Development and validation of predictive models for the effect of storage temperature and pH on the growth boundaries and kinetics of Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks.

This study was undertaken to provide quantitative tools for predicting the behavior of the spoilage bacterium Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks. In the first part of the study, a growth/no growth interface model was developed, predicting the probability of growth as a function of temperature and pH. For this purpose, the growth ability of A. acidoterrestris was studied at different combinations of temperature (15-45 °C) and pH (2.02-5.05). The minimum pH and temperature where growth was observed was 2.52 (at 35 and 45 °C) and 25 °C (at pH ≥ 3.32), respectively. Then a logistic polynomial regression model was fitted to the binary data (0: no growth, 1: growth) and, based on the concordance index (98.8%) and the Hosmer-Lemeshow statistic (6.226, P = 0.622), a satisfactory goodness of fit was demonstrated. In the second part of the study, the effects of temperature (25-55 °C) and pH (3.03-5.53) on A. acidoterrestris growth rate were investigated and quantitatively described using the cardinal temperature model with inflection and the cardinal pH model, respectively. The estimated values for the cardinal parameters Tmin, Tmax, Topt and pHmin, pHmax, pHopt were 18.11, 55.68, 48.60 °C and 2.93, 5.90, 4.22, respectively. The developed models were validated against growth data of A. acidoterrestris obtained in eight commercial pasteurized fruit drinks. The validation results showed a good performance of both models. In all cases where the growth/no growth interface model predicted a probability lower than 0.5, A. acidoterrestris was, indeed, not able to grow in the tested fruit drinks; similarly, when the model predicted a probability above 0.9, growth was observed in all cases. A good agreement was also observed between growth predicted by the kinetic model and the observed kinetics of A. acidoterrestris in fruit drinks at both static and dynamic temperature conditions.

Effect of storage temperature on the lag time of Geobacillus stearothermophilus individual spores.

The lag times (λ) of Geobacillus stearothermophilus single spores were studied at different storage temperatures ranging from 45 to 59 °C using the Bioscreen C method. A significant variability of λ was observed among individual spores at all temperatures tested. The storage temperature affected both the position and the spread of the λ distributions. The minimum mean value of λ (i.e. 10.87 h) was observed at 55 °C, while moving away from this temperature resulted in an increase for both the mean and standard deviation of λ. A Cardinal Model with Inflection (CMI) was fitted to the reverse mean λ, and the estimated values for the cardinal parameters Tmin, Tmax, Topt and the optimum mean λ of G. stearothermophilus were found to be 38.1, 64.2, 53.6 °C and 10.3 h, respectively. To interpret the observations, a probabilistic growth model for G. stearothermophilus individual spores, taking into account λ variability, was developed. The model describes the growth of a population, initially consisting of N0 spores, over time as the sum of cells in each of the N0 imminent subpopulations originating from a single spore. Growth simulations for different initial contamination levels showed that for low N0 the number of cells in the population at any time is highly variable. An increase in N0 to levels exceeding 100 spores results in a significant decrease of the above variability and a shorter λ of the population. Considering that the number of G. stearothermophilus surviving spores in the final product is usually very low, the data provided in this work can be used to evaluate the probability distribution of the time-to-spoilage and enable decision-making based on the "acceptable level of risk".

Development and application of Geobacillus stearothermophilus growth model for predicting spoilage of evaporated milk.

