预测微生物模型在水产品中的应用

水产品在捕获后的微生物存活状况十分复杂,如果消费者在水产品中微生物状况未知的情况下食用了水产品,就可能会发生食物中毒。预测食品微生物学是食品微生物学的关键领域,也是食品安全控制的重要学科组成,能够帮助食品专家和从业人员有效评估和控制食品的安全状况。水产品中病原微生物生长模型的建立在水产品的食用安全性方面能够起到重要作用,微生物预测模型能够分析和预测水产品中微生物随时间的变化,以及不同温度、不同环境条件下微生物的存活情况,为水产品的生产加工方式、储存条件及安全状况提供参考。     

预测食品微生物学概述及应用

为了解预测食品微生物学的基本内容,综述了预测微生物学在食品中的应用.预测食品微生物学通过数学模型来预测微生物在不同环境条件下生长或死亡的数据.预测模型的分类有多种方法,根据微生物生长或失活的情况将预测模型分为生长模型和失活/存活模型.预测微生物模型已经广泛应用于食品安全质量管理和生产工艺中.     

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。     

预测食品微生物学在肉品安全领域的应用

预测食品微生物学是一门对食品微生物进行数量化预测的新兴学科,可以在不进行传统微生物检测的条件下快速对食品的安全性和货架期进行预测。本文简述了预测食品微生物学的概念,模型分类及建模步骤,重点介绍了预测食品微生物学在肉品安全中的定量微生物风险评估、危害分析和关键控制点以及产品货架期等领域的应用,并对其未来发展进行了展望。     

基于食品安全性的预测微生物学研究模式

预测微生物学是依据各种食品微生物在不同加工、贮藏和流通条件下的基础信息库,预测食品中微生物数量的动态变化,并对食品的安全性做出快速判断的一门学科研究新领域。预测微生物学的核心在于建立完善的数学模型。介绍了预测微生物学的研究模式以及其与不同学科的结合方式,并聚焦到将成为预测微生物学未来发展源动力的神经元网络技术。     

预测微生物学的概述及应用

世界各国因微生物引起的人畜严重病害的事例不计其数,人类的传染性疾病主要是食品和饮用水中的病原微生物引起的,由于食品和水听 致病微生物基本相似,所以食用污染的食品和水的后果是相似的,预测食品微生物学就是通过对食品中各种微生物的基本特征,如营养需求、酸碱度、温度条件、需厌氧程度以及对各种阻碍因子敏感程度的研究,应用数学和统计学的方法,将这些特性输入计算机,并编制各种细菌在不同条件下生长繁殖情况的程序,逻辑预测微生物学使我们在产品设计阶段就可以了解该食品可能存在的微生物问题,从而预先采取相应措施控制微生物以达到卫生和和微生物方面的安全要求,关于不同微生物模型,其分类方法很多,在此我们仅略述定量微生物风险评估的方法及应用。     

乳制品中快速微生物检测技术分析

乳制品具有丰富的营养,成为人们生活的必备品,同时乳制品也属于天然的微生物培养基中的一种,极易被微生物污染,当乳制品中微生物含量超出标准规定的范围时,则会对产品的质量和保持期带来较大的影响,还会影响到消费者的健康。基于当前日益严竣的食品安全形势,乳品企业需要配备快速的微生物检测技术,以此来确保乳制品的质量,为人们提供安全、健康的乳品。     

预测微生物学在传统白酒酿造中的应用构想

预测微生物学是运用微生物学、工程数学以及统计学进行数学建模,并建立各种食品微生物在产品加工、贮藏和流通条件下的基础信息库,以及预测食品中微生物数量的动态变化规律,达到运用模型预测和描述特定食品中微生物的生长和死亡状况的目的。白酒酿造过程建立白酒微生物学资源数据库和预测微生物学数学模型,可探究制曲和发酵过程中各类微生物的变化规律及各种环境因素对酿酒微生物类群衍变的影响规律,提高白酒酿造工艺设计的最适化。（孙悟）     

预测微生物学及其在食品科学中的应用

预测微生物学是运用微生物学、工程数学以及统计学进行数学建模,利用所建模型,通过计算机及其配套软件,预测和描述处在特定的环境下微生物的生长和死亡规律。预测微生物学模型按Whiting和Buchanan的分类方法分为初级模型、次级模型和三级模型,文中按该分类方法分别对预测微生物学及其模型的发展进行了系统的介绍,并对预测微生物学在食品科学中的应用进行了综述,为在食品工业中更好的利用预测微生物学提供帮助。     

