FOOD. Science. Technology. Quality

Food. SCIENCE. Technology. Quality

Food. Science. TECHNOLOGY. Quality

Food. Science. Technology. QUALITY

Authors

KATARZYNA KAJAK, DANUTA KOŁOŻYN-KRAJEWSKA

Title

Assessment of the shelf-life of meat products using predictive models

Abstract

The objective of this paper was to construct and develop predictive models, the application of which it makes possible to assess the shelf-life of meat products produced of ground beet meat. There were constructed primary linear models with a free parameter of growth of the total viable count (TVC) [log cfu/g] containing all the analyzed variables (the addition of NaCl and NaNO2, storage time, and temperature); the said models were constructed using a linear regression, as well as Gompertz (G) and logistic (L) response surface models of the growth of total viable count (TVC) [log cfu/g] including the impact as exerted by NaCl and NaNO2 added. The computation was performed using a nonlinear least squares method supported by the Gauss-Newton  algorithm. On the basis of the results obtained from the microbiological analyses performed, linear models of the total viable count (TVC) were developed; with those models, it was possible to assess the shelf-life of meat products, and, first of all, of those stored at a low temperature (5ºC). The Gompertz and logistic surface response models obtained and statistically well fitted, enable manufacturers to satisfactorily predict the shelf-life of meat products, in particular of those stored at a higher storage temperature (15ºC).

Keywords

predictive microbiology, modelling, beef-meat, NaCl, NaNO2

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