Stage‐specific probabilistic phenology model of Cydia pomonella (Lepidoptera: Tortricidae) using laboratory maximum likelihood parameter estimates

Abstract

In this study, a probabilistic degree‐day phenology model has been developed for the codling moth, Cydia pomonella, and calibrated using data from laboratory growth studies. The model is further used to predict the succession and overlapping of certain biological events of C. pomonella in probabilistic‐physiological time scale in northern Greece fruit orchards. The model satisfactorily predicts the stage‐specific pest population dynamics, including egg laying and hatching, the occurrence of larvae and pupae stages and the emergence of adults. According to the model projections for the adult flights, there is a very high probability, p = 0.999, of observing adults of the first flight generation until 333 degree‐days (DD), but a very low probability of finding adults of the second flight generation. Moreover, at 575 DD, the probability of finding an individual to lay eggs is p = 0.15. However, there is nearly the same probability of egg hatch, p = 0.36, and larval completion p = 0.313, while at the same time, the probability of pupal completion is very low, p = 0.001. The above model predictions were validated using field data for the adult stage emergence as well as for the percentage of larval damage providing satisfactory results considering that larval emergence prediction was close to actual fruit damage observed in field. This information is very important considering that IPM programs rely on the use of biorational compounds, such as IGRs and bio‐toxins which are stage selective and often have a shorter residual activity than the preceding broad‐spectrum insecticides.

Advances in insect pest and disease monitoring and forecasting in horticulture

“…Improvements of phenology models are still needed to make the outputs more precise and to improve region or site specificity of outputs, as shown for root-feeding insect pests such as the carrot fly and the cabbage root fly (Bažok et al, 2012;Biron et al, 2002;Collier et al, 2020;Dreves, 2006;Villeneuve and Latour, 2017) and the codling moth (Damos and Soulopoulou, 2019). Producing phenological forecasting models can be complicated by genetic and behavioural differences between different pest (or natural enemy) populations, as exemplified by the winter morphs of D. suzukii (Amarasekare and Shearer, 2013;Shearer et al, 2016) and late and early emerging forms of Delia radicum.…”