| AI tool | Short summary/description | Core Features | Use Cases | Link | Price | |
|---|---|---|---|---|---|---|
| biogrowth (R package) | Modelling of population growth under static and dynamic environmental conditions. Includes functions for model fitting and making predictions under isothermal and dynamic conditions. | Model fitting for population growth; Predictions under isothermal and dynamic conditions; Various algorithms and models based on predictive microbiology; | Ecological Studies; Food safety analysis; Environmental studies; Resource Management | https://cran.r-project.org/package=biogrowth | Free | |
| biogrowth-web (Shiny app) | This application serves as an interface to the functions for modelling microbial growth included in the biogrowth R package | Prediction of microbial growth under static and dynamic conditions; Stochastic growth prediction under static conditions; Model fitting for primary and secondary growth models; Estimation of cardinal parameters; Editable, "publication ready" plots; Statistical information and fitting diagnostics; | Predictive microbiology research;Food safety analysis; Environmental studies; | https://foodmicrowur.shinyapps.io/biogrowth/ | Free | |
| Bioinactivation (R package) | Functions for modelling microbial inactivation under isothermal or dynamic conditions | Modeling microbial inactivation under various conditions; Making predictions, parameter estimation; Model fitting using an Adaptive Monte Carlo method for Bayesian parameter estimation. | Scientific research and industry applications; Microbial kinetics; Food safety and preservation sectors; | https://cran.r-project.org/web/packages/bioinactivation/vignettes/inactivation.html | Free | |
| Bioinactivation (Shiny app) | A web based application developed to ease the modeling of microbial inactivation. It includes functions for fitting inactivation models and making predictions under static or dynamic conditions | Fitting of inactivation models commonly used in predictive microbiology; Predictions under static or dynamic conditions; | Predictive microbiology research; Food safety analysis; | https://foodlab-upct.shinyapps.io/bioinactivation4/ | Free | |
| bioOED (R package) | bioOED is an R package that extends the bioinactivation package with functions for Sensitivity Analysis and Optimum Experiment Design for microbial inactivation. | Provides functions for Sensitivity Analysis; Offers tools for Optimum Experiment Design in microbial inactivation; Extends the capabilities of the bioinactivation package; | bioOED is ideal for researchers and professionals in microbial inactivation who want to design optimal experiments and conduct sensitivity analysis on their models. | https://cran.r-project.org/web/packages/bioOED/index.html | Free | |
| ComBase Predictor | ComBase Predictor is a web-based tool that provides predictive models for the growth and survival of foodborne pathogens | Predictive models for a wide range of foodborne pathogens; User-friendly interface with dropdown menus for selecting microorganisms and conditions; Graphical representation of predicted growth/survival curves; Option to compare predictions with actual experimental data from the ComBase database; | Assessing the risk of microbial contamination in specific food products; Designing food processing and preservation methods to ensure microbial safety; Comparing predicted microbial behavior with actual experimental data; Research and academic projects related to food microbiology and safety; | https://www.combase.cc/index.php/en/ | Free | |
| ComBase | ComBase is a web resource for quantitative and predictive food microbiology. It offers a database of microbial growth and survival curves and predictive models based on this data. | Database of microbial growth and survival curves; Predictive models for microbial growth and inactivation; | Informing the design of food safety risk management plans; Producing Food Safety Plans and HACCP plans; Reducing food waste; Assessing microbiological risk in foods; | https://www.combase.cc/index.php/en/ | Free | |
| EFSA zoonoses, antimicrobial resistance and food-borne outbreaks | The European Union system monitors and collects information on zoonoses based on Directive 2003/99/EC. EFSA, in cooperation with the European Centre for Disease Prevention and Control (ECDC), publishes annual European Union Summary Reports on the occurrence of zoonoses, zoonotic agents, antimicrobial resistance, and food-borne outbreaks. | The system provides annual European Union Summary Reports on the occurrence of zoonoses, zoonotic agents, antimicrobial resistance, and food-borne outbreaks; It also includes National zoonoses country reports and EU-wide baseline survey reports. | The system is used for monitoring and collecting data on zoonoses, zoonotic agents, antimicrobial resistance, and food-borne outbreaks in the European Union. The data collected helps in understanding the evolving situation and identifying the pathogens causing zoonotic infections. | Free | ||
