A probabilistic approach to determine thermal process setting parameters: application for commercial sterility of products

Cardinal models to describe the effect of temperature and pH on the growth of Anoxybacillus flavithermus & Bacillus licheniformis

Anoxybacillus flavithermus and Bacillus licheniformis are among the predominant spore-formers of heat-processed foods. To our knowledge, no systematic analysis of growth kinetic data of A. flavithermus or B. licheniformis is currently available. In the present study, the growth kinetics of A. flavithermus and B. licheniformis in broth at various temperature and pH conditions were studied. Cardinal models were used to model the effect of the above-mentioned factors on the growth rates. The estimated values for the cardinal parameters T_min,T_opt,T_max,pH_min and pH_1/2 for A. flavithermus were 28.70 ± 0.26, 61.23 ± 0.16 and 71.52 ± 0.32 °C, 5.52 ± 0.01 and 5.73 ± 0.01, respectively, while for B. licheniformis they were 11.68 ± 0.03, 48.05 ± 0.15, 57.14 ± 0.01 °C, 4.71 ± 0.01 and 5.670 ± 0.08, respectively. The growth behaviour of these spoilers was also investigated in a pea beverage at 62 and 49 °C, respectively, to adjust the models to this product. The adjusted models were further validated at static and dynamic conditions and demonstrated good performance with 85.7 and 97.4% of predicted populations for A. flavithermus and B. licheniformis, respectively, being within the -10%-10% relative error (RE) zone. The developed models can be useful tools in assessing the potential of spoilage of heat-processed foods including plant-based milk alternatives.

Quantitative microbial spoilage risk assessment of plant-based milk alternatives by Geobacillus stearothermophilus in Europe

Geobacillus stearothermophilus is one of the predominant spoilers of UHT-treated food products, due to its extremely heat-resistant spores. However, the surviving spores should be exposed to temperature higher than their minimum growth temperature for a certain time to germinate and grow to spoilage levels. Considering the projected temperature increase due to climate change, the events of non-sterility during distribution and transportation are expected to escalate. Hence, the aim of this study was to build a quantitative microbial spoilage risk assessment (QMRSA) model to quantify the risk of spoilage of plant-based milk alternatives within Europe. The model consists of four main steps: 1. Initial contamination of raw materials 2. Heat inactivation of spores during UHT treatment 3. Partitioning 4. Germination and outgrowth of spores during distribution and storage. The risk of spoilage was defined as the probability of G. stearothermophilus to reach its maximum concentration (N_max = 10^7.5 CFU/mL) at the time of consumption. The assessment was performed for North (Poland) and South (Greece) Europe, and the risk of spoilage was estimated for the current climatic conditions and a climate change scenario. Based on the results, the risk of spoilage was negligible for the North European region, while the risk of spoilage in South Europe was 6.2 × 10^-3 95% CI (2.3 × 10^-3;1.1 × 10^-2) under the current climatic conditions. The risk of spoilage was increased for both tested countries under climate change scenario; from zero to 1.0 × 10^-4 in North Europe, risk multiplied 2 or 3 in South Europe depending on air conditioning implementation at consumer's place. Therefore, the heat treatment intensity and the use of insulated trucks during distribution were investigated as mitigation strategies and led to significant reduction of the risk. Overall, the QMRSA model developed in this study can support risk management decisions of these products by quantify the potential risk under current climatic conditions and climate change scenarios.

Development and validation of a predictive model for the effect of temperature, pH and water activity on the growth kinetics of Bacillus coagulans in non-refrigerated ready-to-eat food products

A cardinal model (CM) for the effects of temperature (range: 32-59 °C), pH (range: 5.0-8.5) and water activity (a_w) (range: 0.980-0.995) on Bacillus coagulans DSM 1 growth rate was developed in brain heart infusion broth (BHI), using the Bioscreen C method and further validated in selected food products. The estimated values for the cardinal parameters T_min, T_opt, T_max, pH_min, pH_opt, pH_max, [Formula: see text] and [Formula: see text] were 23.77 ± 0.19 °C, 52.89 ± 0.01 °C, 59.37 ± 0.07 °C, 4.70 ± 0.02, 6.43 ± 0.02, 8.56 ± 0.01, 0.969 ± 0.0007 and 0.998 ± 0.0011, respectively. The growth behaviour of B. coagulans was studied in five commercial non-refrigerated ready-to-eat food products under static conditions at 53 °C in order to estimate the optimum specific growth rate for each tested food product. The developed models were validated in the five selected food products under four different dynamic temperature profiles by comparing predicted and observed growth behaviour of B. coagulans. The validation results indicated a good performance of the model for all tested products with the overall Bias factor (B_f) and Accuracy factor (A_f) estimated at 1.00 and 1.12, respectively. The developed model can be considered an effective tool in predicting B. coagulans growth and spoilage risks of non-refrigerated ready-to-eat food products during distribution and storage.

