Abstract:
Trichoderma is a genus commonly found in the soils of all climatic zones. All most all the species
of Trichoderma can produce antimicrobial antibiotics and are good competitors of fungal
pathogens, which promote plant growth, enhance stress resistance and induce disease resistance
in plants. Interactions between plants and Trichoderma are ecologically important. Moreover, this
genus is economically much important because Trichoderma has been used as a biofertilizer and
bio pesticide. In the present study, the attention is given to Trichoderma species: Trichoderma
harzianum. The aim of this study was to detect a proper mathematical model to investigate the
frequency of occurrence of fungus; Trichoderma harzianum in Hakgala Montane Forest in Sri
Lanka at any period of time. Data for the frequency of occurrence of Trichoderma harzianum
were collected at once in three months intervals from the decomposing leaf litter of Hakgala
Montane Forest in a previous study. Significance of the data was checked using the ANOVA test.
Data were tested with five mathematical models (Exponential, Logistic, Gompertz, Brody, Von
Bertalanffy) and parameters estimated using the nonlinear least square method in R Studio
software. The models were tested for goodness of fit using the adjusted coefficient of
determination (R2), Akaike’s information criterion (AIC) and Bayesian information criterion
(BIC). The logistic model provided the best fit of the data due to the highest value of R2, lower
values of AIC and BIC than other models. The developed logistic model revealed 0.549% for the
growth rate of Trichoderma harzianum in Hakgala Montane Forest. Since the Hakgala Montane
Forest is an undisturbed natural ecosystem with its equilibrium stage this proposed model can be
used to investigate the frequency of Trichoderma harzianum at any time period even for future
predictions.