*2.7. Data Analysis*

Data were analysed with JMP Pro (JMP®, version 14. SAS Institute, Inc., Cary, NC, USA). All data were assessed for normality and homoscedasticity. Growth rate data, DML, respiration and ergosterol, were normally distributed, homoscedastic and independent. Therefore, data sets were analysed using two-way Analysis of Variance (ANOVA) for the determination of the significance between aw treatments and inoculation position. Then, Students t- or Tukeys HSD test were used to identify significant differences between groups. Mycotoxins accumulation data were not normally distributed, therefore a Kruskal–Wallis test for the determination of the significance between aw treatments and inoculation position was undertaken. Then, non-parametric comparisons for each pair was conducted using the Wilcoxon test. The statistical relationship between variables was assessed by Pearson or Spearman correlations. A signification level of 5% was assumed for all statistical analysis.

The "fit\_growthmodel" function of the "growthrates" R package [24] was used to fit the colonisation data to a two-phase linear model of the form:

$$\mathbf{C}\_{l} = (t \succ \lambda) \ast \mathbf{R}\_{\mathbb{C}} \ast (t - \lambda), \tag{1}$$

where *Ct* is the colonisation (cm<sup>2</sup> or cm3) at time *t* (days), λ a lag phase with 0 colonisation (days) and *Rc* the colonisation rate (cm<sup>2</sup>·day−<sup>1</sup> or cm3·day−1).
