Prediction Challenges

The seedcorn maggot presents a unique challenge because many crop fields that may be at risk for attack are unpredictable. While most fields will receive negligible damage from the seedcorn maggot, some fields may suffer high stand losses. This uncertainty creates a management dilemma and an opportunity to make a risk assessment model.

The seedcorn maggot is a pest during a limited period when seeds are susceptible to damage during and shortly after germination. Therefore, avoidance by planting before or after seedcorn maggot emerges is a cultural management strategy to consider. This cultural practice relies on highly accurate models for seedcorn maggot emergence based on local temperatures.

Refining Data to Increase Accuracy

The current seedcorn maggot model launched by New York State IPM on the NEWA platform relies on data collected from Iowa, Ohio, and Manitoba, due to the absence of data specific to New York State. Entomologists at Cornell University are working on updating this model with data from the growing regions within New York State. This work has already increased the accuracy of the NYS model by three weeks, and it will continue to refine the model with data from upcoming growing seasons (check the most up-to-date model.)

Researchers are working on modeling when seedcorn maggots will emerge and what variables predict where they will be a problem. Determining if seedcorn maggot damage correlates with factors such as local management practices or the composition of the landscape around a field will further increase the predictive capacity of this model.

Findings are preliminary and are not intended to replace current management plans or control methods. Additional research is being conducted to help inform long term recommendations and guidance.