The COM-Poisson Process for Stochastic Modeling of Osmotic Inactivation Dynamics of Listeria monocytogenes

Controlling harmful microorganisms, such as Listeria monocytogenes, can require reliable inactivation steps, including those providing conditions (e.g., using high salt content) in which the pathogen could be progressively inactivated. Exposure to osmotic stress could result, however, in variation in the number of survivors, which needs to be carefully considered through appropriate dispersion measures for its impact on intervention practices. Variation in the experimental observations is due to uncertainty and biological variability in the microbial response. The Poisson distribution is suitable for modeling the variation of equi-dispersed count data when the naturally occurring randomness in bacterial numbers it is assumed. However, violation of equi-dispersion is quite often evident, leading to over-dispersion, i.e., non-randomness. This article proposes a statistical modeling approach for describing variation in osmotic inactivation of L. monocytogenes Scott A at different initial cell levels. The change of survivors over inactivation time was described as an exponential function in both the Poisson and in the Conway-Maxwell Poisson (COM-Poisson) processes, with the latter dealing with over-dispersion through a dispersion parameter. This parameter was modeled to describe the occurrence of non-randomness in the population distribution, even the one emerging with the osmotic treatment. The results revealed that the contribution of randomness to the total variance was dominant only on the lower-count survivors, while at higher counts the non-randomness contribution to the variance was shown to increase the total variance above the Poisson distribution. When the inactivation model was compared with random numbers generated in computer simulation, a good concordance between the experimental and the modeled data was obtained in the COM-Poisson process.

Development and validation of an extended predictive model for the effect of pH and water activity on the growth kinetics of Geobacillus stearothermophilus in plant-based milk alternatives

The cardinal model for the effect of temperature on Geobacillus stearothermophilus ATCC 7953 growth developed by Kakagianni, Gougouli, & Koutsoumanis, 2016 was expanded for the effect of pH and water activity (a_w). The effect of pH (range: 5.7-8.5) and a_w (range: 0.985-0.999) on G. stearothermophilus growth rate was studied in tryptone soy broth (TSB) using the Bioscreen C method and further modelled using a Cardinal Model (CM). The estimated values for the cardinal parameters [Formula: see text] , and [Formula: see text] were 5.65 ± 0.14, 6.74 ± 0.03, 8.71 ± 0.03, 0.984 ± 0.007 and 0.998 ± 0.001, respectively. The growth behaviour of G. stearothermophilus was investigated in 7 commercial non-refrigerated plant-based milk alternatives under static conditions (62 °C) and the estimated maximum specific growth rates were used to determine the optimum growth rate for each product. The developed model was validated against observed growth of G. stearothermophilus in the 7 products during storage at non-isothermal conditions (testing 4 different temperature profiles). The validation results showed a good performance of the model with overall Bias factor (B_f) = 1.06 and Accuracy factor (A_f) = 1.12. The developed model can be used as an effective tool by the food industry in predicting spoilage of plant-based milk alternatives during distribution and storage at retail and domestic levels.

Ultraviolet-C inactivation and hydrophobicity of Bacillus subtilis and Bacillus velezensis spores isolated from extended shelf-life milk

Bacterial spores are important in food processing due to their ubiquity, resistance to high temperature and chemical inactivation. This work aims to study the effect of ultraviolet C (UVC) on the spores of Bacillus subtilis and Bacillus velezensis at a molecular and individual level to guide in deciding on the right parameters that must be applied during the processing of liquid foods. The spores were treated with UVC using phosphate buffer saline (PBS) as a suspension medium and their lethality rate was determined for each sample. Purified spore samples of B. velezensis and B. subtilis were treated under one pass in a UVC reactor to inactivate the spores. The resistance pattern of the spores to UVC treatment was determined using dipicolinic acid (Ca-DPA) band of spectral analysis obtained from Raman spectroscopy. Flow cytometry analysis was also done to determine the effect of the UVC treatment on the spore samples at the molecular level. Samples were processed for SEM and the percentage spore surface hydrophobicity was also determined using the Microbial Adhesion to Hydrocarbon (MATH) assay to predict the adhesion strength to a stainless-steel surface. The result shows the maximum lethality rate to be 6.5 for B. subtilis strain SRCM103689 (B47) and highest percentage hydrophobicity was 54.9% from the sample B. velezensis strain LPL-K103 (B44). The difference in surface hydrophobicity for all isolates was statistically significant (P < 0.05). Flow cytometry analysis of UVC treated spore suspensions clarifies them further into sub-populations unaccounted for by plate counting on growth media. The Raman spectroscopy identified B4002 as the isolate possessing the highest concentration of Ca-DPA. The study justifies the critical role of Ca-DPA in spore resistance and the possible sub-populations after UVC treatment that may affect product shelf-life and safety. UVC shows a promising application in the inactivation of resistant spores though there is a need to understand the effects at the molecular level to design the best parameters during processing.

