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Why Your GDD Estimate Isn’t Good Enough—and How to Fix It
Webinar - May 28, 2021

Why Your GDD Estimate Isn’t Good Enough—and How to Fix It

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You may be unwittingly compromising your predictions

If you’re running GDD models to know when to act for disease and pest management and your data is not accurate, your predictions can be off by 7-10% or more, impacting both yield and profit.

Check out the graph below from a Washington apple orchard. Inaccurate virtual temperature data caused huge errors—nearly 500 degree days in 2019.

How to nail your estimates and act at the right time

When you use inaccurate data, the further you are into the growing season, the greater the estimate will differ from reality. For longer season crops, the difference could be quite significant, which is a problem because plant maturity, flowering, and pest/disease GDD targets often have tight windows.

In this 20-minute webinar, Dr. Colin Campbell discusses what you need to know for more accurate models, so you can be confident in your management decisions.

Virtual data GDD error vs. observed degree days AgWeatherNet
Figure 1. Source: AgWeatherNet

 

Presenter

Dr. Colin Campbell has been a research scientist at METER for 20 years following his Ph.D. at Texas A&M University in Soil Physics. He is currently serving as Vice President of METER Environment. He is also adjunct faculty with the Dept. of Crop and Soil Sciences at Washington State University where he co-teaches Environmental Biophysics, a class he took over from his father, Gaylon, nearly 20 years ago. Dr. Campbell’s early research focused on field-scale measurements of CO2 and water vapor flux but has shifted toward moisture and heat flow instrumentation for the soil-plant-atmosphere continuum. He recently received the prestigious Fellow Award for outstanding scientific contributions from the American Society of Agronomy (ASA).

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