Verdure: Before growing degree days were cool

GDDs have become a popular tool for the modern-day superintendent, but the concept first cropped up in turf management about 25 years ago.

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Filed to: Verdure

Recently, we’ve been hearing a lot about growing degree days (GDD). It seems like everyone is studying them and using them for everything from growth regulator application to measuring turfgrass growth.

GDDs are a great tool, but it should be noted that they are not especially new. Growing degree days have existed since the late 1950s, when the idea of using accumulated temperature degrees above (or below) some base temperature was first introduced for corn.

About 25 years ago, researchers at the University of Maryland (Mike Fidanza, Ph.D., now at Penn State, and Pete Dernoeden, Ph.D.) adopted the idea of GDD accumulation as a potential way to predict emergence of smooth crabgrass [Digitaria sanguinalis (L.) Scop.]. They thought that if they could predict soil and air temperatures at which crabgrass emerged, they could write a GDD model that would predict crabgrass emergence and allow for better timing of pre- and post-emergence herbicide applications, reducing pesticide use.

The study was conducted on a mature stand of Kentucky bluegrass with replicated treatments of two different mowing heights: 1.5 inches (3.7 centimeters) or 2.5 inches (6.4 centimeters). Every week from April until August for two years, newly germinated smooth crabgrass seedlings were counted (from predetermined squares of a known area) and removed. These crabgrass numbers were then used with collected soil and air temperatures (measured every 10 seconds, then averaged at five-minute intervals) from sensors that had been placed at three depths in each plot: thatch, 1 inch (2.5 centimeters) and 2 inches (5.0 centimeters). That data was used to produce a smooth crabgrass emergence model that used GDD accumulation.

At this location (the University of Maryland, Silver Spring, Md.), no crabgrass emerged before April 1. The best fit model for predicting crabgrass emergence was found using the soil temperature at the 1-inch depth. The best base temperature (at 1 inch), which is defined as the temperature below which biological activity or plant growth is zero, was found to be 54 F (12 C).

So, if soil temperatures were below the base temperature of 54 F, no GDD would be accumulating, and emergence would not yet occur. Of note: Most GDD models use a base temperature of 50 F (10 C), but with this study, a base temperature of 54 F (12 C) statistically provided the best mathematical fit.

And when did smooth crabgrass start to emerge? About one week before crabgrass was visible, soil temperatures of 60 F (15.6 C), 57 F (13.9 C) and 64 F (17.5 C) were measured in 1992, 1993 and 1994, respectively. This corresponded to a range of 52 GDDs in 1992, 42 GDDs in 1993, and 78 GDDs in 1994 for the first emergence of seedlings. The majority of seedlings emerged once the soil temperature was greater than 72.5 F (22.5 C), or within a range of 140 to 230 GDD (the range over the three years of study).

Did mowing height affect the utility of the model or the presence of smooth crabgrass? In general, seedling counts were similar under both mowing heights. Although smooth crabgrass is typically thought to be more invasive under low mowing heights, that did not hold true in this study in terms of initial seedling emergence.

The authors hypothesized that weekly removal of the crabgrass for counting eliminated competition and thus minimized differences caused by mowing height. As a result, the one GDD model could be applied across both mowing heights.

The GDD model accurately described the patterns of smooth crabgrass emergence at this location. However, the authors noted that such work is local in nature, and further work is always needed to expand the region of use. The authors pointed out that other factors such as soil moisture could affect time of germination and, thus, the GDD model.

Even so, the researchers’ GDD model is still in use by several turf pest forecast systems and programs today. Continued work will add greatly to the use of GDD models for predicting germination and emergence of weed species in turf.

Source: Fidanza, M.A., P.H. Dernoeden and M. Zhang. 1996. Degree-days for predicting smooth crabgrass emergence in cool-season turfgrasses. Crop Science 36:990-996.


Beth Guertal, Ph.D., is a professor in the Department of Crop, Soil and Environmental Sciences at Auburn University in Auburn, Ala., and the 2019 president of the Crop Science Society of America. She is a 20-year member of GCSAA.

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