Using local weather stations to generate growing degree‐day data to predict the flowering pattern of an annual bluegrass fairway in Michigan. Issue 1 (12th December 2021)

• Record Type: Journal Article
• Authors: Calhoun, Ronald N.; Frank, Kevin W.; Hathaway, Aaron D.
• Is Part Of: International Turfgrass Society Research Journal. Volume 14:Issue 1(2020)
• Page Start: 462
• Page End: 469
• Publication Date: 2021-12-12
• Subjects: 635.9
• DOI: 10.1002/its2.93
• Languages: English
• ISSNs: 1817-0641

Abstract

Abstract: Six 1‐yr observational studies were conducted from 2001 to 2006 at the Hancock Turfgrass Research Center in East Lansing, MI to characterize the timing, duration, and amplitude of annual bluegrass (AB) ( Poa annua L.) seedhead emergence in a 10‐ to 15‐yr‐old AB fairway. The objective of this research was to collect data that could be used in the development of a growing degree‐day (GDD) model to predict AB seedhead emergence at other locations by using readily available weather station data. New GDD models were compared with previously published models. Plots were established on two adjacent perennial stands of AB maintained at 1.5 cm, receiving 0.5 to 0.6 cm of automatic daily irrigation throughout the growing season and 120 kg N ha –1 yr –1 from 2001 to 2006. The soil type is a Marlette sandy loam (fine‐loamy, mixed, semiactive, mesic Oxyaquic Glossudalf). Line intersects and visual estimations of seedhead cover were evaluated multiple times throughout the spring seedhead emergence period. A base temperature of –5 °C most accurately predicted the onset, peak duration, and completion of the AB seedhead emergence period for all 5 yr. The final model flowering rate = (–3.331599 × 10 –6 × gdd 2) + (6.968782 × 10–3 × gdd ) + –2.841894, accurately predicted ( R 2 = .64) flowering stages of an AB fairway turf over 6 yr in Michigan. Core Ideas: Growing degree‐days (GDD) were reliable for predicting annual bluegrass flowering events. Simple average GDD calculations (base temperature: −5 °C) provided accurate estimates. Local weather stations can be used to calculate GDD effectively, which could expand GDD use.