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

摘要

Growth of Listeria innocua at 9 ℃ 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) T_2 relaxation parameters (relaxation times constants, relative areas and width of peaks) and their applicability as predictive factors for maximum specific growth rate, (μ_(max))～(1/2) 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))～(1/2) as response for the model including pH, GA_U, a_w and Width T_(21) revealing the lowest relative root mean squared errors of 14.0%. As the T_2 relaxation population T_(21) is assigned to represent immobilized bulk water protons and the width T_(21) 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.