Estimation of microbial growth using population measurements subject to a detection limit

In this paper we develop a maximum likelihood estimation procedure for determining the mean and variance in microbial population size from microbial population measurements subject to a detection limit. Existing estimation methods generally set non-detectable measurements equal to the detection limit and are highly biased. Because changes in the mean and variance in the microbial population size are typical in industrial processes we also outline statistical tests for detecting such changes when measurements are subject to a detection limit, which is critical for process control. In an industrial process there may also potentially be variability in the microbial growth rate due to variation in the microbial strain, environment, and food characteristics. Accordingly, we also present a maximum likelihood procedure for estimating microbial growth model parameters and their variance components from microbial population measurements subject to a detection limit. Such information can be used to generate the mean and variance through time of the microbial population size, which is vital for the application of predictive microbiological models to risk assessment and food product shelf-life estimation.     

Rapid and quantitative detection of the microbial spoilage of muscle foods: current status and future trends

The requirement for real-time monitoring in the modern and highly automated food processing environment has stimulated research into rapid microbiological testing. This review will concentrate on the search for a rapid detection system for the microbial spoilage of meats that has been ongoing since at least the 1970s. The metabolic processes and bacteria involved within the microbial spoilage of muscle foods will be outlined prior to a detailed overview of the current methods employed in the industry to quantify levels of spoilage organisms. Despite these detailed microbiological studies there is still a requirement within the food industry for new techniques which would ideally be accurate, non-destructive and give answers in real-time and a range of novel analytical technologies which are currently being developed for the rapid assessment of microbial spoilage in muscle foods will be examined.     

A retail and consumer phase model for exposure assessment of Bacillus cereus

An exposure assessment is conducted for psychrotrophic and mesophilic Bacillus cereus in a cooked chilled vegetable product. A model is constructed that covers the retail and consumer phase of the food pathway, using the output of a similar model on the industrial process as input. Microbial growth is the predominant process in the model. Variability in time and temperature during transport and storage is included in the model and different domestic refrigerator temperature distributions are compared. As an end point, probable levels of B. cereus colony forming units (cfu) in packages of vegetable purée are predicted at the moment the consumer takes the product from its refrigerator, that is prior to a cooking process. The psychrotrophic strain is predicted to end up above a threshold level of 10(5) cfu/g in 0.9% to 6.3% of the vegetable purée packages, depending on domestic refrigerator temperature. Accounting for spoilage this reduces to 0.3% to 2.4%. Even if the purée is stored at 4 degrees C in the domestic refrigerator and use-by-date (UBD) is respected, the threshold level may be passed. For the mesophilic strain the threshold level is rarely passed, but in contrast to the total viable count, the spore load at the end point is predicted to be higher than in the psychrotrophic strain. Our study illustrates how an exposure assessment model, which may be used in quantitative risk assessment, can integrate expertise in modelling, food processing and microbiology over the food pathway, and thus evaluate food safety, identify gaps in knowledge and compare risk management measures. As important gaps in knowledge, the lack of sporulation and germination models and data, validated non-isothermal growth models and a spoilage model useful for risk assessment are identified. Knowledge of the dose-response relationship is limited and does not allow a full risk assessment. It is shown that exposure can be lowered by lowering domestic refrigerator temperatures, and less so much by monitoring and withdrawing contaminated products at the end of industrial processing.     

基于活性包装视角下的水产品保鲜机制研究进展

研究发现,内源酶、微生物、脂质氧化及环境等是引起水产品腐败的重要因素,如何提升保鲜效果以减少水产品的腐败损失和保障消费者的食用安全成为水产行业能否可持续发展的关键,引起行业内的广泛关注。近年来随着人们对食品安全和食品包装关注的不断提高,活性包装逐渐发展起来,并在改善保鲜效果方面作用显著,成为研究的热点。鉴于此,本文在探究水产品腐败机制的基础上,从内源酶活性、微生物生长、脂质氧化和环境4 个方面,综合分析了基于活性包装的水产品保鲜机制,并探讨了活性包装可能的增效机制。旨在为未来研发靶向的水产品保鲜活性包装提供支撑。     

