Using local weather stations to generate growing degree-day data to predict the flowering pattern of a perennial annual bluegrass (Poa annua L.) fairway in Michigan

November 9, 2021 - Author: Douglas Minier and Linda Hanson

Ronald N. Calhoun, Kevin W. Frank, Aaron D. Hathaway

Using local weather stations to generate growing degree-day data to predict the flowering pattern of a perennial annual bluegrass (Poa annua L.) fairway in Michigan

Intl Turfgrass Research Journal

In this paper, which was part of Ron Calhoun’s PhD dissertation, researchers tested a growing degree-day model with five years of observational studies data, to predict annual bluegrass (AB) seedhead emergence using readily available weather station data. The team found that a base temperature of -5 C most accurately predicted onset, peak duration, and completion of the AB seedhead emergence period for all five years. The final model accurately predicted flowering stages of an AB fairway turf over six years in Michigan, which proves it as a reliable method to predict key flowering events. This research was the foundation for the GDDTracker.net website which is used by industry professionals to track AB seedhead emergence and schedule plant growth regulator applications to suppress AB seedheads. 

https://doi.org/10.1002/its2.93

Tags: psmnewpublications

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