| Emerging Zoonoses Information and Priority systems (EZIPs) | EZIPs is a platform designed to assist Dutch decision-makers in prioritizing emerging zoonoses concerning public health. This aids in the formulation of effective and efficient policies on control, prevention, and surveillance. | Database of 86 emerging zoonotic pathogens in the Netherlands; Prioritization based on seven criteria of threat; Provides scientific input for decision-making by Dutch ministries; | Assisting Dutch decision-makers in prioritizing emerging zoonoses; Formulating policies on control, prevention, and surveillance of zoonoses; | https://ezips.rivm.nl/ | Free | |
| Food Commodity Intake Database (FCID) | The FoodRisk FCID is a platform developed by the U.S. EPA's Office of Pesticide Programs to improve the utility of the WWEIA (What We Eat in America) food consumption survey for pesticide dietary exposure assessment. | FCID Recipes: A tool to search FCID recipes and generate reports; FCID Consumption Calculator: An application that uses NHANES/WWEIA food intake and FCID recipes; To estimate food commodity consumption for pesticide dietary exposure assessment; | The FCID is used for pesticide dietary exposure assessment and provides estimates of food consumption expressed as food commodities; It's also used to update food consumption rates in EPA’s Exposure Factors Handbook; | https://fcid.foodrisk.org/ | Free | |
| FDA-iRISK | FDA-iRISK is a web-based system developed by the Food and Drug Administration (FDA) to analyze data related to microbial and chemical hazards in food. It provides an estimate of the health burden these hazards might impose on a population level. | Web-Based System; Comprehensive Analysis; User Workspace; Data Privacy | In the field of food safety: Educational Tool; Risk assessment; Data Analysis; | https://irisk.foodrisk.org/ | Free | |
| FDA's Fresh Produce Risk Ranking Tool | Semiquantitative tool developed to prioritize pathogen-produce commodity combinations based on explicit data-driven risk criteria. It aims to identify significant risks and prioritize them for interventions to prevent contamination in fresh produce. | Provides a systematic means to prioritize pathogen-produce commodities based on explicit data-driven risk criteria. It characterizes risk in terms of epidemiological association, severity of disease, pathogen characteristics, and commodity characteristics. | The tool is used to identify and prioritize significant risks associated with fresh produce and to guide interventions that might help prevent contamination or inactivate contaminants when they are present in food. | https://www.foodrisk.org/resources/display/26 | Free | |
| Fishmap & FSLP | Fishmap and FSLP are software tools developed by AZTI in collaboration with the Institute of Food Research, Norwich, UK. They predict and visualize the growth of spoilage bacteria in fish products under various conditions, aiding in understanding the shelf life of fish products. | Prediction and visualization of growth of spoilage bacteria in fish products; Graphical comparison of experimental growth microbiological data with microbial growth models; Sensory acceptability prediction in farmed turbot products; Response prediction of time-temperature integrators (TTIs); | Prediction and understanding the growth of spoilage bacteria in fish products under various conditions, including modified atmosphere packed (MAP) and varying concentrations of CO2. These tools aid in determining the shelf life of fish products and understanding the sensory acceptability of farmed turbot products. | https://www.azti.es/servicios/fishmap-fslp-software-prediccion-de-vida-util/ | Free | |
| fitdistrplus (R package) | Fitdistrplus is an R package that extends the fitdistr() function of the MASS package. It provides several functions to assist in fitting a parametric distribution to non-censored or censored data. | Statistical Analysis: fitdistrplus can be used by statisticians and researchers to fit parametric distributions to their data, considering both non-censored and censored scenarios. Data Modeling: The package provides a comprehensive set of tools for modeling data distributions, making it suitable for various applications in data science and analytics. Educational Tool: fitdistrplus can serve as a resource for students and educators in the field of statistics and data analysis. | https://cran.r-project.org/web/packages/fitdistrplus/index.html | Free | ||
| FSSP | Food Spoilage and Safety Predictor (FSSP) is a software designed to predict the growth of spoilage and pathogenic microorganisms in food. It aims to facilitate the practical use of mathematical models for this purpose. | Models for predicting microbial growth and shelf-life; Modules to compare predictions with user data; | Predict the effect of storage conditions on product shelf-life; Predict growth of spoilage and pathogenic microorganisms in food; | http://fssp.food.dtu.dk/ | Free | |
| FoodProcess-Lab | FoodProcess-Lab is an open-source software framework designed for the application of predictive microbial models on food process chains, such as production steps in breweries and dairy factories. It aims to assist the food and feed industry in monitoring microbial development in production processes and to aid public authorities in risk assessment. | Represents process chains by combining nodes for process steps, ingredients, and contaminating agents; Assigns PMM-Lab models to steps to model microbial contaminants' tenacity; Considers various factors like temperature, pH value, and more for modeling. | The tool is beneficial for the food and feed industry to monitor microbial development in production processes. It also aids public authorities in risk assessment and can be particularly useful in crisis situations for predicting bacterial tenacity. | https://foodrisklabs.bfr.bund.de/foodprocess-lab/ | Free | |
