Abstract

The presence and growth of spoilage organisms in food might affect the shelf life. In this study, the effects of experimental, reproduction, and strain variabilities were quantified with respect to growth and thermal inactivation using 20 Lactobacillus plantarum strains. Also, the effect of growth history on thermal resistance was quantified. The strain variability in μmax was similar (P > 0.05) to reproduction variability as a function of pH, aw, and temperature, while being around half of the reproduction variability (P < 0.05) as a function of undissociated lactic acid concentration [HLa]. The cardinal growth parameters were estimated for the L. plantarum strains, and the pHmin was between 3.2 and 3.5, the aw,min was between 0.936 and 0.953, the [HLamax], at pH 4.5, was between 29 and 38 mM, and the Tmin was between 3.4 and 8.3°C. The average D values ranged from 0.80 min to 19 min at 55°C, 0.22 to 3.9 min at 58°C, 3.1 to 45 s at 60°C, and 1.8 to 19 s at 63°C. In contrast to growth, the strain variability in thermal resistance was on average six times higher than the reproduction variability and more than ten times higher than the experimental variability. The strain variability was also 1.8 times higher (P < 0.05) than the effect of growth history. The combined effects of strain variability and growth history on D value explained all of the variability as found in the literature, although with bias. Based on an illustrative milk-processing chain, strain variability caused ∼2-log10 differences in growth between the most and least robust strains and >10-log10 differences after thermal treatment. Accurate control and realistic prediction of shelf life is complicated by the natural diversity among microbial strains, and limited information on microbiological variability is available for spoilage microorganisms. Therefore, the objectives of the present study were to quantify strain variability, reproduction (biological) variability, and experimental variability with respect to the growth and thermal inactivation kinetics of Lactobacillus plantarum and to quantify the variability in thermal resistance attributed to growth history. The quantitative knowledge obtained on experimental, reproduction, and strain variabilities can be used to improve experimental designs and to adequately select strains for challenge growth and inactivation tests. Moreover, the integration of strain variability in prediction of microbial growth and inactivation kinetics will result in more realistic predictions of L. plantarum dynamics along the food production chain.

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