The effect of the olive phenolic compound, oleuropein, on growth and enterotoxin B production by Staphylococcus aureus

The presence of low concentrations (0.1% w/v) of oleuropein, a phenolic compound extracted from olives, delayed the growth of Staphylococcus aureus in NZ amine A and brain heart infusion media modified by the addition of growth factors and glucose (NZA + and BHI +), as indicated by changes in conductance, whilst higher concentrations (0.4–0.6% w/v) inhibited growth completely. Intermediate concentrations of oleuropein (0.2%) prevented growth in BHI + but allowed growth to occur in NZA + despite an extended lag phase (30 h). Concentrations of oleuropein > 0.2% inhibited growth and production of enterotoxin B in both types of media. Lower levels (0.1%) did not affect the final viable count and production of toxin in BHI + but decreased the number of viable organisms and reduced the toxin production in NZA + by eightfold. An increase in the concentration of oleuropein resulted in a decrease in the amount of glucose assimilated and consequently the amount of lactate produced. In addition, oleuropein prevented the secretion of a number of exoproteins. Addition of oleuropein during the exponential phase appeared to have no effect on the growth of Staph. aureus in NZA +.     

Inhibition of Salmonella enteritidis by oleuropein in broth and in a model food system

The inhibitory effect of commercial 'pure' oleuropein was tested against Salmonella enteritidis in a coliform broth and in reconstituted milk (model food system). It was found that the inhibition of this organism in the broth was influenced by the initial inoculum size, the pH of the medium and the concentration of additive. The inhibition was more pronounced in samples with low pH and low inoculum size. No such inhibition was evident in the model food system.     

Image analysis as a mean to model growth of Escherichia coli O157:H7 in gel cassettes

AIMS: The potential of image analysis for rapid and quantitative determination of the effect of environmental parameters such as temperature and pH on the growth of colonies of Escherichia coli O157:H7 derived from immobilized cells in gel cassettes was investigated. METHODS AND RESULTS: The organism was grown in brain heart infusion agar contained within a cassette formed between sheets of PVC film. The medium was adjusted to pH 5, 6 or 7 and incubated at 10, 20, 30 or 40 degrees C. The primary model of Baranyi was used to fit the growth data obtained by conventional plate counting and changes in colony area (2-dimensional spread of colonies) by light microscopy to derive estimates of maximum specific growth rates (micromax and Area micromax) in both cases. Growth rate values from both measurements were correlated and a secondary quadratic model was developed to predict micromax obtained via image analysis in response to environmental factors (temperature and pH). A progressive decrease of micromax and Area micromax was observed at lower temperatures and pH values. Immobilized cells failed to initiate growth at a pH of 5.0 and 10 degrees C. There was high correlation between micromax values estimated by conventional plate counting and Area micromax values from microscopic observations in gel cassettes, regardless of temperature and pH. The values of micromax derived indirectly from the correlation with Area micromax values fitted well to the secondary model and gave realistic predictions of maximum specific growth rate values estimated by standard plate counting. CONCLUSIONS: The micromax of E. coli O157:H7 determined by plate counting was linearly correlated with Area micromax estimated by light microscopy, enabling indirect determination of micromax via the Area micromax. The estimates of micromax via the image analysis technique may be further modelled in response to environmental factors such as temperature and pH to predict the response of the organism in intermediate conditions. SIGNIFICANCE AND IMPACT OF THE STUDY: Image analysis in combination with gel cassettes could be a potential tool for rapid and convenient data collection and construction of accurate mathematical models as an alternative to conventional plate counting methods.     

Modelling the combined effect of temperature,pH and aw on the growth rate of Monascus ruber,a heat-resistant fungus isolated from green table olives

AIMS: Growth modes predicting the effect of pH (3.5-5.0), NaCl (2-10%), i.e. aw (0.937-0.970) and temperature (20-40 degrees C) on the colony growth rate of Monascus ruber, a fungus isolated from thermally-processed olives of the Conservolea variety, were developed on a solid culture medium. METHODS AND RESULTS: Fungal growth was measured as colony diameter on a daily basis. The primary predictive model of Baranyi was used to fit the growth data and estimate the maximum specific growth rates. Combined secondary predictive models were developed and comparatively evaluated based on polynomial, Davey, gamma concept and Rosso equations. The data-set was fitted successfully in all models. However, models with biological interpretable parameters (gamma concept and Rosso equation) were highly rated compared with the polynomial equation and Davey model and gave realistic cardinal pHs, temperatures and aw. CONCLUSIONS: The combined effect of temperature, pH and aw on growth responses of M. ruber could be satisfactorily predicted under the current experimental conditions, and the models examined could serve as tools for this purpose. SIGNIFICANCE AND IMPACT OF THE STUDY: The results can be successfully employed by the industry to predict the extent of fungal growth on table olives.     