Describing Uncertainty in Salmonella Thermal Inactivation Using Bayesian Statistical Modeling

Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. In the context of microbial risk assessment, the uncertainty in the predicted microbial behavior can be an important component of the overall uncertainty. Conventional deterministic modeling approaches which provide point estimates of the pathogen's levels cannot quantify the uncertainty around the predictions. The objective of this study was to use Bayesian statistical modeling for describing uncertainty in predicted microbial thermal inactivation of Salmonella enterica Typhimurium DT104. A set of thermal inactivation data in broth with water activity adjusted to 0.75 at 9 different temperature conditions obtained from the ComBase database (www.combase.cc) was used. A log-linear microbial inactivation was used as a primary model while for secondary modeling, a linear relation between the logarithm of inactivation rate and temperature was assumed. For comparison, data were fitted with a two-step and a global Bayesian regression. Posterior distributions of model's parameters were used to predict Salmonella thermal inactivation. The combination of the joint posterior distributions of model's parameters allowed the prediction of cell density over time, total reduction time and inactivation rate as probability distributions at different time and temperature conditions. For example, for the time required to eliminate a Salmonella population of about 107 CFU/ml at 65°C, the model predicted a time distribution with a median of 0.40 min and 5th and 95th percentiles of 0.24 and 0.60 min, respectively. The validation of the model showed that it can describe successfully uncertainty in predicted thermal inactivation with most observed data being within the 95% prediction intervals of the model. The global regression approach resulted in less uncertain predictions compared to the two-step regression. The developed model could be used to quantify uncertainty in thermal inactivation in risk-based processing design as well as in risk assessment studies.

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.

Development of a Quantitative PCR Assay for Thermophilic Spore-Forming Geobacillus stearothermophilus in Canned Food

The thermophilic spore forming bacteria Geobacillus stearothermophilus is recognized as a major cause of spoilage in canned food. A quantitative real-time PCR assay was developed to specifically detect and quantify the species G. stearothermophilus in samples from canned food. The selected primer pairs amplified a 163-bp fragment of the 16S rRNA gene in a specific PCR assay with a detection limit of 12.5 fg of pure culture DNA, corresponding to DNA extracted from approximately 0.7 CFU/mL of G. stearothermophilus. Analysis showed that the bacterial species G. stearothermophilus was not detected in any canned food sample. Our approach presented here will be useful for tracking or quantifying species G. stearotethermophilus in canned food and ingredients.

Risk assessment and risk management for safe foods: Assessment needs inclusion of variability and uncertainty, management needs discrete decisions

The introduction of relevant food safety changes in legislation, like time-temperature criteria for pasteurisation and sterilisation, microbiological criteria, HACCP and FSOs, generally took several decades. All these approaches have helped to define specific targets or systems to improve the management of food safety. More and more the measures could be related to specific efficiency in public health protection. With the use of quantitative risk assessment, theoretically the effect of all interventions on the final risk can be determined, which can help to design the appropriate controls in the food safety management system. In such an assessment in practice, however results have understandably large variability and also uncertainty. There is large variability and uncertainty in the biological parts of the assessment, the dose response (infectivity, human susceptibility) the micro-organism kinetics in the chain (growth, inactivation, stress response) and also in the more technological parts, the conditions in the chain and the consumer behaviour. Often the results of risk assessments are probability distributions of the variability in illness probability, also sometimes represented with their uncertainty. To make a link from these distributions to managerial decisions, that need to be black and white, should not be considered the job of risk managers. This link needs investment from both the assessor and the manager.

