Modelling the Growth Rate of in Cooked Ham Stored at Different Temperatures.

INTRODUCTION

The purpose of the study was to determine and model the growth rates of in cooked cured ham stored at various temperatures.

MATERIAL AND METHODS

Samples of cured ham were artificially contaminated with a mixture of three strains and stored at 3, 6, 9, 12, or 15ºC for 16 days. The number of listeriae was determined after 0, 1, 2, 3, 5, 7, 9, 12, 14, and 16 days. A series of decimal dilutions were prepared from each sample and plated onto ALOA agar, after which the plates were incubated at 37ºC for 48 h under aerobic conditions. The bacterial counts were logarithmised and analysed statistically. Five repetitions of the experiment were performed.

RESULTS

Both storage temperature and time were found to significantly influence the growth rate of listeriae (P > 0.01). The test bacteria growth curves were fitted to three primary models: the Gompertz, Baranyi, and logistic. The mean square error (MSE) and Akaike's information criterion (AIC) were calculated to evaluate the goodness of fit. It transpired that the logistic model fit the experimental data best. The natural logarithms of mean growth rates from this model were fitted to two secondary models: the square root and polynomial.

CONCLUSION

Modelling in both secondary types can predict the growth rates of in cooked cured ham stored at each studied temperature, but mathematical validation showed the polynomial model to be more accurate.