Model of Grapholita molesta spring emergence in pear orchards based on statistical information criteria

Abstract

The oriental fruit moth, Grapholita molesta, is becoming a large threat to Korean pear production. Timely management of the egg and early larval stages from the spring emergence is critical to reduce the G. molesta population during the pear growing season. A model was developed to precisely predict the spring occurrence of G. molesta adults as a function of accumulated degree-days. The model was validated with male moth caught in sex pheromone-baited traps placed in pear orchards at two major pear production regions (Icheon and Naju) of Korea in 2010. We applied nine distribution models to describe the cumulative proportions of G. molesta males caught relative to accumulated degree-days. The observed phenology of the G. molesta spring population was well described by the nine models. The predicted dates for the cumulative 50% male moth catches were within a 5day period. Based on statistical information criteria (Akaike's and Bayes–Schwartz information criteria), we recommend the sigmoid function referred by Brown and Mayer, because of its ease of use and meaningfulness; the parameter “b” denotes the degree-day accumulation at 50% moth emergence. The G. molesta spring emergence model could be applied to determine optimal chemical treatment timing for controlling G. molesta in fruit tree orchards and further help to develop a full-cycle phenology model of G. molesta.