The presence of Geobacillus stearothermophilus spores in evaporated milk constitutes an important quality problem for the milk industry. This study was undertaken to provide an approach in modelling the effect of temperature on G. stearothermophilus ATCC 7953 growth and in predicting spoilage of evaporated milk. The growth of G. stearothermophilus was monitored in tryptone soy broth at isothermal conditions (35-67 °C). The data derived were used to model the effect of temperature on G. stearothermophilus growth with a cardinal type model. The cardinal values of the model for the maximum specific growth rate were Tmin = 33.76 °C, Tmax = 68.14 °C, Topt = 61.82 °C and µopt = 2.068/h. The growth of G. stearothermophilus was assessed in evaporated milk at Topt in order to adjust the model to milk. The efficiency of the model in predicting G. stearothermophilus growth at non-isothermal conditions was evaluated by comparing predictions with observed growth under dynamic conditions and the results showed a good performance of the model. The model was further used to predict the time-to-spoilage (tts) of evaporated milk. The spoilage of this product caused by acid coagulation when the pH approached a level around 5.2, eight generations after G. stearothermophilus reached the maximum population density (Nmax). Based on the above, the tts was predicted from the growth model as the sum of the time required for the microorganism to multiply from the initial to the maximum level ( [Formula: see text] ), plus the time required after the [Formula: see text] to complete eight generations. The observed tts was very close to the predicted one indicating that the model is able to describe satisfactorily the growth of G. stearothermophilus and to provide realistic predictions for evaporated milk spoilage.

Plant-Mediated Effects of Beneficial Microbes and a Plant Strengthener against Spider Mites in Tomato.

The two-spotted spider mite Tetranychus urticae is a polyphagous herbivore with a worldwide distribution, and is a serious pest in tomato and other crops. As an alternative to chemical pesticides, biological control with the release of natural enemies such as predatory mites represent an efficient method to control T. urticae in many crops, but not in tomato. Other biological control agents, such as beneficial microbes, as well as chemical compounds, which can act as plant defense elicitors that confer plant resistance against pests and pathogens, may prove promising biological solutions for the suppression of spider mite populations in tomato. Here, we assessed this hypothesis by recording the effects of a series of fungal and bacterial strains and the plant strengthener acibenzolar-s-methyl for their plant-mediated effects on T. urticae performance in two tomato cultivars. We found significant negative effects on the survival, egg production and spider mite feeding damage on plants inoculated with microbes or treated with the plant strengthener as compared to the control plants. Our results highlight the potential of beneficial microbes and plant strengtheners in spider mite suppression in addition to plant disease control.

Above- and below-ground microbiome in the annual developmental cycle of two olive tree varieties.

The olive tree is a hallmark crop in the Mediterranean region. Its cultivation is characterized by an enormous variability in existing genotypes and geographical areas. As regards the associated microbial communities of the olive tree, despite progress, we still lack comprehensive knowledge in the description of these key determinants of plant health and productivity. Here, we determined the prokaryotic, fungal and arbuscular mycorrhizal fungal (AMF) microbiome in below- (rhizospheric soil, roots) and above-ground (phyllosphere and carposphere) plant compartments of two olive varieties 'Koroneiki' and 'Chondrolia Chalkidikis' grown in Southern and Northern Greece respectively, in five developmental stages along a full fruit-bearing season. Distinct microbial communities were supported in above- and below-ground plant parts; while the former tended to be similar between the two varieties/locations, the latter were location specific. In both varieties/locations, a seasonally stable root microbiome was observed over time; in contrast the plant microbiome in the other compartments were prone to changes over time, which may be related to seasonal environmental change and/or to plant developmental stage. We noted that olive roots exhibited an AMF-specific filtering effect (not observed for bacteria and general fungi) onto the rhizosphere AMF communities of the two olive varieties/locations/, leading to the assemblage of homogenous intraradical AMF communities. Finally, shared microbiome members between the two olive varieties/locations include bacterial and fungal taxa with putative functional attributes that may contribute to olive tree tolerance to abiotic and biotic stress.

Climate change threatens the microbiological stability of non-refrigerated foods.

Most studies on the impact of climate change on foods focus on the consequences to security and safety. In the present study we provide scientific evidence on an overlooked aspect of climate change related to the microbiological stability of foods. Most microbiologically stable processed foods are contaminated with spores of thermophilic spoilage bacteria which are highly heat-resistant and can survive thermal processing. Current temperatures during distribution and storage in temperate climates do not allow growth of thermophilic bacteria to levels that can cause spoilage, ensuring their microbiological stability. Our findings suggest that the latter limiting condition can be eliminated by global warming. By assessing different global warming scenarios for 38 European cities in a case study with canned milk, we show that failing to limit the increase of global mean surface temperature below 2 °C can lead to a very high risk of spoilage and subsequently cause a collapse of the shelf-stable food chain.

