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Microrisk Lab: an online freeware for predictive microbiology

Yangtai Liu, Xiang Wang, Baolin Liu, Qingli Dong
doi: https://doi.org/10.1101/2020.07.23.218909
Yangtai Liu
1University of Shanghai for Science and Technology, Shanghai, China
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Xiang Wang
1University of Shanghai for Science and Technology, Shanghai, China
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Baolin Liu
1University of Shanghai for Science and Technology, Shanghai, China
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  • For correspondence: blliuk@163.com dongqingli@126.com
Qingli Dong
1University of Shanghai for Science and Technology, Shanghai, China
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  • For correspondence: blliuk@163.com dongqingli@126.com
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Abstract

Microrisk Lab was designed as an interactive modeling freeware to realize parameter estimation and model simulation in predictive microbiology. This tool was developed based on the R programming language and ‘Shinyapps.io’ server, and designed as a fully responsive interface to the internet-connected devices. A total of 36 peer-reviewed models were integrated for parameter estimation (including primary models of bacterial growth/ inactivation under static and non-isothermal conditions, secondary models of specific growth rate, and competition models of two-flora growth) and model simulation (including integrated models of deterministic or stochastic bacterial growth/ inactivation under static and non-isothermal conditions) in Microrisk Lab. Each modeling section was designed to provide numerical and graphical results with comprehensive statistical indicators depending on the appropriate dataset and/ or parameter setting. In this research, six case studies were reproduced in Microrisk Lab and compared in parallel to DMFit, GInaFiT, IPMP 2013/ GraphPad Prism, Bioinactivation FE, and @Risk, respectively. The estimated and simulated results demonstrated that the performance of Microrisk Lab was statistically equivalent to that of other existing modeling system in most cases. Microrisk Lab allowed for uniform user experience to implement microbial predictive modeling by its friendly interfaces, high-integration, and interconnectivity. It might become a useful tool for the microbial parameter determination and behavior simulation. Non-commercial users could freely access this application at https://microrisklab.shinyapps.io/english/.

Competing Interest Statement

The authors have declared no competing interest.

  • List of symbols

    Y(t), Y0, Ymax
    the natural logarithm of real-time, initial, and maximum bacterial counts (ln CFU/g).
    y(t), y0, ymax
    the 10-base logarithm of real-time, initial, and maximum bacterial counts (log10 CFU/g).
    yres
    the 10-base logarithm of the residual bacterial counts (log10 CFU/g).
    μmax, μopt
    the maximum and optimal specific growth rate.
    kmax
    the maximum specific inactivation rate.
    D
    the time of decimal reduction in inactivation.
    Dref
    the referenced decimal reduction time at Tref.
    tlag
    the time of lag in growth.
    Sl
    the time of shoulder (or before inactivation) in inactivation.
    t
    the time point.
    tmax
    the time when entering the stationary phase in growth.
    St
    the time when entering the stationary phase in inactivation.
    T, pH, aw
    The temperature (°C), pH, and water activity at t.
    Tmin, Topt, Tmax
    the minimum, optimal, and maximum growth temperature (°C).
    Tref
    the referenced inactivation temperature (°C).
    pHmin, pHopt, pHmax
    the minimum, optimal, and maximum growth pH.
    awmin, awopt, awmax
    the minimum, optimal, and maximum growth water activity.
    q0
    the initial physiological state of the inoculum in the Baranyi model.
    δ, p
    the coefficients in the Weibull model.
    δref
    the referenced δ value at Tref.
    a, b
    the coefficients in the square-root model.
    A, m
    the coefficients in the dynamic Huang model.
    z
    the coefficients of the bacterial thermal resistance (°C).
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    Posted July 24, 2020.
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    Microrisk Lab: an online freeware for predictive microbiology
    Yangtai Liu, Xiang Wang, Baolin Liu, Qingli Dong
    bioRxiv 2020.07.23.218909; doi: https://doi.org/10.1101/2020.07.23.218909
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    Microrisk Lab: an online freeware for predictive microbiology
    Yangtai Liu, Xiang Wang, Baolin Liu, Qingli Dong
    bioRxiv 2020.07.23.218909; doi: https://doi.org/10.1101/2020.07.23.218909

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