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ScanLag: High-throughput Quantification of Colony Growth and Lag Time
Published on: July 15, 2014
Parameter estimation for the distribution of single cell lag times
József Baranyi1, Susan M George, Zoltán Kutalik
1Institute of Food Research, Norwich Research Park, Norwich, UK. jozsef.baranyi@bbsrc.ac.uk
Journal of Theoretical Biology
|March 31, 2009
Summary
Understanding bacterial lag time distributions is crucial for predicting pathogen growth and contamination risks. This study introduces a method to estimate single-cell lag times, vital for quantitative microbial risk assessment.
Area of Science:
- Microbiology
- Quantitative Microbial Risk Assessment (QMRA)
Background:
- Accurate prediction of bacterial growth is essential for QMRA.
- Understanding the distribution of single-cell lag times is critical for modeling population dynamics.
Purpose of the Study:
- To model and estimate the distribution of single-cell lag times in bacterial populations.
- To provide a method for predicting pathogen proliferation to harmful levels.
Main Methods:
- Modeling single-cell lag time as a delay in the growth function of the resulting subpopulation.
- Implementing a procedure based on the method of moments for parameter estimation.
Main Results:
- The proposed method allows for the estimation of single-cell lag time distribution parameters.
- The method is particularly advantageous for small, random initial cell numbers and detection during the exponential growth phase.
Conclusions:
- The developed method offers an accessible approach to characterizing bacterial lag time distributions.
- This contributes to more accurate risk assessments in microbial contamination scenarios.
