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.

Abstract Meat is one of the most perishable foods owing to its nutrient availability, high water activity, and pH around 5.6. These properties are highly conducive for microbial growth. Fresh meat, when exposed to oxygen, is subjected to the action of aerobic psychrotrophic, proteolytic, and lipolytic spoilage microorganisms, such as Pseudomonas spp. The spoilage results in the appearance of slime and off-flavor in food. In order to predict the growth of Pseudomonas fluorescens in fresh meat at different pH values, stored under refrigeration, and temperature abuse, microbial mathematical modeling was applied. The primary Baranyi and Roberts and the modified Gompertz models were fitted to the experimental data to obtain the growth parameters. The Ratkowsky extended model was used to determine the effect of pH and temperature on the growth parameter µmax. The program DMFit 3.0 was used for model adjustment and fitting. The experimental data showed good fit for both the models tested, and the primary and secondary models based on the Baranyi and Roberts models showed better validation. Thus, these models can be applied to predict the growth of P. fluorescens under the conditions tested.

Pão de queijo é um produto brasileiro que se originou em Minas Gerais e que é altamente consumido. Na produção industrial, há uma crescente utilização de aditivos que enriquecem e melhoraram as características físicas do produto, acrescentando valor aos olhos do consumidor. Assim, o objetivo deste trabalho foi estudar o efeito da adição de amido modificado e estabilizadores sobre a qualidade físico-química de pão de queijo. Por esse motivo, foram tomadas medidas para umidade, pH e acidez, volume, densidade, coeficiente de dilatação e resistência à compressão (texturômetro). Os resultados mostram que os estabilizadores usados melhoraram estas características no pão de queijo, mostrando melhores características físico-químicas.

Cheese bread is a Brazilian product which originated in Minas Gerais and which is highly consumed. In industrial production, there is increasing use of additives which enrich and enhance the physical of this product, adding value in the eyes of the consumer. Thus, the purpose of this paper was to study the effect of addition of modified starch and stabilizers on the physical-chemical of cheese bread. For this reason, measures taken so moisture, pH and acidity, volume, density, coefficient of expansion, and compression resistance (texturometer) Results show that the stabilizers used improve these characteristics in the cheese bread, showing better physicochemical characteristics.