Selection of process conditions by risk assessment for apple juice pasteurization by UV-heat treatments at moderate temperatures

The effect of bactericidal UV-C treatments (254 nm) on Escherichia coli O157:H7 suspended in apple juice increased synergistically with temperature up to a threshold value. The optimum UV-C treatment temperature was 55 °C, yielding a 58.9% synergistic lethal effect. Under these treatment conditions, the UV-heat (UV-H55 °C) lethal variability achieving 5-log reductions had a logistic distribution (α = 37.92, β = 1.10). Using this distribution, UV-H55 °C doses to achieve the required juice safety goal with 95, 99, and 99.9% confidence were 41.17, 42.97, and 46.00 J/ml, respectively, i.e., doses higher than the 37.58 J/ml estimated by a deterministic procedure. The public health impact of these results is that the larger UV-H55 °C dose required for achieving 5-log reductions with 95, 99, and 99.9% confidence would reduce the probability of hemolytic uremic syndrome in children by 76.3, 88.6, and 96.9%, respectively. This study illustrates the importance of including the effect of data variability when selecting operational parameters for novel and conventional preservation processes to achieve high food safety standards with the desired confidence level.

Potential application of quantitative microbiological risk assessment techniques to an aseptic-UHT process in the food industry

Aseptic ultra-high-temperature (UHT)-type processed food products (e.g., milk or soup) are ready to eat products which are consumed extensively globally due to a combination of their comparative high quality and long shelf life, with no cold chain or other preservation requirements. Due to the inherent microbial vulnerability of aseptic-UHT product formulations, the safety and stability-related performance objectives (POs) required at the end of the manufacturing process are the most demanding found in the food industry. The key determinants to achieving sterility, and which also differentiates aseptic-UHT from in-pack sterilised products, are the challenges associated with the processes of aseptic filling and sealing. This is a complex process that has traditionally been run using deterministic or empirical process settings. Quantifying the risk of microbial contamination and recontamination along the aseptic-UHT process, using the scientifically based process quantitative microbial risk assessment (QMRA), offers the possibility to improve on the currently tolerable sterility failure rate (i.e., 1 defect per 10,000 units). In addition, benefits of applying QMRA are (i) to implement process settings in a transparent and scientific manner; (ii) to develop a uniform common structure whatever the production line, leading to a harmonisation of these process settings, and; (iii) to bring elements of a cost-benefit analysis of the management measures. The objective of this article is to explore how QMRA techniques and risk management metrics may be applied to aseptic-UHT-type processed food products. In particular, the aseptic-UHT process should benefit from a number of novel mathematical and statistical concepts that have been developed in the field of QMRA. Probabilistic techniques such as Monte Carlo simulation, Bayesian inference and sensitivity analysis, should help in assessing the compliance with safety and stability-related POs set at the end of the manufacturing process. The understanding of aseptic-UHT process contamination will be extended beyond the current "as-low-as-reasonably-achievable" targets to a risk-based framework, through which current sterility performance and future process designs can be optimised.

Food safety objective approach for controlling Clostridium botulinum growth and toxin production in commercially sterile foods

As existing technologies are refined and novel microbial inactivation technologies are developed, there is a growing need for a metric that can be used to judge equivalent levels of hazard control stringency to ensure food safety of commercially sterile foods. A food safety objective (FSO) is an output-oriented metric that designates the maximum level of a hazard (e.g., the pathogenic microorganism or toxin) tolerated in a food at the end of the food supply chain at the moment of consumption without specifying by which measures the hazard level is controlled. Using a risk-based approach, when the total outcome of controlling initial levels (H(0)), reducing levels (ΣR), and preventing an increase in levels (ΣI) is less than or equal to the target FSO, the product is considered safe. A cross-disciplinary international consortium of specialists from industry, academia, and government was organized with the objective of developing a document to illustrate the FSO approach for controlling Clostridium botulinum toxin in commercially sterile foods. This article outlines the general principles of an FSO risk management framework for controlling C. botulinum growth and toxin production in commercially sterile foods. Topics include historical approaches to establishing commercial sterility; a perspective on the establishment of an appropriate target FSO; a discussion of control of initial levels, reduction of levels, and prevention of an increase in levels of the hazard; and deterministic and stochastic examples that illustrate the impact that various control measure combinations have on the safety of well-established commercially sterile products and the ways in which variability all levels of control can heavily influence estimates in the FSO risk management framework. This risk-based framework should encourage development of innovative technologies that result in microbial safety levels equivalent to those achieved with traditional processing methods.