Probabilistic Model for Listeria monocytogenes Growth during Distribution,Retail Storage,and Domestic Storage of Pasteurized Milk

A survey on the time-temperature conditions of pasteurized milk in Greece during transportation to retail, retail storage, and domestic storage and handling was performed. The data derived from the survey were described with appropriate probability distributions and introduced into a growth model of Listeria monocytogenes in pasteurized milk which was appropriately modified for taking into account strain variability. Based on the above components, a probabilistic model was applied to evaluate the growth of L. monocytogenes during the chill chain of pasteurized milk using a Monte Carlo simulation. The model predicted that, in 44.8% of the milk cartons released in the market, the pathogen will grow until the time of consumption. For these products the estimated mean total growth of L. monocytogenes during transportation, retail storage, and domestic storage was 0.93 log CFU, with 95th and 99th percentiles of 2.68 and 4.01 log CFU, respectively. Although based on EU regulation 2073/2005 pasteurized milk produced in Greece belongs to the category of products that do not allow the growth of L. monocytogenes due to a shelf life (defined by law) of 5 days, the above results show that this shelf life limit cannot prevent L. monocytogenes from growing under the current chill chain conditions. The predicted percentage of milk cartons—initially contaminated with 1 cell/1-liter carton—in which the pathogen exceeds the safety criterion of 100 cells/ml at the time of consumption was 0.14%. The probabilistic model was used for an importance analysis of the chill chain factors, using rank order correlation, while selected intervention and shelf life increase scenarios were evaluated. The results showed that simple interventions, such as excluding the door shelf from the domestic storage of pasteurized milk, can effectively reduce the growth of the pathogen. The door shelf was found to be the warmest position in domestic refrigerators, and it was most frequently used by the consumers for domestic storage of pasteurized milk. Furthermore, the model predicted that a combination of this intervention with a decrease of the mean temperature of domestic refrigerators by 2°C may allow an extension of pasteurized milk shelf life from 5 to 7 days without affecting the current consumer exposure to L. monocytogenes.L. monocytogenes is an important safety concern for the dairy industry. Several listeriosis outbreaks have been associated with the consumption of dairy products, including pasteurized milk (13, 22). An effective control of L. monocytogenes in pasteurized milk should be based on the selection of raw milk and the controls of the processing, packaging, distribution, and storage conditions. In general, the pathogen is effectively controlled during pasteurization. However, its presence in the finished product is possible as a result of postpasteurization contamination from sources in the plant environment. Considering that the levels of postpasteurization contamination are usually very low, the extent of L. monocytogenes growth during distribution, retail storage, and domestic storage is of major significance for the safety status of pasteurized milk at the time of consumption.The growth of L. monocytogenes during distribution and storage of pasteurized milk can be evaluated using the available predictive models. During the last decade, a large number of mathematical models for L. monocytogenes growth have been published (9, 11, 16, 19, 21, 24, 26, 31, 38), and some of them have been targeted to pasteurized milk (1, 40, 49). However, since the available data show that conditions that prevail during the chill chain vary significantly (8, 17, 23, 27, 28, 34, 44, 45, 48), the value of a deterministic application of these models as a tool in safety management of pasteurized milk would be limited.In recent years the need for taking into account the variabilities of the various factors in predictive microbiology has been increasingly recognized, leading to a more sophisticated modeling approach called probabilistic or stochastic modeling. The main characteristic of probabilistic modeling is the specific quantification of variabilities using probability distributions for the input data rather than point estimates. The importance of characterizing variability was stressed by Nauta (41), who illustrated the differences in decisions that could result if variability is ignored. Probabilistic modeling is being used with increasing frequency in the area of food safety. It has been extensively applied in quantitative microbial risk assessments (12, 18, 20), in quality and safety management systems (25, 30, 32), and recently for more specific topics, such as the evaluation of the effects of food processing (39) and the compliance of food products to safety criteria set by regulations (33).In the present study a probabilistic modeling approach was applied for evaluating the growth of Listeria monocytogenes in pasteurized milk from production to the time of consumption based on a Monte Carlo simulation. The objectives of the study were (i) to estimate the growth of the pathogen at the various stages of the chill chain, including transportation to retail, retail storage, and domestic storage, (ii) to analyze the importance of the chill chain factors, (iii) to evaluate the effects of selected intervention scenarios related to the improvement of the chill chain and handling conditions, and (iv) to evaluate the effect of a potential extension of milk shelf life on the growth of Listeria monocytogenes.     

