Improving Soil Moisture Assessment of Turfgrass Systems Utilizing Field Radiometry

The need for water conservation continues to increase as global freshwater resources dwindle. Turfgrass mangers are adapting these concerns by implementing new tools reduce consumption. Time-domain reflectometer (TDR) soil moisture sensors can decrease usage when scheduling irrigation, but nonuniformity across unsampled locations creates irrigation inefficiencies. Remote sensing data have been used estimate stress in turfgrass systems through the normalized difference vegetation index (NDVI). However, numerous stressors other than constraints impact NDVI values. band (WBI) is an alternative that uses narrowband, near-infrared light reflectance limitations within plant canopy. green-to-red ratio (GRI) a has proposed cheaper WBI it be measured using digital values of visible instead relying on more costly hyperspectral measurements. A replicated 2 × 3 factorial experimental design was repeatedly measure turf canopy and over time soils dried. Pots ‘007’ creeping bentgrass (CBG) ‘Latitude 36’ hybrid bermudagrass (HBG) were grown three textures: United States Golf Association (USGA) 90:10 sand, loam, clay. Reflectance collected hourly between 07:00 19:00 radiometer volumetric content (VWC) continuously embedded sensor from saturation until complete necrosis drought stress. had strongest relationship VWC (r = 0.62) compared GRI 0.56) 0.47). identified significant approximately 28 h earlier (p 0.0010). Those metrics also predicted prior fifty percent visual estimation wilt 0.0317), with lead times 12 9 (GRI). By contrast, provided prediction time. Nonlinear regression analysis showed useful predicting CBG HBG different textures controlled environment.