储粮预测微生物模型的研究进展

粮食的安全储藏,关系到食品安全和人类健康。依据预测微生物学,构建储粮中微生物生长预测模型,可以快速对储粮中微生物的生长情况进行判断,对储粮中病原微生物和腐败微生物的控制有重要的意义。对实现"生态储粮",确保储粮安全也具有重要的理论和实际应用价值。以文献综述形式,简要概述了储粮微生物,根据不同的数学模型,综述了初级、二级和三级模型中常见的模型,并在此基础上,简述了储粮中主要有害霉菌模拟研究的最新研究进展。     

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。     

低温肉制品微生物控制与预测模型应用研究进展

低温肉制品营养丰富,是我国肉制品未来的发展方向。本文介绍了低温肉制品中的主要微生物来源、种类以及控制措施;综述了低温肉制品中微生物预测的各级模型,分析了其优缺点;简述了预测模型在实际生产中的应用。     

Predicting mycotoxins in foods: A review

The need to ensure the microbiological quality and safety of food products has stimulated interest in the use of mathematical models for quantifying and predicting microbial behaviour. For 20 years, predictive microbiology has been developed for predicting the occurrence of food-borne pathogens, although these tools are dedicated to bacteria. Recently, the situation has changed and a growing number of studies are available in the literature dealing with the predictive modelling approach of fungi. To our knowledge the present one is the first review focussed on predictive mycology and food safety, including mycotoxins; existing kinetic and probability models applied to mycotoxigenic fungi germination and growth, and mycotoxin production are reviewed.     

Opportunities and challenges in pulsed electric field processing of dairy products

Consumer demand and current market conditions warrant investigation of dairy processing technologies that can deliver improved product quality and stability and reduced energy use during processing, without compromising product and process safety. One candidate technology for the extension of shelf-life in dairy products is pulsed electric field (PEF) processing. PEF is considered to be an effective, non-thermal intervention that appears to hold some promise. Research on the application of PEF to control spoilage and pathogenic microorganisms and enzyme systems in dairy products spans a wide array of processing equipment and reaction conditions. PEF has been reported to effectively reduce the numbers of both pathogens and spoilage organisms in milk; however, there is a high degree of variability between studies. The application of PEF in combination with lower temperature thermal processing can deliver comparable reductions in microbial load without significant detrimental effects to the sensory and physico-chemical properties of food products.     

Recent Advances in Food Processing Using High Hydrostatic Pressure Technology

High hydrostatic pressure is an emerging non-thermal technology that can achieve the same standards of food safety as those of heat pasteurization and meet consumer requirements for fresher tasting, minimally processed foods. Applying high-pressure processing can inactivate pathogenic and spoilage microorganisms and enzymes, as well as modify structures with little or no effects on the nutritional and sensory quality of foods. The U.S. Food and Drug Administration (FDA) and the U.S. Department of Agriculture (USDA) have approved the use of high-pressure processing (HPP), which is a reliable technological alternative to conventional heat pasteurization in food-processing procedures. This paper presents the current applications of HPP in processing fruits, vegetables, meats, seafood, dairy, and egg products; such applications include the combination of pressure and biopreservation to generate specific characteristics in certain products. In addition, this paper describes recent findings on the microbiological, chemical, and molecular aspects of HPP technology used in commercial and research applications.     

Status of Microbial Modeling in Food Process Models

ABSTRACT: Food process models are typically aimed at improving process design or operation by optimizing some physical or chemical outcome, such as maximizing processing yield, minimizing energy usage, or maximizing nutrient retention. However, in seeking to achieve these objectives, one of the critical constraints is usually microbiological. For example, growth of pathogens or spoilage organisms must be held below a certain level, or pathogen reduction for a kill step must achieve a certain target. Therefore, mathematical models for microbial populations subjected to food processing operations are essential elements of the broader field of food process modeling. However, the complexity of the underlying biological phenomena presents special challenges in formulating, validating, and applying microbial models to real‐world applications. In that context, the narrow purpose of this article is to (1) outline the general terminology and constructs of microbial models, (2) evaluate the state of knowledge/state of the art in application of these models, and (3) offer observations about current limitations and future opportunities in the area of predictive microbiology for food process modeling.     

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.     

基于微生物和量纲模型对茶叶货架期的研究

茶叶在贮藏和销售过程中易受到理化及微生物的影响,造成茶叶保质期短,严重阻碍茶业发展。为更好地探索茶叶微生物生长模型对茶叶货架期的影响,该文对微生物生长学一级、二级模型的含义与内容进行概述,并剖析茶叶品质的影响因素,主要从微生物和物理角度来对茶叶货架期的评价,归纳和建立茶叶货架期的预测模型。以提高茶叶卫生检测效率,保证茶叶质量安全,延长茶叶保质期。