Statistical analyses on bacterial growth was performed using R Statistical Software, version 3.6.0 [28 ]. The maximum possible population size in a particular environment, referred to as carrying capacity k, was determined for each growth curve using the R CRAN Packages “growthCurver” [29 (link)]. Carrying capacity k of both strains was compared across the media applying an ANOVA followed by a Tukey post-hoc test.
The analyses of the data collected on white-rot fungi growth was performed using R Statistical Software, version 3.6.0. The R/CRAN Packages used were “tidyverse”, “ggpubr” and “rstatix” [28 ,30 ,31 ,32 (link)]. Data of daily fungal growth rate over time was computed for each fungus by subtracting the previous from the following diametrical measurements and expressed as cm∙day−1. All data firstly underwent the Shapiro–Wilk’s Normality Test. The daily growth rates of the fungi, per each additive and concentrations, were then elaborated by non-parametric Kruskal–Wallis (p < 0.05) to evaluate the presence of significant differences among groups, followed by multiple comparisons between groups using Dunn’s Test (p < 0.05).
The analyses of the data collected on white-rot fungi growth was performed using R Statistical Software, version 3.6.0. The R/CRAN Packages used were “tidyverse”, “ggpubr” and “rstatix” [28 ,30 ,31 ,32 (link)]. Data of daily fungal growth rate over time was computed for each fungus by subtracting the previous from the following diametrical measurements and expressed as cm∙day−1. All data firstly underwent the Shapiro–Wilk’s Normality Test. The daily growth rates of the fungi, per each additive and concentrations, were then elaborated by non-parametric Kruskal–Wallis (p < 0.05) to evaluate the presence of significant differences among groups, followed by multiple comparisons between groups using Dunn’s Test (p < 0.05).