The relation between temperature and growth of bacteria in dairy products

Short communication: Postpasteurization hold temperatures of 4 or 6°C, but not raw milk holding of 24 or 72 hours, affect bacterial outgrowth in pasteurized fluid milk

As fluid milk processors continue to reduce microbial spoilage in fluid milk through improved control of postpasteurization contamination and psychrotolerant sporeformer outgrowth, it is necessary to identify strategies to further improve the quality and extend the shelf life of fluid milk products that are high-temperature, short-time pasteurized. Solutions that optimize product quality, and are economically feasible, are of particular interest to the dairy industry. To this end, this study examined the effects of raw milk holding time and temperature of pasteurized milk storage over shelf life on bacterial growth. In 3 independent replicates, raw milk was stored for 24 and 72 h before pasteurization at 76°C for 25s and then incubated at 3 different storage conditions: (1) 4°C for 21d; (2) 4°C for the first 48 h, then 6°C for the duration of the 21-d shelf life; or (3) 6°C for 21d. Total bacteria counts were assessed initially and on d 7, 14, and 21. No substantial difference in bacterial growth over shelf life was observed between samples processed from raw milk held for 24 versus 72 h. A significantly lower bacterial load was seen at d 21 after pasteurization in samples held at 4°C, versus 4°C for the first 48 h followed by 6°C for the duration of the 21-d shelf life and samples held at 6°C for 21d. This work demonstrates the importance of maintaining control of the fluid milk cold chain throughout postpasteurization, transportation, and retail storage on fluid milk microbial quality.

The effect of micro-architectural structure of cabbage substratum and or background bacterial flora on the growth of Listeria monocytogenes

The effect of micro-architectural structure of cabbage (Brassica oleracea var. capitata L.) substratum and or background bacterial flora on the growth of Listeria monocytogenes as a function of incubation temperature was investigated. A cocktail mixture of Pseudomonas fluorescens, Pantoea agglomerans and Lactobacillus plantarum was constituted to a population density of approximately 5 log CFU/ml in order to pseudo-simulate background bacterial flora of fresh-cut cabbage. This mixture was co-inoculated with L. monocytogenes (approximately 3 log CFU/ml) on fresh-cut cabbage or in autoclaved cabbage juice followed by incubation at different temperatures (4-30 degrees C). Data on growth of L. monocytogenes were fitted to the primary growth model of Baranyi in order to generate the growth kinetic parameters of the pathogen. During storage, microbial ecology was dominated by P. fluorescens and L. plantarum at refrigeration and abuse temperature, respectively. At all temperatures investigated, lag duration (lambda, h), maximum specific growth rate (micro(max), h(-1)) and maximum population density (MPD, log CFU/ml) of L. monocytogenes were only affected by medium micro-architectural structure, except at 4 degrees C where it had no effect on the micro(max) of the pathogen. Comparison of observed values of micro(max) with those obtained from the Pathogen Modelling Program (PMP), showed that PMP overestimated the growth rate of L. monocytogenes on fresh-cut cabbage and in cabbage juice, respectively. Temperature dependency of micro(max) of L. monocytogenes, according to the models of Ratkowsky and Arrhenius, showed linearity for temperature range of 4-15 degrees C, discontinuities and linearity again for temperature range of 20-30 degrees C. The results of this experiment have shown that the constituted background bacterial flora had no effect on the growth of L. monocytogenes and that micro-architectural structure of the vegetable was the primary factor that limited the applicability of PMP model for predicting the growth of L. monocytogenes on fresh-cut cabbage. A major limitation of this study however is that nutrient profile of the autoclaved cabbage juice may be different from that of the raw juice thus compromising realistic comparison of the behaviour of L. monocytogenes as affected by micro-architectural structure.

Predictive food microbiology for the meat industry: a review

Predictive food microbiology (PFM) is an emerging multidisciplinary area of food microbiology. It encompasses such disciplines as mathematics, microbiology, engineering and chemistry to develop and apply mathematical models to predict the responses of microorganisms to specified environmental variables. This paper provides a critical review on the development of mathematical modelling with emphasis on modelling techniques, descriptions, classifications and their recent advances. It is concluded that the role and accuracy of predictive food microbiology will increase as understanding of the complex interactions between microorganisms and food becomes clearer. However the reliance of food microbiology on laboratory techniques and skilled personnel to determine process and food safety is still necessary.

