This study aimed to model mycelial growth in a factorial experiment with two species of white rot fungi growing at five temperatures. The nonlinear models evaluated were logistic, Gompertz, Weibull and von Bertalanffy. The adjustments were performed first by evaluating the fixed and mixed-effects models with random effects, added to the fixed parameters. Then, the best adjusted model was improved by an adequated covariance structure, and dummy variables were added to the parameters asymptote $\left(\alpha \right)$ and abscissa of the inflection point $\left(\beta \right)$ in the model in order to verify the effect of the experiment factors, species and temperatures on the regression parameters. The criteria used to compare models were residual variance and Akaike information criterion. Gompertz and von Bertalanffy mixed-effects models were better adjusted. The parameters differed between species. Moreover, the linear and quadratic effects of temperature evaluated in each species were significant. The models were reparametrized in order to consider two parameters of interest: velocity ($\mu )$ at the inflection point and lag time ($\lambda$). The maximum growth velocity was obtained at 25.4 °C by S. ostrea, while T. villosa was achieved at 30.5 °C; both fungi suffered less lag time by increasing the temperature.

本研究旨在模拟在五个温度下生长的两种白腐真菌的因子实验中的菌丝体生长。评估的非线性模型是 Logistic、Gompertz、Weibull 和 von Bertalanffy。首先通过评估具有随机效应的固定和混合效应模型进行调整，添加到固定参数。然后，通过适当的协方差结构改进最佳调整模型，并在参数渐近线中加入虚拟变量$\left(\alpha \right)$ 和拐点的横坐标 $\left(\beta \right)$在模型中以验证实验因素、物种和温度对回归参数的影响。用于比较模型的标准是残差方差和 Akaike 信息标准。Gompertz 和 von Bertalanffy 混合效应模型得到了更好的调整。参数因物种而异。此外，在每个物种中评估的温度的线性和二次效应是显着的。模型被重新参数化以考虑两个感兴趣的参数：速度（$\mu )$ 在拐点和滞后时间（$\lambda$）。S. ostrea在 25.4 °C 下获得最大生长速度，而T. villosa在 30.5 °C 下获得；通过提高温度，这两种真菌的滞后时间都更短。