Predictive modelling of the growth and survival of Listeria in fishery products

Predictive microbiology provides a powerful tool to aid the exposure assessment phase of 'quantitative microbial risk assessment'. Using predictive models changes in microbial populations on foods between the point of production/harvest and the point of eating can be estimated from changes in product parameters (temperature, storage atmosphere, pH, salt/water activity, etc.). Thus, it is possible to infer exposure to Listeria monocytogenes at the time of consumption from the initial microbiological condition of the food and its history from production to consumption. Predictive microbiology models have immediate practical application to improve microbial food safety and quality, and are leading to development of a quantitative understanding of the microbial ecology of foods. While models are very useful decision-support tools it must be remembered that models are, at best, only a simplified representation of reality. As such, application of model predictions should be tempered by previous experience, and used with cognisance of other microbial ecology principles that may not be included in the model. Nonetheless, it is concluded that predictive models, successfully validated in agreement with defined performance criteria, will be an essential element of exposure assessment within formal quantitative risk assessment. Sources of data and models relevant to assessment of the human health risk of L. monocytogenes in seafoods are identified. Limitations of the current generation of predictive microbiology models are also discussed. These limitations, and their consequences, must be recognised and overtly considered so that the risk assessment process remains transparent. Furthermore, there is a need to characterise and incorporate into models the extent of variability in microbial responses. The integration of models for microbial growth, growth limits or inactivation into models that can predict both increases and decreases in microbial populations over time will also improve the utility of predictive models for exposure assessment. All of these issues are the subject of ongoing research.     

Use of Bayesian modelling in risk assessment: application to growth of Listeria monocytogenes and food flora in cold-smoked salmon

An attempt to use a Bayesian approach to model variability and uncertainty separately in microbial growth in a risk assessment is presented. It was conducted within the framework of a French project aiming at assessing the exposure to Listeria monocytogenes in cold-smoked salmon. The chosen model describes the effect of time and temperature on bacterial growth. A Bayesian approach close to the one proposed by Pouillot et al. [Int. J. Food Microbiol. 81 (2003) 87] is used to estimate the variability and uncertainty of growth parameters from both literature data and data experimentally acquired during the project. Variability between strains and between products is taken into account. The growth of the food flora of cold-smoked salmon is also modelled by the same method. The results obtained for both models are used to predict the simultaneous growth of L. monocytogenes and food flora in cold-smoked salmon with a competitive model, expressing variability and uncertainty through a second-order Monte Carlo simulation.     

食品预测微生物软件的分析与比较

近年来,微生物预测和风险评估软件取得了一定的发展。微生物预测是利用所建模型来预测和描述处在特定食品环境下微生物的生长和死亡。文章概述了16款微生物预测软件,并且依据不同的标准对其做了比较分析,如建模方法,功能模块,研究过程中的环境变量(温度、酸碱度、水活性),不同的基质类型和不同的微生物种类等。对食品微生物研究领域有一定的研究和参考价值,并且可以满足不同用户对不同微生物研究的需要。     

Food-borne Listeria monocytogenes risk assessment

Listeria monocytogenes is ubiquitous in the environment and in food processing plants. Consequently, foods are frequently contaminated. However, the occurrence rate of listeriosis is only about five cases per million people per year. Listeriosis primarily strikes immunocompromised individuals, pregnant women and the elderly with a fatality rate of 20-25%. The FDA is in the process of finishing a risk assessment that is being conducted as an initial step in reviewing its approach to maximizing the public protection from foodborne L. monocytogenes . The risk assessment evaluated the presence and quantitative levels of L. monocytogenes in 21 groups of ready-to-eat foods. The potential growth of L. monocytogenes between retail point-of-sale, where contamination data originated, and consumption was modelled. The frequency and amount of consumption of these foods completed the data for the exposure assessment. For the hazard characterization or dose response part of the risk assessment, data from animal studies, virulence assays and epidemiological investigations were used to estimate the likelihood of illness for different human groups from consuming different numbers of L. monocytogenes . This risk assessment is a virtual review of current scientific knowledge. Quantitative modelling provides greater insight than a qualitative review and also indicates the uncertainty about our knowledge. The risk assessment does not attempt to define an acceptable or tolerable level of L. monocytogenes consumption or propose changes in regulations. These decisions are the responsibility of risk managers who consider additional factors such as food preferences, technical feasibility and societal values when evaluating regulatory policies.     

三文鱼气调保鲜技术的研究进展

三文鱼不仅是补充人体营养物质的理想食物来源,而且还具有良好的保健作用。本文主要介绍了三文鱼气调保鲜技术的研究进展,指出了三文鱼气调保鲜技术的发展趋势,即单一采用气调保鲜技术只能有限地延长三文鱼的货架期,而气调保鲜技术与酸浸、盐渍、烟熏、保鲜剂和抑菌剂等结合使用可以更好地延长三文鱼的货架期,这将是气调保鲜技术发展的一个趋势。气调包装抑制了好氧菌的生长,气调贮藏中的特定腐败菌为发光磷杆菌、乳酸菌等。通过腐败菌生长建立的货架期预测模型可用于预报三文鱼的货架期,从而建立起一种准确及时的食品质量安全评估方法。      