Assessment of Escherichia coli O157:H7 growth in ground beef in the Greek chill chain.

A predictive mathematical model of the effect of temperature (10-47 °C) on the growth of Escherichia coli O157:H7 in natural contaminated ground beef was developed. The estimated values for the cardinal parameters Tmin, Tmax, Topt and the optimum maximum specific growth rate (µopt) of E. coli O157:H7 were found to be 3.36, 46.87, 43.16 °C and 1.385/h, respectively. The developed model was further validated against observed growth of E. coli O157:H7 in ground beef at non - isothermal chilling conditions by using two periodically changing temperature profiles with temperature ranging from 0 to 15 °C. Overall the model predicted satisfactorily the growth of E. coli O157:H7 in ground beef at dynamic temperature conditions. The model was combined with temperature data collected from ground beef chill chain in Greece in order to assess the growth of the pathogen from purchase of the product at retail to consumption. Retail storage average temperature from 50 retail cabinets in Greek super markets ranged from 0.1 to 7.4 °C with a mean of 3.2 °C and a mean standard deviation of 1.7 °C. The predicted growth of the pathogen after 7 days of storage at retail ranged between 0 and 2.03 log10 CFU/g, with an average growth to 0.31 log10 CFU/g. The growth of the pathogen during transportation from retail to domestic refrigerators ranged between 0.03 and 0.45 log10 CFU/g, with an average growth to 0.16 log10 CFU/g. The average temperature of 160 domestic refrigerators ranged from -2.7 to 18.1 °C. Differences in the temperature among the shelves of the refrigerators were observed. The predicted growth of E. coli O157:H7 in ground beef stored in domestic refrigerators for 1 day ranged between 0.00 and 2.3 log10 CFU/g. For a scenario storage of ground beef in retail for 3 days, transportation from retail domestic refrigerators over a period of 6 h and storage in domestic refrigerators for 3 days the 99th percentile of the total growth was 4.83 log10 CFU/g for storage at the upper self of the domestic refrigerator. The data and models provided in the present work can be further used in a quantitative risk assessment model of E. coli O157:H7 in ground beef consumed in Greece.

Mapping the risk of evaporated milk spoilage in the Mediterranean region based on the effect of temperature conditions on Geobacillus stearothermophilus growth.

A predictive model for the effect of storage temperature on the growth of Geobacillus stearothermophilus was applied in order to assess the risk of evaporated milk spoilage in the markets of the Mediterranean region. The growth of G. stearothermophilus in evaporated milk was evaluated during a shelf life of one year based on historical temperature profiles (hourly) covering 23 Mediterranean capitals for five years over the period 2012-2016 obtained from the Weather Underground database (http://www.wunderground.com/). In total, 115 scenarios were tested simulating the distribution and storage conditions of evaporated milk in the Mediterranean region. The highest growth of G. stearothermophilus was predicted for Marrakech, Damascus and Cairo over the period 2012-2016 with mean values of 7.2, 7.4 and 5.5 log CFU/ml, respectively, followed by Tunis, Podgorica and Tripoli with mean growth of 2.8, 2.4 and 2.3 log CFU/ml, respectively. For the rest 17 capitals the mean growth of the spoiler was <1.5 log CFU/ml. The capitals Podgorica, Cairo, Tunis and Ankara showed the highest variability in the growth during the 5 years examined with standard deviation values for growth of 2.01, 1.79, 1.77 and 1.25 log CFU/ml, respectively. The predicted extent and the variability of growth during the shelf life were used to assess the risk of spoilage which was visualised in a geographical risk map. The growth model of G. stearothermophilus was also used to evaluate adjustments of the evaporated milk expiration date which can reduce the risk of spoilage. The quantitative data provided in the present study can assist the food industry to effectively evaluate the microbiological stability of these products throughout distribution and storage at a reduced cost (by reducing sampling quality control) and assess whether and under which conditions (e.g. expiration date) will be able to export a product to a country without spoilage problems. This decision support may lead to a significant benefit for both the competitiveness of the food industry and the consumer.