Physical sample structure as predictive factor in growth modeling of Listeria innocua in a white cheese model system.

Growth of Listeria innocua at 9 °C was investigated in white cheeses manufactured from ultra-filtrate milk concentrate added varying amounts of skimmed milk powder, NaCl and glucono-delta-lactone. Characterization of the white cheese structures was performed using nuclear magnetic resonance (NMR) T2 relaxation parameters (relaxation times constants, relative areas and width of peaks) and their applicability as predictive factors for maximum specific growth rate, √µ(max) and log-increase in 6 weeks of L. innocua was evaluated by polynomial modeling. Inclusion of NMR parameters was able to increase the goodness-of-fit of two basic models; one having pH, undissociated gluconic acid (GA(u), mM) and NaCl (% w/v) as predictive factors and another having pH, GA(u) and a(w) as predictive factors. However, the best model fit was observed using √µ(max) as response for the model including pH, GA(u), aw and Width T21 revealing the lowest relative root mean squared errors of 14.0%. As the T2 relaxation population T21 is assigned to represent immobilized bulk water protons and the width T21 the heterogeneity of this water population, growth of L. innocua in white cheese seemed to be dependent on the heterogeneity of the immobilized bulk water present in cheese.

Water properties in cream cheeses with variations in pH, fat, and salt content and correlation to microbial survival.

Water mobility and distribution in cream cheeses with variations in fat (4, 15, and 26%), added salt (0, 0.625, and 1.25%), and pH (4.2, 4.7, and 5.2) were studied using (1)H NMR relaxometry. The cheese samples were inoculated with a mixture of Listeria innocua, Escherichia coli O157 and Staphylococcus aureus, and partial least-squares regression revealed that (1)H T(2) relaxation decay data were able to explain a large part of the variation in the survival of E. coli O157 (64-83%). However, the predictions of L. innocua and S. aureus survival were strongly dependent on the fat/water content of the samples. Consequently, the present results indicate that NMR relaxometry is a promising technique for predicting the survival of these bacteria; however, the characteristics of the sample matrix are substantial.