By Greg Loeb and Juliet Carroll
Grape growers in New York State concerned about grape berry moth (GBM) infestations have a new ally: a user-friendly, online tool to predict the timing of outbreaks. This tool is the latest addition to the New York State Integrated Pest Management (IPM) Program's Network for Environmental and Weather Applications (NEWA) website, which provides growers with on-site agricultural weather information from over 50 locations throughout New York. The GBM forecasting tool joins disease forecasting models for grapes hosted at the site, providing growers with tools to target sprays at the best time for managing pests.
GBM is a key pest of grapes in the Northeast and capable of producing up to four generations per growing season. Predicting when each generation will emerge has been difficult for grape growers and entomologists alike. Yet growers must align the spray's window of effectiveness—usually seven days or less—with egg hatch, before the larvae shelter inside the berry. This new tool allows growers to improve the timing of insecticide sprays, for more effective and sustainable pest management.
To develop the forecasting model, researchers had to identify key predictors for outbreaks. GBM's development, like that of grapes, is driven largely by daily temperature accumulations or degree days (DD) during the growing season. The other crucial piece of information is the 'biofix', a baseline date to start the degree day accumulation count for this particular insect. Research has shown that the bloom date of the common wild grape Vitis riparia—which typically occurs 8 to 14 days before commercial grapes bloom—can serve as an accurate biofix for GBM.
To use the model, growers enter three pieces of information: the date at which V. riparia reached 50% bloom in their area, the closest NEWA weather station, and the current date. If the V. riparia bloom date is unknown, the program will estimate it based on historical records. Growers can select from over 50 weather stations in the New York State NEWA network to find the site closest to their vineyard for weather records. Then, the model calculates the accumulated DD based on weather data and provides the following information:
- DD accumulations since the biofix date
- a forecast of degree-day accumulation over the next five days
- the predicted pest status and management recommendations for their vineyard.
For example, when degree day accumulations approach 810 DD, the program will predict peak egg-laying activity of the second generation of GBM. It will also advise when to apply insecticide in high-risk vineyards and scout for damage in low or intermediate risk vineyards.
The 'GBM risk' categories are based on the 1991 publication Risk Assessment of Grape Berry Moth and Guidelines for Management of Eastern Grape Leafhopper. While the forecasting tool is not a substitute for growers' observations about plant growth, pest presence, and disease in their vineyards, it can provide a timely warning when the likelihood of an outbreak is high.
This new program joins the existing disease forecasting tools available through NEWA for grape powdery mildew, phomopsis cane and leaf spot, black rot, and downy mildew previously developed by the New York State IPM Program. The GBM module was developed through the collaboration of entomologists Greg Loeb (Cornell University), Mike Saunders (Pennsylvania State University), and Rufus Isaacs (Michigan State University) with climatologist Keith Eggleston (Northeast Regional Climate Center-NEWA) and IPM experts Juliet Carroll and Tim Weigle (New York State IPM program).
The pest and disease forecast models can be accessed through this interactive page at the NEWA website.
Greg Loeb is a professor of entomology at the New York State Agricultural Experiment Station. Juliet Carroll is the Fruit IPM Coordinator for the New York State IPM Program.