Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 264

The DOI matches its Crossref record.

Predictive microbiology: towards the interface and beyond

Open access
McMeekin, T.A., Olley, J., Ratkowsky, D.A., Ross, T.·2002·International Journal of Food Microbiology

Abstract

This review considers the concept and history of predictive microbiology and explores aspects of the modelling process including kinetic and probability modelling approaches. The "journey" traces the route from reproducible responses observed under close to optimal conditions for growth, through recognition and description of the increased variability in responses as conditions become progressively less favourable for growth, to defining combinations of factors at which growth ceases (the growth/no growth interface). Death kinetics patterns are presented which form a basis on which to begin the development of nonthermal death models. This will require incorporation of phenotypic, adaptive responses and may be influenced by factors such as the sequence in which environmental constraints are applied. A recurrent theme is that probability (stochastic) approaches are required to complement or replace kinetic models as the growth/no growth interface is approached and microorganisms adopt a survival rather than growth mode. Attention is also drawn to the interfaces of predictive microbiology with microbial physiology, information technology and food safety initiatives such as HACCP and risk assessment.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/s0168-1605(01)00663-8

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 264

Metadata

Authors
McMeekin, T. A., Olley, J., Ratkowsky, D. A., & Ross, T.
Venue
International Journal of Food Microbiology
Publisher
Elsevier BV
Published
2002-03
Volume
73
Issue
2-3
Pages
395-407
ISSN
0168-1605 (ISSN-L)
OpenAlex
W1997208103
Cited by
264
References
0
FWCI
11.19
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Predictive microbiology: towards the interface and beyond. https://app.cochat.ai/papers/10.1016/s0168-1605(01)00663-8
The paper
McMeekin, T. A., Olley, J., Ratkowsky, D. A., & Ross, T. (2002). Predictive microbiology: towards the interface and beyond. International Journal of Food Microbiology. https://doi.org/10.1016/s0168-1605(01)00663-8

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.