Microbial Growth Prediction Calculator

Work out microbial growth prediction instantly with clear inputs, formula shown and shareable results.

About Microbial Growth Prediction Calculator

During exponential growth a population doubles every generation time, so N = N0 x 2^(t/g) after the lag phase ends. Generation times shorten sharply with temperature: Salmonella doubles roughly every 20-30 minutes at 37 C but takes many hours near 10 C, which is why chilled holding works.

Formulas

Exponential growth

N = N0 x 2^((t - lag) / generation time)

Log increase

Log increase = log10(N / N0)

Worked example

With the default values below, Microbial Growth Prediction Calculator returns Predicted Count of 409,600.00. Change any input above and every figure here is recalculated in your browser.

Inputs used

Initial Countminimum 0 CFU/g: 100 CFU/g
Generation Timeminimum 0 minutes: 30 minutes
Elapsed Timeminimum 0 hours: 8 hours
Lag Phase Durationminimum 0 hours: 2 hours

Results

Predicted Count: 409,600.00
Generations Elapsed: 12.0000
Log Increase: 3.6124
Hours To Reach 1 Million CFU/g: 8.644

Step by step

1Values used
2Exponential growth
3Log increase
4Predicted Count= 409,600.00
5Generations Elapsed= 12.0000
6Log Increase= 3.6124
7Hours To Reach 1 Million CFU/g= 8.644

Assumptions and limits

The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
Figures are rounded for display to 4 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.
Growth predictions are indicative only. Food safety decisions require validated predictive models or challenge testing for the specific product and organism.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Growth predictions are indicative only. Food safety decisions require validated predictive models or challenge testing for the specific product and organism.

Frequently Asked Questions

Why does the lag phase matter?

It is the adaptation period before growth begins, and keeping food within the lag phase is often the practical control. Lag shortens when the inoculum is already adapted to the conditions.

When does this model stop applying?

Once nutrients deplete or metabolites accumulate the population enters stationary phase. Predictions above about 10^8 CFU/g are unrealistic, and full sigmoid models such as Baranyi should be used.