Microbiological predictive modeling and risk analysis based on the one-step kinetic integrated Wiener process

The actual growth-monitoring data of microbial hazards in food are characterized by uncertainty, accumulation, discreteness, and nonlinearity, and thus it is difficult to accurately predict and analyze food safety microbiological risks in real time. Hence, we propose an approach of microbiological predictive modeling and risk analysis based on the one-step kinetic integrated Wiener process (OS-WP). First, the microbial tertiary prediction model was directly constructed through one-step kinetic analysis. Then, the WP was integrated with a tertiary model for predictive modeling of the actual microbial stochastic growth. Second, an indicator, “remaining safety life” (RSL), was introduced to analyze the potential microbiological risk on the basis of the established prediction models. Finally, the maximum likelihood estimation was used obtaining the model parameters online, and for calculating the RSL value in real time. The OS-WP approach was applied to a case study of the mixed mildew hazard during wheat storage. For different datasets, the root mean square error (RMSE) of the microbiological predictive model was less than 1.5; the relative RMSE of the RSL prediction reached 6.77%; the running time was less than 0.6 s. The result showed that the proposed approach is effective and feasible in modeling the actual growth of microbial hazards in food and can achieve online risk analysis. It can provide valuable microbiological early warning information to risk-management and decision-making departments for ensuring food safety.     

核心参数模型在食品微生物监控中的研究进展

食源性疾病的暴发促使研究人员寻找更快捷有效的方法来监控食品中的微生物.预测微生物模型通过定量内在因素和外在因素对食品中微生物行为的影响,从而进行食品风险管理和产品研发.核心参数模型是其中的一种二级模型,适用于多种环境因素共同作用下微生物生长情况的预测.近年来,随着其不断被完善,已经发展成为研究微生物的重要工具.本文首先...     

分子生物学技术在预测微生物学中的应用与展望

预测微生物学是食品微生物学的重要组成部分,其本质在于利用数学模型描述特定环境条件下微生物的生长和死亡规律。预测微生物模型既能应用于预测食品的货架期、控制腐败菌的滋生,又有助于完善食品微生物风险评估体系,减少致病菌的患病风险,对保障食品安全和改善公共卫生状况具有十分重要的意义。本文以综述的形式,概述预测微生物学的发展历史,并分析当前预测微生物学的研究热点。在此基础之上,着重介绍分子生物学技术在预测微生物学中应用的最新研究进展,阐述分子预测模型的概念和构建方法,并对其他分子生物学技术在预测微生物学中应用的可行性以及分子预测模型的应用前景进行展望,以期为全面推动预测微生物学这一学科的进步提供理论参考。     

USE OF TIME/TEMPERATURE INTEGRATORS, PREDICTIVE MICROBIOLOGY, AND RELATED TECHNOLOGIES FOR ASSESSING THE EXTENT AND IMPACT OF TEMPERATURE ABUSE ON MEAT AND POULTRY PRODUCTS

Temperature abuse is a main concern for chilled and/or MAP meat and poultry products since it will not only cause economic loss, but may also lead to a foodborne illness hazard. A major question for such products is whether organoleptic spoilage due to microbial or chemical action will occur before pathogen numbers or toxin levels become a risk when a product undergoes abuse temperatures. Time-temperature integrators (TTI) have shown potential to indicate or estimate temperature abuse. However knowledge of predictive food microbiology is needed for each food to employ a TTI tag. The simple Monod and the nonlinear Gompertz function can be used to obtain growth parameters (i.e., lag time, exponential growth rate) from kinetic studies of microbial spoilage. The temperature dependence of these parameters is best evaluated by the Arrhenius or the square root model. Effects of temperature on other deteriorative processes can also be described similarly. Three approaches are presented to evaluate the extent and impact of temperature abuse on meat and poultry by use of TTI tags, which include the effective temperature, the equivalent time and the equivalent point approach. Other technologies to evaluate or to reduce the impact of temperature abuse are also discussed .     

Food spoilage--interactions between food spoilage bacteria

Food spoilage is a complex process and excessive amounts of foods are lost due to microbial spoilage even with modern day preservation techniques. Despite the heterogeneity in raw materials and processing conditions, the microflora that develops during storage and in spoiling foods can be predicted based on knowledge of the origin of the food, the substrate base and a few central preservation parameters such as temperature, atmosphere, a(w) and pH. Based on such knowledge, more detailed sensory, chemical and microbiological analysis can be carried out on the individual products to determine the actual specific spoilage organism. Whilst the chemical and physical parameters are the main determining factors for selection of spoilage microorganisms, a level of refinement may be found in some products in which the interactive behavior of microorganisms may contribute to their growth and/or spoilage activity. This review gives three such examples. We describe the competitive advantage of Pseudomonas spp. due to the production of iron-chelating siderophores, the generation of substrates for spoilage reactions by one organism from another microorganism (so-called metabiosis) and the up-regulation of phenotypes potentially involved in spoilage through cell-to-cell communication. In particular, we report for the first time the widespread occurrence of N-acyl homoserine lactones (AHL) in stored and spoiling fresh foods and we discuss the potential implications for spoilage and food preservation.     

