Primary and secondary modeling of Brochothrix thermosphacta growth under different temperature and ph values

Abstract

Bochothrix thermosphacta is an optional aerobic psychrotrophic related to the meat deterioration and consequently loss of a refrigerated cargo contaminated. Predictive microbiology can be used as a quality assurance tool, since it allows the prediction of microbial response based in pass observations. This work aimed model the growth of B. thermosphacta under variation of pH and temperature. For this purpose, the experimental growth data were fitted to the primary models of Baranyi and Roberts and the modified Gompertz model and the data for the maximum rate of growth (μmax) were adjusted to Ratkowsky extended secondary model. The results showed us that the influence of temperature on growth parameters was more evident than pH. Since, by fixing the temperature the change of pH little altered the μmax. However, as the temperature rises the elevation at the μmax is considerable, for example the comparison of predicted values for μmax, when the temperature exceeds 4 °C to 12 °C, it is clear that these rates are more than double. Finally, it is emphasized that all tested models feature good fit to the experimental data, which makes them validated for prediction growth of B. thermosphacta in the same conditions tested experimentally.Keywords: deterioration; refrigeration; predictive models. Pratical Application:To predict the growth of B. thermosphacta under varying temperature and pH conditions.

Hyperspectral imaging for one-step growth simulation of Brochothrix thermosphacta in chilled beef during storage

“…The model estimated Tmin of -12.20 ℃ in the study differed from the reported result (Tmin = -3.36 ℃) [39] , because of the differences in strains and growth media. Similar results were also reported for B. thermosphacta in which Tmin values for the growth of B. thermosphacta in laboratory media were found to be -9.79 ℃ [40] and -11.70 ℃ for meat broth [8] ,…”

“…To evaluate the behavior of B. thermosphacta in beef, predictive microbiology can be employed to obtain reliable predictive models, in order to monitor bacterial populations and estimate growth parameters [8] .…”

Investigation of the Suitability of a Combination of Ethyl-Να-dodecanyl-L-arginat_HCl (LAE) and Starter Culture Bacteria for the Reduction of Bacteria from Fresh Meat of Different Animal Species

“…thermosphacta on the different meat species pig, cattle and chicken. With regard to the pH value, Goncalves et al [47] showed that maximum growth rate of Br. thermosphacta at a pH of 5.5 was lower than at a pH of 6.0.…”

Viability of Lactobacillus acidophilus in whole goat milk yogurt during fermentation and storage stages: a predictive modeling study

“…In addition to this, it can also be an important ally in the study of the behavior of probiotic cells, such as lactic bacteria, present in milk and its derivatives. Mathematical modeling of the experimental data aids to obtain important data on the growth dynamics of probiotics under the studied conditions, which contributes to the optimization of the food manufacturing process, as well as to the estimation of their functional viability (Gonçalves et al, 2018;Stavropoulou & Bezirtzoglou, 2019).…”

“…In addition, it is noteworthy that dairy goat products are potential food matrices for delivery of probiotic bacteria (Ranadheera et al, 2019) In recent years, interest has grown in the study of the survival kinetics of true probiotic species, applied to different environmental conditions and food matrices, highlighting the fact that fermentation is one of the main strategies for probiotics to synthesize compounds of interest, the probioactives (Champagne et al, 2018;Ryan et al, 2020). Predictive microbiology is a science that investigate parameters for predicting the behavior of microorganisms in food, which provides a fast and reliable path to knowledge about microbial growth, inactivation, and survival under specific conditions (Gonçalves et al, 2018;Ross & McMeekin, 1994).…”