Digital Image Analysis and Spectral Reflectance to Determine Turfgrass Quality

Abstract

ABSTRACTe limitations of the conventional visual rating system used to assess turfgrass quality include its subjective nature and the need for properly trained observers who can discern di erences among treatments or turfgrass varieties. e objective of our study was to investigate if digital image analysis (DIA) and spectral re ectance [normalized di erence vegetative index (NDVI)] can be used to evaluate turfgrass varieties. Trials were established at New Mexico State University and visual quality ratings, digital images, and NDVI were collected monthly on three warm-season and three cool-season variety trials and on one cool-season and one warm-season mixed species trial. Correlations among quality, NDVI, dark green color index (DGCI) and percent green cover (PCov) were computed. Multiple regression was used to determine if combining NDVI and DIA improved the association between visual turfgrass quality and other variables. uality was most strongly associated with NDVI (R 2 ranging from 0.37 to 0.65) for most datasets. Additionally, multiple linear regressions identi ed NDVI as the variable a ecting a higher change in R 2 when entered to the model than either DGCI or PCov. Visual quality had a weaker association with sampling date than did NDVI or DGCI, which indicates that NDVI may track quality changes more reliably over time. However, a stronger association between variety and visual quality than between variety and NDVI or DGCI indicates that a visual assessment detects varietal di erences better. erefore, it is questionable whether visual assessments can be replaced by NDVI or DIA to characterize the aesthetic appeal of turfgrasses accurately.

Surfactant and Polymer‐Coated Sand Effects on Deficit Irrigated Bermudagrass Turf

“…Moreover, our visual quality data mirrored percentage green cover and NDVI measurements and our correlation analysis indicated a strong association between quality and NDVI and cover. These findings support those of Schiavon et al (2014) and Leinauer et al (2014) who also reported a significant correlation between subjective quality ratings taken on an ordinal scale and objective NDVI and DIA measurements.…”

“…Normalized difference vegetation indices (NDVI) were determined with a GreenSeeker Hand Held Optical Sensor Unit Model 505 (Trimble Corp., Sunnyville, CA) attached to a shoulder strap and held approximately 80 cm above the canopy. The unit was operated at walking speed (approximately 4 km h -1 ), thereby scanning a 100 cm wide area perpendicular to the direction of walking (Bell et al, 2009;Leinauer et al, 2014). Turfgrass quality was assessed visually on a 1 to 9 scale (1 = dead turf and 9 = dark green, uniform turf).…”

Plant Colorants Interfere with Reflectance‐Based Vegetation Indices

“…Reflectance‐based methods are more objective than traditional visual ratings, and the two methods are well correlated (Trenholm et al, 1999; Bell et al, 2009; Bremer et al, 2011a; Schiavon et al, 2011; Rimi et al, 2013; Leinauer et al, 2014). Still, several studies have demonstrated the limitations of replacing visual ratings with reflectance‐based methods.…”

Paspalum vaginatum NDVI when Grown on Shallow Green Roof Systems and under Moisture Deficit Conditions

“…Spectral reflectance has been widely used by many researchers for evaluating drought response of various turfgrass species (Fenstermaker‐Shaulis et al, 1997; Jiang and Carrow, 2007; Jiang et al, 2009; Merewitz et al, 2010; Rowland et al, 2014). Trenholm et al (1999) and Leinauer et al (2014) reported that NDVI was highly correlated with visual turf quality and shoot density of seashore paspalum.…”