Quantifying recontamination through factory environments--a review

Recontamination of food products can be the origin of foodborne illnesses and should therefore be included in quantitative microbial risk assessment (MRA) studies. In order to do this, recontamination should be quantified using predictive models. This paper gives an overview of the relevant modelling approaches that are available in the literature to quantify recontamination via factory environment. Different recontamination routes are described: recontamination via air, via processing equipment or via hand contact. Unfortunately, not many available models are directly applicable to the food industry; most models are developed for aquatic or environmental systems. Finally, a general systematic approach is proposed for modelling contamination from surfaces via air, hands or liquid into the product and ranges for the parameters are given.     

Biological variability and exposure assessment

Predictive models are now commonly used for exposure assessment, with growth parameters defined for each microbial species. In this study, we tried to take into account microbial growth variability among strains of a single species. Bacillus cereus in pasteurized milk was chosen to illustrate the influence of the biological variability on the outcome of exposure assessment. Each parameter of the exposure assessment (growth parameters, shelf-life conditions) was characterized by a probability distribution describing variability and/or uncertainty. The impact of the intra-species variability on the result of the exposure assessment was then quantified and discussed. Two simple domestic shelf life conditions were tested. The results confirm that the biological variability has a great impact on the accuracy of the result and should not be systematically neglected.     

Testing nano-silver food packaging to evaluate silver migration and food spoilage bacteria on chicken meat

Migration of nanomaterials from food containers into food is a matter of concern because of the potential risk for exposed consumers. The aims of this study were to evaluate silver migration from a commercially available food packaging containing silver nanoparticles into a real food matrix (chicken meat) under plausible domestic storage conditions and to test the contribution of such packaging to limit food spoilage bacteria proliferation. Chemical analysis revealed the absence of silver in chicken meatballs under the experimental conditions in compliance with current European Union legislation, which establishes a maximum level of 0.010 mg kg^–1 for the migration of non-authorised substances through a functional barrier (Commission Regulation (EU) No. 10/2011). On the other hand, microbiological tests (total microbial count, Pseudomonas spp. and Enterobacteriaceae) showed no relevant difference in the tested bacteria levels between meatballs stored in silver-nanoparticle plastic bags or control bags. This study shows the importance of testing food packaging not only to verify potential silver migration as an indicator of potential nanoparticle migration, but also to evaluate the benefits in terms of food preservation so as to avoid unjustified usage of silver nanoparticles and possible negative impacts on the environment.     

Predictive models for bacterial growth in sea bass (Dicentrarchus labrax) stored in ice

The purpose of this paper was to estimate microbial growth through predictive modelling as a key element in determining the quantitative microbiological contamination of sea bass stored in ice and cultivated in different seasons of the year. In the present study, two different statistical models were used to analyse changes in microbial growth in whole, ungutted sea bass (Dicentrarchus labrax) stored in ice. The total counts of aerobic mesophilic and psychrotrophic bacteria, Pseudomonas sp., Aeromonas sp., Shewanella putrefaciens, Enterobacteriaceae, sulphide‐reducing Clostridium and Photobacterium phosphoreum were determined in muscle, skin and gills over an 18‐day period using traditional methods and evaluating the seasonal effect. The results showed that specific spoilage bacteria (SSB) were dominant in all tissues analysed, but were mainly found in the gills. Predictive modelling showed a seasonal effect among the fish analysed. The application of these models can contribute to the improvement of food safety control by improving knowledge of the microorganisms responsible for the spoilage and deterioration of sea bass.     

农药残留膳食暴露评估模型研究进展

农药残留膳食暴露风险评估为化学品风险管理、食品安全与人类健康领域的重点关注问题，有效的定量风险评估模型是开展农药残留膳食暴露评价的基础工具。本文结合国内外农药残留膳食暴露风险评估研究进展，旨在归纳农药残留膳食暴露风险评估模型，包括确定性评估模型、概率性评估模型和累积性评估模型；根据模型演变、适用情形与评估需求，比对分析模型间优缺点，探讨模型不确定度、评估软件、数据库应用等关键因子。同时立足我国农药残留膳食风险评估现状，展望模型相关参数整合的紧迫性与重要性，为完善农药残留膳食暴露风险评估体系建设提供科学参考。