104-8 Improved Turfgrass Digital Image Analysis Through Normalization to Single Light Conditions.



Monday, October 17, 2011
Henry Gonzalez Convention Center, Hall C, Street Level

Scott M. Dworak, Roch E. Gaussoin and Timothy J. Arkebauer, University of Nebraska - Lincoln, Lincoln, NE
Perception of turf greenness is affected by conditions overhead.  Clear skies and diffuse shading from clouds alter light color temperature, which affects turf color.  Color temperature is the temperature of a black-body radiator that radiates light of comparable hue to that of the light source and is a characteristic of visible light.  Turf exposed to midday sunlight during clear conditions (~5500 K) appears more reddish yellow (warmer) compared to that under clouds (~6500 K), appearing more bluish green (cooler).  Collecting turf imagery under equal sunlight conditions averts this but is often not possible, necessitating use of artificial light sources.  Our work has demonstrated that digital image analysis (DIA)-based dark green color index (DGCI) data are highly correlated with color temperature in buffalograss (R2 = 0.97), creeping bentgrass (R2 = 0.96), and Kentucky bluegrass (R2 = 0.93) in field conditions and greenhouse-grown Kentucky bluegrass (R2 = 0.92) and tall fescue (R2 = 0.96) under natural sunlight.  DGCI coefficients of variation normalized to single light conditions (5000 K) versus varying cloud conditions (4900-7000 K) were, on average, 2.3% and 9.4%, respectively.  These data suggest turf DIA data can be normalized to a single light condition, correcting for changes in lighting conditions and vastly improving turf visual quality evaluation with DIA.
See more from this Division: C05 Turfgrass Science
See more from this Session: Student Poster Competition: Environment & Thatch-Soil, Water, and Pest Management