预测食品微生物学

预测食品微生物学是食品微生物学的一个新兴分支学科,是在微生物学、数学、统计学和计算机应用学的基础上建立起来的新学科。预测食品微生物学研究和设计一系列描述和预测微生物在特定条件生长和衰亡的模型,因而一种防止病原微生物对食品污染的有效有预警工具。     

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.     

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。     

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。     

预测微生物学及其在粮食储藏中的应用

储粮中微生物的活动会引发粮食品质劣变，利用预测微生物学的研究方法，通过总结不同温度、湿度条件下微生物活动的变化规律，建立回归线性方程作为预测模型，可随时了解粮食中微生物的活动状况，确保储粮的品质和储藏安全。     

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。     

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。     

预测微生物学及其在熟肉制品贮藏中的应用

熟肉制品中微生物的活动会引发产品品质劣变,利用预测微生物学的研究方法,通过总结不同加工、包装、贮藏条件下微生物活动的变化规律,建立回归线性方程作为预测模型,可随时了解熟肉制品中微生物的活动状况,确保熟肉制品的品质和储藏安全。     

预测微生物学的研究进展及其在食品中的应用

预测微生物学是食品微生物学中的一个亚学科。本文阐述了预测模型的分类及修改后主要模型的方程式;预测微生物学的研究内容,包括预测模型的改进,环境因子(温度、pH、水分活度等)对微生物(以致病菌和腐败菌为主)生长的影响以及在食品货架期预测、食品安全质量管理等方面的应用等。提出目前研究中存在的问题,并展望该领域今后的研究方向。     

预测微生物学——风险评估

本文略述了预测微生物学——风险评估的步骤及其应用     

预测微生物学与食品质量安全

预测食品微生物学利用数学模型定量地分析不同环境条件下食品中病原菌和腐败菌的生长和存活，对食品的货架期作出合理的预测。该文简要介绍了预测模型的3个水平及其在预测货架期中的应用，并展望了预测微生物学未来的发展趋势。     

Predictive microbiology and food safety

The evaluation of risk in food safety requires knowledge of the probability that microbial population sizes will not exceed defined levels. This probability is evaluated assuming that the growth of the microbial population can be described by the Gompertz equation with the variance of growth depending on the population size. It is shown that the probability density associated with this phenomenon is skewed, so that the risk of a high microbial population is greater than that which would be estimated using a symmetrical probability distribution such as the Gaussian. Maximum likelihood estimates of the parameters of the Gompertz equation based on the derived probability density are calculated using data published by Zwietering et al. [23] for the growth of Lactobacillus plantarum under different temperatures. The probability that a microbial population of a given size will exceed an unacceptable level within a given time is calculated for growth at two temperatures, 10 and 25 degrees C. The implication of these theoretical results for the management of risk in food safety and in the design of hazard analysis critical control point procedures is discussed.     

Bibliography of food microbiology

The European and International Standard method for the detection of Listeria monocytogenes, described in EN ISO 11290 Part 1: 1997 (International Organisation for Standardisation, Geneva) was validated by order of the European Commission (Standards, Measurement and Testing Fourth Framework Programme Project SMT4-CT96-2098). Nineteen laboratories in 14 countries in Europe participated in a collaborative trial to determine the performance characteristics of the method, which are intended for publication in the corresponding standard. An additional objective of this project was to devise a new series of parameters to indicate the 'precision' of microbiological qualitative methods. The method was challenged with three food types, namely fresh cheese, minced beef and dried egg powder and a reference material. Inoculation levels ranged from 5 to 100 cfu/25 g. Each participant examined five replicates of each food type at three inoculum levels and five reference materials. Both PALCAM and Oxford media were assessed. All test materials were subjected to stringent homogeneity and stability testing before being used in the collaborative trial. The results demonstrated that the method prescribed in EN ISO 11290-1 had an overall sensitivity of 85.6% and a specificity of 97.4%. L. monocytogenes was detected in most cases after primary enrichment, although secondary enrichment often yielded further positives. However, a significant number of false-negative results were obtained with all food types when large numbers of L. innocua were present in the test materials. L. innocua tended to dominate L. monocytogenes during the selective enrichment stages and thus masked small numbers of colonies of L. monocytogenes on the isolation media. There was no evidence from this collaborative study to demonstrate a significant difference in performance between Oxford and PALCAM media. Due to the problem of false-negative results with this method as highlighted in this trial, recommendations have been made to ISO to launch a revision of the standard to improve the detection of low numbers of L. monocytogenes in foods. New statistical methods devised to advance the measurement of the performance of qualitative microbiological methods are also described.