| FOSCOLLAB | The Food Safety Collaborative Platform (FOSCOLLAB) is a platform developed by WHO that integrates data from various sources, including the JECFA database, JMPR database, GEMS/Food Contaminants database, and more. It aims to provide reliable data for better risk assessment and decision-making by food safety professionals and authorities. | Integrates data from multiple reliable sources; Provides risk assessment reports and specifications; Offers food consumption and food contamination data analysis; Allows access and download of raw data for food contamination; Provides summary statistics for food consumption; | The platform is designed for food safety professionals and authorities to access integrated data from various sources, facilitating better risk assessment and decision-making processes. | https://apps.who.int/foscollab | Free | |
| FRISBEE | The Cold Chain Database, also known as ColdBase, is part of the FRISBEE project, a European Union-funded initiative aimed at improving refrigeration technologies along the European food cold chain. The database provides insights into refrigeration needs, current technologies in the food industry, and consumer expectations related to the food cold chain. | Comprehensive database of the cold chain in Europe; Provides insights into refrigeration needs and current technologies; Investigates consumer needs and expectations related to the food cold chain; Part of the broader FRISBEE project aimed at improving refrigeration technologies; | The Cold Chain Database is designed for stakeholders in the food industry, researchers, and policymakers to gain insights into the refrigeration needs, current technologies, and consumer expectations related to the European food cold chain; | http://frisbee-wp2.chemeng.ntua.gr/coldchaindb/ | Free | |
| GInaFiT | GInaFiT is a freeware add-in for Microsoft© Excel designed to bridge the gap between predictive modeling developers and end-users in the food industry or research groups. It offers nine different types of microbial survival models. | Nine different types of microbial survival models; Automatic reporting of statistical measures; Built-in features for misuse testing; | Testing microbial survival models on user-specific experimental data; Comparing different model types; | https://frisbeetool.eu/GInaFit/What-is-GInaFiT.html | Free | |
| GroPIN | GroPIN is a standalone application developed in VBA (Visual Basic for Application) that uses Microsoft® Excel 2007 2010 as a platform for data introduction and processing. It serves as a predictive modeling database for kinetic (growth or inactivation) and probabilistic models. | 367 registered models; Simulation under both static and dynamic conditions; Monte Carlo simulation for risk estimation; | Setting performance-, process- or product criteria; Evaluating compliance with microbiological criteria regulation; | https://www.aua.gr/psomas/gropin/ | Free | |
| growthrates (R package) | provides a collection of methods to determine growth rates from experimental data, particularly from batch experiments and plate reader trials. | Offers a range of functionalities for growth rate estimation. | https://cran.r-project.org/web/packages/growthrates/index.html | Free | ||
| IPMP 2013 | a new generation predictive microbiology tool developed by the USDA Agricultural Research Service (ARS). It is designed to analyze experimental data commonly encountered in predictive microbiology and for the development of predictive models. | Data analysis tool for microbial growth and inactivation; User-friendly interfaces; No programming knowledge needed; | Analyzing kinetic data of microbial growth and inactivation; Developing primary and secondary models; | https://www.ars.usda.gov/northeast-area/wyndmoor-pa/eastern-regional-research-center/docs/ipmp-2013/ | Free | |
| mc2d (R package) | Offers a complete framework for building and studying Two-Dimensional Monte-Carlo simulations, also known as Second-Order Monte-Carlo simulations. It includes various distributions such as pert, triangular, Bernoulli, empirical discrete, and continuous. | Provides tools for Two-Dimensional Monte-Carlo simulations; Includes various distributions for simulation; Designed for advanced Monte-Carlo simulations in a two-dimensional space; | Used by researchers and data scientists for conducting TwoDimensional Monte-Carlo simulations. It can be applied in various fields where advanced simulations are required, including finance, engineering, and data analysis. | https://cran.r-project.org/web/packages/mc2d/index.html | Free | |
