Evaluating Turfgrass Color through Digital Image Analysis Using Greenindex+ Turf Smartphone App.

Turfgrass color is an important component of overall turf quality. Visual assessments of turfgrass color pertaining to nutrient and water status can be valuable indicators of plant health. While visually rating turf color using a 1-9 scale is a longstanding practice in turfgrass research, visual evaluations are an inherently subjective process which encounter both temporal and spatial limitations due to effects of ambient lighting. Digital image analysis (DIA) based on the dark green color index (DGCI) is a more objective method for quantifying turfgrass color; however a digital camera, standardized lighting source, and image analysis software are required. The GreenIndex+ Turf app (Spectrum Technologies Inc.) calculates DGCI in the field while accounting for ambient lighting conditions. The GreenIndex+ Turf app utilizes the built-in digital camera of a smart device along with reference color standards of a target board, without the need for artificial lighting or additional image analysis software. The objective of this research was to compare the GreenIndex+ Turf app to traditional DIA methods for measuring turfgrass color. In 2014 various nitrogen fertility treatments were used to create a range of turf color on a creeping bentgrass (Agrostis stolonifera) putting green. Plots were evaluated ten times over nine weeks using both methods. Regression analysis produced a linear prediction equation relating DGCI values from the GreenIndex+ Turf app to those obtained from traditional DIA methods with an average slope and intercept of 0.45151 and 0.42409 respectively. In 2015 ambient lighting conditions were measured throughout image collection as plots were evaluated seven times over a 16 hour period. Comparisons using the 2014 equation achieved maximum R² (0.7516) within ambient light range of 7 to 24 μmol m^-2 s^-1. Further comparisons using different smart device cameras offer potential for improving correlation of this app to accepted research methodology.