Yeast Populations Residing on Healthy or Botrytis-Infected Grapes from a Vineyard in Attica, Greece

The yeast flora associated with healthy and Botrytis-infected grapes was assessed. Molecular identification methods assigned isolates to six genera and nine species. For the first time Hanseniaspora opuntiae was encountered as an inhabitant of the grape ecosystem. By using DraI, an informative restriction fragment length polymorphism pattern was generated to distinguish H. opuntiae from the closely related organism Hanseniaspora guilliermondii. Botrytis infection resulted in a larger population and greater diversity of yeasts enriched with fermentative or spoilage species.     

Bacterial Synergism or Antagonism in a Gel Cassette System

The growth and the metabolic activity of Shewanella putrfaciens, Brochothrix thermosphacta, and Pseudomonas sp., when cultured individually or in all possible combinations in gel cassettes system supplemented with 0.1% glucose at 5°C, were investigated. The overall outcome was that the coexistence of the above-mentioned microorganisms affected not only each growth rate but also their type of metabolic end products compared to the control cultures. These effects were varied and depended on the selection of the combination of the tested bacteria. For example, the growth of Pseudomonas sp. strains cocultured with either B. thermosphacta or S. putrefaciens strains resulted in different effects: a promoting one for the first and an inhibitory one for the second. Moreover, the production of formic acid and two unidentified organic acids (peaks a and b) was characteristic in all cases in which S. putrefaciens was cultured.     

Development of a Microbial Model for the Combined Effect of Temperature and pH on Spoilage of Ground Meat, and Validation of the Model under Dynamic Temperature Conditions

The changes in microbial flora and sensory characteristics of fresh ground meat (beef and pork) with pH values ranging from 5.34 to 6.13 were monitored at different isothermal storage temperatures (0 to 20°C) under aerobic conditions. At all conditions tested, pseudomonads were the predominant bacteria, followed by Brochothrix thermosphacta, while the other members of the microbial association (e.g., lactic acid bacteria and Enterobacteriaceae) remained at lower levels. The results from microbiological and sensory analysis showed that changes in pseudomonad populations followed closely sensory changes during storage and could be used as a good index for spoilage of aerobically stored ground meat. The kinetic parameters (maximum specific growth rate [μ_max] and the duration of lag phase [λ]) of the spoilage bacteria were modeled by using a modified Arrhenius equation for the combined effect of temperature and pH. Meat pH affected growth of all spoilage bacteria except that of lactic acid bacteria. The “adaptation work,” characterized by the product of μ_max and λ(μ_max × λ) was found to be unaffected by temperature for all tested bacteria but was affected by pH for pseudomonads and B. thermosphacta. For the latter bacteria, a negative linear correlation between ln(μ_max × λ) and meat pH was observed. The developed models were further validated under dynamic temperature conditions using different fluctuating temperatures. Graphical comparison between predicted and observed growth and the examination of the relative errors of predictions showed that the model predicted satisfactorily growth under dynamic conditions. Predicted shelf life based on pseudomonads growth was slightly shorter than shelf life observed by sensory analysis with a mean difference of 13.1%. The present study provides a “ready-to-use,” well-validated model for predicting spoilage of aerobically stored ground meat. The use of the model by the meat industry can lead to effective management systems for the optimization of meat quality.     

Growth/survival of Salmonella enteritidis on fresh poultry and fish stored under vacuum or modified atmosphere

G.-J.E. NYCHAS AND C.C. TASSOU. 1996. The effect of vacuum and modified atomosphere packaging on the growth/survival of Samonella entertidis on fresh poultry and fish (Boops boos) is described. Salmonella enteritidis survived but did not grow significantly in all samples (poultry or fish) at 3^oC. At 10^oC the numbers of Salm. enteritidis increased rapidly in vacuum-packed samples and in samples flushed with 100% N₂, 20%, CO²/80% O² of both types of proteinaceous food. Growth was also evident in fish and poultry flushed with 100% CO²; however the rate of growth was greater in fish samples rather than in poultry.     

The influence of different oils on the death rate of Salmonella enteritidis in homemade mayonnaise

The death rate of Salmonella enteritidis was always faster in mayonnaise made with extra virgin olive oil than in that prepared from blended olive or sunflower oils. The acidity and the phenolic profiles of these oils differed significantly. The most acidic oils (0·5% oleic acid), the extra virgin oils, also had the most complex phenolic profiles. The acidity of sunflower and blended olive oil was 0·2% and 0·4% respectively.