| MicroHibro | Predictive software designed for microbial risk assessment in the food industry. The software has 3500 users, 516 simulations, 237 models and 6 events. It offers modules for microbial prediction, shelf life estimation, risk assessment, sampling plans, and validation. | An unique predictive software with advanced functionalities for microbial risk assessment from farm to table; Easy-to-use features to facilitate the application of Predictive Microbiology models for Food Quality and Safety; 3500 users, | Evaluating food safety and hygiene in microbiological terms; Determining the shelf life of food products based on microbial, sensory, and physicochemical models; Conducting microbial risk assessments; Creating sampling plans for quality control; Validating experimental data against predictive models; | https://microhibro.com/ | Free | |
| Microrisk Lab | Microrisk Lab is an online freeware built by R language and Shinyapp.io. It covers comprehensive models in predictive microbiology and aims to simplify the process of microbial kinetic analysis or simulation. | Estimation module for various models; Simulation module for deterministic or stochastic simulation; | Microbial kinetic analysis; Simulation of microbial growth or inactivation; | https://microrisklab.shinyapps.io/english/ | Free | |
| Microbial Responses Viewer (MRV) | MR Viewer is a tool that provides access to a database of bacterial strains and their associated information. It appears to be focused on microbiological research, particularly in the area of food safety. | Database of bacterial strains; Number of records available for each strain; | Microbiological research Food safety research | http://mrviewer.info/ | Free | |
| nlsMicrobio (R package) | nlsMicrobio is an R package that provides data sets and nonlinear regression models dedicated to predictive microbiology. | offers a range of nonlinear regression models specifically for predictive microbiology | It aims to facilitate the analysis and modeling of microbial growth and inactivation data | https://cran.r-project.org/web/packages/nlsMicrobio/index.html | Free | |
| openFSMR | The open Food Safety Model Repository (openFSMR) is a community-driven search engine for predictive microbial models. | It serves as a search engine for predictive microbial models. | A search engine that focuses on predictive microbial models, desigmed for scientists | https://foodrisklabs.bfr.bund.de/openfsmr/ | Free | |
| OptiPa (an ODE modelling optimisation interface) | A free software tool built in MatLab that aims to simulate, calibrate, and validate ODE-based simulation models. It is primarily focused on food-related disciplines. | Simulation; Optimization; Sensitivity analysis; Bootstrapping; Monte-Carlo simulation; | Simulating, calibrating, and validating ODE-based models; Food-related disciplines | https://www.biw.kuleuven.be/biosyst/mebios/downloads/optipa/ | Free | |
| PMM-Lab | Predictive Microbial Modeling Lab is an open-source extension to the Konstanz Information Miner (KNIME). It is designed to ease and standardize the statistical analysis of experimental microbial data and the development of predictive microbial models. | Library of KNIME nodes; Library of standard workflows; HSQL database for data storage; | Statistical analysis of experimental microbial data; Development of predictive microbial models; | https://foodrisklabs.bfr.bund.de/pmm-lab/ | Free | |
| PMP | The Pathogen Modeling Program (PMP) Online is a tool developed by the United States Department of Agriculture's Agricultural Research Service. It focuses on providing models based on extensive experimental data of microbial behavior in liquid microbiological media and food. | Models based on extensive experimental data; Focuses on microbial behavior in liquid microbiological media and food; | Predict microbial behavior in liquid microbiological media and food; Validate models for specific foods; | https://pmp.errc.ars.usda.gov/PMPOnline.aspx | Free | |
| Praedicere Possumus | Praedicere Possumus is a free, web-based tool for predictive microbiology. It offers modules for modeling the behavior of foodborne pathogens under various conditions, helping users enhance food safety, design new food products, and assess microbiological risks. | http://praedicere.uniud.it/ | Free | |||
| Predoxypack | Predoxypack is an online software tool designed to simulate the oxygen evolution over time in the headspace of user-defined packages. | Simulates oxygen evolution in the headspace of packages; Allows customization of packaging designs, materials, and temperature profiles; Compares different packaging materials based on technical data sheets; | PredOxyPack is useful for professionals in the packaging industry, researchers, and businesses looking to understand and optimize the oxygen levels in their product packaging over time. | https://www.packitbetter.be/en/services/predoxypack/ | Free | |
| Process Lethality Spreadsheet | The Process Lethality Spreadsheet is a validation tool designed for processors to verify the efficacy of a specific heat process in destroying targeted microorganisms. It allows users to input in-process data and determine if the process meets the required log reduction for the microorganism in question. | The spreadsheet offers definitions for terms like Thermal Death Time, T ref, D-Value, z-Value, and F-Value. If the process achieves the necessary log reduction, the data and visual graphs from the spreadsheet can be incorporated into the HACCP validation materials. The tool is compatible with specific versions of Microsoft Excel. | The interactive model allows the user to input actual in-process data from a given cook cycle and determine if the process achieves the required log reduction for the microorganism of concern. | https://meatpoultryfoundation.org/content/process-lethality-spreadsheet | Free | |