Shelf life prediction: status and future possibilities

Although there is rapid progress in the field of chemical detection technology, little of this technology appears to have found application in estimation of the remaining shelf life of foods and early detection of spoilage. Predictive microbiology aims to summarise the probable behaviour of specific spoilage organisms and the progression of spoilage processes in foods. The quantitative knowledge generated in the field of predictive microbiology provides a sound basis for the rational development of devices with which to monitor loss of product shelf life during storage, distribution and retail sale. To predict remaining shelf life accurately it is necessary, however, to consider the microbial ecology of the food system. Aspects of microbial ecology and physiology relevant to the spoilage of foods are briefly reviewed and the potential benefits of the use of predictive microbiology in shelf life estimation are described. These points are exemplified by reference to a modelling program undertaken to develop, validate and 'package' in an easily useable from, models of the effect of temperature, water activity and pH on the growth rate of psychrotrophic spoilage pseudomonads. Necessary properties of devices to monitor loss of shelf life are discussed. 'Bioindicators' are identified as potential monitors of spoilage and suggestions made for their development based on the concept of 'upper limiting bacterial growth' rates, for which preliminary evidence is presented.

Predictive modelling: applications in the dairy industry

Predictive modelling has been used in the dairy industry for determining the keeping quality of raw milk and pasteurized products. More recently, predictive equations describing growth and toxin production for a number of bacteria of concern to dairy microbiologists have been developed. A more mathematical approach is also being adopted for determining effective pasteurization conditions for organisms present in milk.

Predictive microbiology

Predictive microbiology is based upon the premise that the responses of populations of microorganisms to environmental factors are reproducible, and that by considering environments in terms of identifiable dominating constraints it is possible, from past observations, to predict the responses of those microorganisms. Proponents claim that predictive microbiology offers many benefits to the practice of food microbiology, and there is growing interest internationally. This review considers the origins, benefits and approaches to predictive microbiology and critically considers limitations and potential solutions. It is suggested that the traditional delineation between kinetic and probabilistic models is artificial, and that the two approaches represent the opposite ends of a spectrum of modelling needs. It is concluded: that despite the complexity of many food systems predictive modelling can be successfully applied; that strategies based on predictive models can simplify problems and allow useful predictions and analyses to be made; that the full potential of the technique has not yet been realised; and that "predictive microbiology" may be seen as providing a rational framework for understanding the microbial ecology of food.

Psychrotrophs in dairy products: their effects and their control

Health concerns and technological effects of psychrotrophic bacteria in dairy products are reviewed, as well as methods to control their presence and development. The various Gram-negative and Gram-positive psychrotrophic species are listed and, with respect to pathogenic psychrotrophs, emphasis is given on Listeria monocytogenes, Yersinia enterocolitica, and Bacillus cereus. The influence of psychrotrophic bacteria on the quality of raw milk, pasteurized and UHT milks, butter, ice cream, cheese, and powders is examined. Public health considerations of Listeria monocytogenes, Yersinia enterocolitica, and Bacillus cereus of these various dairy products are also presented. Methods that can be used to eliminate or control the development of psychrotropic bacteria include low or high temperatures, chemicals, gases, the lactoperoxidase system, lactic acid bacteria, microfiltration, bactofugation, lactoferrin-related proteins, sanitation, flavors, and naturally occurring spore germinants.

Modeling of bacterial growth as a function of temperature

The temperature of chilled foods is a very important variable for microbial safety in a production and distribution chain. To predict the number of organisms as a function of temperature and time, it is essential to model the lag time, specific growth rate, and asymptote (growth yield) as a function of temperature. The objective of this research was to determine the suitability and usefulness of different models, either available from the literature or newly developed. The models were compared by using an F test, by which the lack of fit of the models was compared with the measuring error. From the results, a hyperbolic model was selected for the description of the lag time as a function of temperature. Modified forms of the Ratkowsky model were selected as the most suitable model for both the growth rate and the asymptote as a function of temperature. The selected models could be used to predict experimentally determined numbers of organisms as a function of temperature and time.

Modelling the growth response of Staphylococcus xylosus to changes in temperature and glycerol concentration/water activity

The growth response of Staphylococcus xylosus strain CM21/3 to changes in temperature and water activity (glycerol concentration) was similar to that observed when water activity was adjusted by added NaCl. At each water activity level the effect of temperature on bacterial growth rate was described well by the square root model. TMIN (the notional minimum temperature for growth) was found to be constant and was similar to the value obtained for the same organism grown in media containing NaCl. Growth rate was proportional to glycerol concentration/water activity allowing the combined effect of this factor and temperature to be modelled by substitution of the constant b in the basic square root model by a term for water activity. The observed minimum water activity for growth at the optimum temperature was close to that predicted by the model.