COMPARISON OF DIFFERENT MODELS FOR PREDICTING DEVELOPMENT TIME OF THEEUROPEAN CORN-BORER (LEPIDOPTERA, PYRALIDAE)

Nine nonlinear models (degree-day with a 10 degrees C base, degree-day model, polynomial, normal distribution, Stinner model, Sharpe and DeM ichele model, Logan model with or without a base, Hilbert and Logan mo del) were tested to describe the relationship between development rate and temperature for the European corn borer, Ostrinia nubilalis Hubne r. These models were calibrated with laboratory experiments based on d estructive sampling under sinusoidal temperatures from 9 to 42 degrees C. They were then evaluated and compared with field experiments, at t emperatures from 4 to 37 degrees C, carried out as artificial infestat ions in various areas. Laboratory development models with the smallest time shifts between predicted and observed molts were the Sharpe and DeMichele model, polynomial model, normal distribution,, and Stinner m odel. A classification with an adjusted coefficient of determination ( taking into account the number of parameters in the model) slightly mo dified the results and the best models were the polynomial and the nor mal distribution, followed by the Stinner model and the degree-day mod el with a 10 degrees C base. The classification was almost reversed un der field conditions. Large shifts occurred in all models in some expe riments, thereby demonstrating that temperature was not the only facto r involved. Models showing the smallest shifts under field conditions were the degree-day model and the Logan model. The experiments that sh owed the greater shifts corresponded to infestations on early or on la te phenological stages of corn. Results confirmed that the experimenta l design and calibration method were adequate. The laboratory experime nts provided a means of calibrating the models and of predicting resul ts under field conditions from laboratory experiments. Future studies will focus on a precise quantitative analysis of factors affecting dev elopment other than temperature, notably infestation date, climatic fa ctors, and phenological stage of corn.