Modeling Growth of Cronobacter sakazakii IFST082014 in Reconstituted Powdered Infant Milk as Function of Temperature
Md. Fakruddin
Industrial Microbiology Laboratory, Institute of Food Science and Technology (IFST), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
Md. Mizanur Rahaman
Industrial Microbiology Laboratory, Institute of Food Science and Technology (IFST), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
Md. Nur Hossain
Industrial Microbiology Laboratory, Institute of Food Science and Technology (IFST), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
Monzur Morshed Ahmed *
Industrial Microbiology Laboratory, Institute of Food Science and Technology (IFST), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
*Author to whom correspondence should be addressed.
Abstract
Aims: Cronobacter sakazakii has been associated most frequently with illness in neonates. This study aims to model effect of temperature on growth of a C. sakazakii isolate (IFST082014).
Methodology: Reconstituted powdered infant milk formulas (RIMFs) inoculated with C. sakazakii were incubated at 10, 20, 30 and 40°C.
Results: The primary model showed a good fit (r2 = 0.9714–0.9821) to a Gompertz equation to obtain growth rates and lag times (LTs) at each temperature. The specific growth rate (SGR) of C. sakazakii in the RIMF increased, and the LT decreased with increasing temperature. The secondary model was “ln SGR = -0.05879+(0.00588 x temperature)+(0.00045 x temperature2).” The SGR predicted using this model increased with an increasing temperature. This secondary polynomial model was judged as appropriate based on the mean square error (MSE of the SGR model = 0.00016), the coefficient of determination (r2 of the SGR model = 0.9845), the bias factor (Bf of the SGR model = 1.0125) and the accuracy factor (Af of the SGR model = 1.0007).
Conclusion: These results will be useful for industry and regulatory agencies.
Keywords: Modelling, temperature, Cronobacter, growth