Suitable models to describe the effect of temperature on conidial germination and mycelial growth of Metarhizium anisopliae and Beauveria bassiana

Abstract

Temperature critically affects the performance of entomopathogenic fungi (EPF). Mathematical models are critical tools used in predictive microbiology but are less adopted for EPF. We selected eight nonlinear models to describe thermal biology; minimum (Tmin), optimal (Topt) and maximum (Tmax) thresholds; and maximal growth (Pmax) of EPF. Conidial germination and mycelial growth of Metarhizium anisopliae (ICIPE 7, ICIPE 20, ICIPE 62, ICIPE 69, ICIPE 78) and Beauveria bassiana (ICIPE 284) isolates incubated at 12, 16, 20, 24, 28, 32 and 36°C were measured and fitted to the models. The models were compared using the Akaike information criterion (AIC) and adjusted R2. The best–fitting models for germination of the isolates were the cardinal temperature model with inflection (CTMI), Ratkowsky 3 and the generalised β function, while the best–fitting models for growth were CTMI, Ratkowsky 3, Lactin 1 and generalised β function. Brière 1, Brière 2, Ratkowsky 2, and Van Der Heide least fitted most germination and growth datasets. Tmin, Topt, Tmax and Pmax ranged from 13.3–13.6°C, 26.3–28.1°C, 35.7–36.3°C and 95.4–100.0% for germination, and 3.7–13.7°C, 25.9–28.6°C, 35.4–37.2°C and 1.44–2.34 mm day–1 for growth, respectively. Topt were below temperatures of central bee brood areas and partly mirrored temperatures of the isolates’ regions of origin. The best–fitting models can be used to better match EPF with different regions’ temperatures for optimal performance against target pests.