Site Specific Codling Moth Population Predictions
Insect phenology models are invaluable in the Integrated Pest Management (IPM) toolbox. They help consultants and growers predict key events in a pest’s life cycle, and enables them to target sprays for maximum impact.
While it’s fantastic that state extension services have made these models widely available for commercial adoption, using a general, or ‘one size fits all’ approach to pest modelling doesn’t always line up with the unique conditions occurring in an orchard.
Next Generation Pest Phenology Modelling
Fortunately, advances in microclimate monitoring have allowed for site-specific pest modelling that can be tailored to a location’s unique set of environmental conditions. This next generation of pest phenology modelling, allows growers to apply sprays so they are more accurate and effective.
A Little History
Codling moth phenology models have been used in Washington since the 1980’s when Jay Brunner and his colleagues adapted a model that had been developed in Michigan a decade earlier. The model developed in Michigan, known as the PETE model, was a game changer in that it allowed researchers to easily share their models for practical use for the first time. Growers and extension services simply had to input temperature data from their site, or a local weather station, and relevant pest predictions would be generated.
While this made phenology models more accessible, generalized models have never been designed to account for all the different variables in the landscape that might affect pest phenology.
It is well known that population phenologies can differ from region to region. Indeed in 2007, Alan Knight presented a new model based on seven sites in Washington, which fit the observed first flight and egg hatch better than the Michigan model. The new model suggested that 50% egg hatch occurred 100 DDF later than what the Michigan model predicted. Knight speculated that the differences between the two models was because of the wide adoption of mating disruption and change in management practices in Washington.
Putting The Data To Work
At Semios we process daily trap capture data for orchards throughout the Columbia Valley in Washington. From what we’ve observed, the model currently in commercial use can vary in its ability to predict pest populations from one grower to another.
Here is a comparison of the codling moth model currently used in Washington State and actual observed trap capture data for two of our Grant County customers from 2017.
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