We have located links that may give you full text access.
Predictive modeling of microbial single cells: A review.
Critical Reviews in Food Science and Nutrition 2018 March 25
In practice, food products tend to be contaminated with food-borne pathogens at a low inoculum level. However, the huge potential risk cannot be ignored because microbes may initiate high-speed growth suitable conditions during the food chain, such as transportation or storage. Thus, it is important to perform predictive modeling of microbial single cells. Several key aspects of microbial single-cell modeling are covered in this review. First, based on previous studies, the techniques of microbial single-cell data acquisition and growth data collection are presented in detail. In addition, the sources of microbial single-cell variability are also summarized. Due to model microbial growth, traditional deterministic mathematical models have been developed. However, most models fail to make accurate predictions at low cell numbers or at the single-cell level due to high cell-to-cell heterogeneity. Stochastic models have been a subject of great interest; and these models take into consideration the variability in microbial single-cell behavior.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app