MONTANA GOVERNOR NAMED COLORADO STATE UNIVERSITY COLLEGE OF ... - Colorado State University (press release)
- Montana Governor Brian Schweitzer will be one of 16 people honored Saturday, April 18 during the Colorado State University Distinguished Alumni Awards ceremony. Schweitzer will receive the College of Agricultural Sciences Honor Alumnus Award.Schweitzer earned a Bachelor of Science degree in International Agronomy from Colorado State in 1978. During his time at CSU, Schweitzer was active in the Agronomy Club, eventually becoming national president of the student section of the American Society of Agronomy.
Schweitzer then began a career of irrigation development that took him to Africa, Asia, Europe and South America before returning to his home state of Montana. In 2004, Schweitzer was elected as Montana's 23rd governor and first Democratic governor since 1988.
"With his ambition, creativity and leadership, you could tell that Brian was going to do big things," said Jack Fenwick, associate professor in the Department of Soil and Crop Sciences at Colorado State. Fenwick nominated Schweitzer for the 2009 Distinguished Alumni Award.
On the right side of my blog I have posted a link to the Michigan State Research Page . University research plays a vital role in turfgrass management and we rely a great deal on the publicly funded research projects for dealing with current as well as new challenges that face the turfgrass ecosystem. Much of this research is communicated via trade magazines and scientific journals but also through local and national seminars throughout the year. One important tool that we utilize which has come from university research is the Growing Degree Day model of predicting when to apply certain chemicals. In short, GDD are calculated by taking the average of the daily maximum and minimum temperatures compared to a base temperature. In our case we use the 32 degree base temperature. Here is a link to Michigan States GDD tracker web page. While this tracker does not include Colorado, it gives a good idea of how application timings can be better predicted for optimal effectiveness.