Weather and Pest Monitoring and Forecasting

UMass has recently joined the Network for Environment and Weather Applications (NEWA), a web-based weather and pest reporting and forecasting system. This was developed by the New York State Integrated Pest Management program, and uses a network of weather monitoring stations. Forecasts and alerts for insect and disease pests of fruits and vegetables are published. Weather stations around New York have been included for a long time, but for the first time there are over twenty Massachsuetts locations that are reporting to this network.  These are located at farms and airports and report hourly temperatures, daily max and min T, rainfall, relative humidity and hours > 90% RH, and windspeed. These data points then run through models that predict key events like when an insect pest will become active or when a disease might develop. For example, it has models for cabbage and onion maggot, and late blight of tomato and potato. There are links to other forecasting website such as cucurbit downy mildew. It also reports out the growing degree day (GDD) accumulation by day, month and season at two base temperatures; 50 F and 40 F, along with GDD models for pest flights. This is a terrific resource for farmers, easy to navigate and updated daily. It’s great to just pick a weather station and get degree days, a whole weather report for the previous month, or a forecast for a specific pest.

The UMass Extension Fruit program has taken the lead to establish this MA connection to NEWA, and it will benefit both fruit and vegetable growers. UMass is working to add additional on-farm stations, and to add leaf wetness to the weather parameters so that certain disease models such as tomato early blight can be included in the MA network.

According to the NEWA website, NEWA users reported that they can save, on average, $19,500 per year in spray costs and prevent, on average, $264,000 per year in crop loss as a direct result of using NEWA pest forecast models.

You can access this data and the associated pest models at www.newa.cornell.edu.