrations corresponding to the QIM score at 14 days were always near to Log 8 CFU g−1 in the …
Study on the application of an interspecific competition model for the prediction of microflora behaviour during the fermentation process of S. Angelo PGI salami.
The use of predictive microbiology models able to evaluate bacterial behaviour as a function of environmental conditions and, at the same time, of natural microflora competition was considered by several authors with different approaches. Some authors modelled bacterial competition as a function of metabolic product with particular regard to lactic acid and modelled interspecific bacterial competition introducing a term into a conventional primary predictive model, which gives account for the interaction between two populations, so that they inhibit each other to the same extent that they inhibit their own growth.
A stochastic interspecific competition model to predict the behaviour of Listeria monocytogenes in the fermentation process of a traditional Sicilian salami
The present paper discusses the use of modified Lotka-Volterra equations in order to stochastically simulate the behaviour of Listeria monocytogenes and Lactic Acid Bacteria (LAB) during the fermentation period (168 h) of a typical Sicilian salami. For this purpose, the differential equation system is set considering T, pH and aw as stochastic variables. Each of them is governed by dynamics that involve a deterministic linear decrease as a function of the time t and an "additive noise" term which instantaneously mimics the fluctuations of T, pH and aw. The choice of a suitable parameter accounting for the interaction of LAB on L. monocytogenes as well as the introduction of appropriate nois…