Using Quantitative Predictive Microbial Modelling with Haccp

D.L. Seman

Using Quantitative Predictive Microbial Modelling with Haccp

In: 63rd International Congress of Meat Science and Technology

Author:

D.L. Seman

D.L. Seman Department of Animal Science, University of Wisconsin, Madison, WI, USA; dseman@wisc.edu

Search for other papers by D.L. Seman in
Current site
Google Scholar
PubMed

Type:: Chapter

Pages:: 482–483

DOI:: https://doi.org/10.3920/9789086868605_212

Purchase instant access (PDF download and unlimited online access):

€42.00€35.00 excl. VAT

Add to Cart

Redeem Access Token

Microbial modeling has been an evolving science for the past 30 to 40 years beginning first as a method of predicting microbial growth curves under varying cardinal conditions (primary models) to the creation of specific models including other factors and interventions to inhibit microbial growth (secondary models). These have proven to be quite valuable to the food industry in general and the meat industry in particular. Regulatory agencies and various research institutes have use microbial modeling in quantitative microbial risk assessments to rank risks and to test various methods to reduce the risks associated with foodborne illnesses. Today, however, with more computing power available, it is possible to introduce ‘next generation’ models that include features of microbial and risk modeling to form new, more powerful stochastic models into the day-to-day operations of food manufacturing facilities. Such models can provide a ‘truer’ representation of the actual processes employed.

Citation Info

Save
Cite
Email this content

Share link with colleague or librarian

You can email a link to this page to a colleague or librarian:
Email this content
or copy the link directly:

https://brill.edhh.ma/abstract/book/9789086868605/BP000212.xml
The link was not copied. Your current browser may not support copying via this button.

Link copied successfully

Collapse
Expand

63rd International Congress of Meat Science and Technology

Nurturing locally, growing globally

E-Book ISBN:: 9789086868605

Publisher:: Wageningen Academic

Print Publication Date:: 15 Nov 2017

Subjects
- Life Sciences

Metrics

	All Time	Past 365 days	Past 30 Days
Abstract Views	75	40	2
Full Text Views	5	0	0
PDF Views & Downloads	3	0	0

African Studies	Education	Media Studies
American Studies	History	Middle East and Islamic Studies
Ancient Near East and Egypt	Human Rights and Humanitarian Law	Musicology
Art History	International Law	Philosophy
Asian Studies	International Relations	Religious Studies
Biblical Studies	Jewish Studies	Slavic and Eurasian Studies
Biology	Languages and Linguistics	Social Sciences
Book History and Cartography	Life Sciences	Theology and World Christianity
Classical Studies	Literature and Cultural Studies

Subjects

Authors

Open Access

Product Information

Company

Contact

Using Quantitative Predictive Microbial Modelling with Haccp

Citation Info

Share link with colleague or librarian

63rd International Congress of Meat Science and Technology

Nurturing locally, growing globally

Table of Contents

Metrics

Metrics