| Shelf Stability Predictor | The Shelf Stability Predictor is a tool developed by the Center for Meat Process Validation at the University of Wisconsin - Madison. It provides models for predicting the growth of Listeria monocytogenes (LM) and Staphylococcus aureus (SA) on Ready-To-Eat meat products based on pH and water activity. | Predictive Models: Provides models for predicting the growth of Listeria monocytogenes and Staphylococcus aureus based on pH and water activity. User-Friendly Interface: Allows users to input the pH and water activity of their product and receive a probability score indicating the likelihood of pathogen growth. Guidance: Offers insights into what constitutes a shelf-stable product and how to interpret the probability scores. | Food Safety Planning: The tool can be used to design food safety plans and determine if a meat product is shelf stable; Risk Assessment: It aids in assessing the risk of pathogen growth in Ready-To-Eat meat products; Product Development: Manufacturers can use the tool to test and develop new meat products that are shelf stable; | https://meathaccp.wisc.edu/ST_calc.html | Free | |
| sQMRA | A swift Quantitative Microbiological Risk Assessment tool is a simplified Quantitative Microbiological Risk Assessment model designed to compare the risk of pathogen-food product combinations. It is implemented in Microsoft Excel and provides insights into pathogen numbers throughout the food chain. | Microsoft Excel Implementation: The tool is built within Excel, making it accessible and easy to use; Educational Emphasis: Designed to be insightful and suitable for educational purposes; Deterministic Model: Factors in cross-contamination, kitchen preparation, and dose-response relationship; Comparative Analysis: Outputs are compared with a comprehensive QMRA for a deeper understanding; | Risk Assessment: The sQMRA tool can be used by researchers and professionals to assess the risk associated with different pathogen-food product combinations; Educational Tool: Due to its clarity and structure, the tool can be used for educational purposes to teach students about risk assessment: Risk Management: The tool can assist in translating research results into risk terms, aiding in risk management decisions; | https://www.foodrisk.org/resources/display/56 | Free | |
| Sym’Previus | Sym’Previus is a comprehensive tool designed for microbiological data prediction. It assists manufacturers in ensuring food safety and quality by providing predictive models validated in food. | Predictive Models: An extensive repository of predictive models validated in food; User-Friendly Interface: Dynamic plots and charts simplify the analysis process; Support for Shelf-Life Determination: Assists in determining the shelf-life of products; Product Formulation and Process Optimization: Helps in product formulation and optimizing processes to reduce costs and time to market; Educational Reference: Referenced in educational kits developed by recognized institutions; | Shelf-Life Determination: Sym’Previus can be used to determine the shelf-life of food products; Product Formulation: Assists manufacturers in formulating products; Process Optimization: Helps in optimizing processes to reduce costs and time to market; Educational Reference: Can be used as a reference tool in educational settings; | https://symprevius.eu/en/ | Free | |
| The European Surveillance System (TESSy) | TESSy is a system that describes who has the right, how to access, and how to use data from TESSy. | Provides guidelines on accessing and using its data; Requires a Data sharing agreement before access is granted; Mandates the destruction of data after use; | TESSy is useful for researchers, public health professionals, and institutions interested in accessing and using surveillance data managed by the European Centre for Disease Prevention and Control. | https://www.ecdc.europa.eu/en/publications-data/european-surveillance-system-tessy | Free | |
| Therm 2.0 | THERM 2.0 is an online tool developed by the University of Wisconsin Center for Meat Process Validation. It is designed for evaluating the safety of meat or poultry at temperatures between 50°F and 115°F (10°C to 46°C). | Temperature-Based Safety Evaluation: Assesses the safety of meat or poultry products based on specific temperature ranges; Research-Based: Developed based on extensive research by the University of Wisconsin Center for Meat Process Validation; Referenced Paper: Provides a detailed paper that delves into the research and methodology behind the tool; | Safety Evaluation: THERM 2.0 can be used by manufacturers and researchers to evaluate the safety of meat or poultry products based on temperature exposure; Research and Study: The tool can be a valuable resource for researchers studying the effects of temperature on meat and poultry safety; Educational Reference: Can be used as a reference tool in educational settings, especially for courses related to food safety and meat processing; | https://meathaccp.wisc.edu/pathogen_modeling/therm.html | Free |