Microrisk Lab: An Online Freeware for Predictive Microbiology

Area of Science:

• Predictive microbiology
• Computational biology
• Food safety modeling

Background:

• Predictive microbiology models are crucial for food safety.
• Existing software often lacks integration or user-friendliness.
• Need for accessible tools for parameter estimation and simulation.

Purpose of the Study:

• Introduce Microrisk Lab, an R-based freeware for predictive microbiology.
• Evaluate Microrisk Lab's performance against established modeling systems.
• Highlight its user-friendly interface and integrated features.

Main Methods:

• Integrated 36 peer-reviewed models for parameter estimation and simulation.
• Performed six case studies comparing Microrisk Lab with DMFit, GInaFiT, IPMP 2013/GraphPad Prism, Bioinactivation FE, and @Risk.
• Assessed numerical, graphical, and statistical outputs.

Main Results:

• Microrisk Lab demonstrated statistically equivalent performance to other modeling systems.
• The freeware provides comprehensive statistical indicators.
• Case studies confirmed the accuracy of estimations and simulations.

Conclusions:

• Microrisk Lab is a valuable, user-friendly tool for predictive microbiology.
• Its high integration and interconnectivity enhance microbial behavior modeling.
• Freely accessible online for researchers and practitioners.