Non-Gaussian Growth Dynamics of Stagonosporopsis cucurbitacearum: A Bayesian Analysis of Logistic Models

We report a study on the growth dynamics of the fungal species Stagonosporopsis cucurbitacearum. Our experimental assays consisted of four different treatments, including a novel plant extract derived from melon. These assays provide valuable information on the growth of this species in various culture media. We fitted the growth curves using two logistic models commonly used in the literature (Verhulst and Gompertz), as well as a new one based on the non-additive Tsallis statistics: the $$\varvec{q-}$$ Gompertz model. We used Bayesian inference to evaluate the models’ fit to the observed data and select the best-fitting model. Our analysis suggests a potential advantage of the $$\varvec{q-}$$ Gompertz model. The entropic index $$\varvec{q}$$ is interpreted as a measure of the adaptation of the fungus to its environment.