A ready-to-use logistic regression implemented in R shiny to estimate growth parameters of microorganisms

Modeling approaches have existed for many years to describe the growth of microorganisms under various physical and chemical conditions (Zwietering et al., 1990). In the environmental field, these models allow determining the conditions of optimal growth for newly isolated strains or describing the degradation of a compound by microorganisms. According to Zwietering et coll. the bacterial growth curve often presents a latency phase, of varying length, in which the specific growth rate is equal to zero and then growth accelerates to a maximum value. The growth curves contain a final phase in which the growth rate decreases and finally reaches zero so that an asymptote is reached. Traditionally in microbiology, the maximum growth rate is calculated by fitting a linear model on arbitrarily selected data from the exponential phase of growth. Here we propose a ready-to-use software to estimate growth parameters (maximum growth rate (named: Gr in-app), maximum density (named: Mp in-app), and the start of exponential phase (Start expo. phase) using nonlinear regression of a logistic equation. No programming or statistical skills are required for the application. With this following link, it is possible to use the app without any installation or coding experience : https://hpteam.shinyapps.io/logistic_microbio