Evaluation of Turfgrass Stress through Thermal Imaging and Visual and near-Infrared Digital Image Analyses.

Published research has indicated that turfgrass quality, as assessed by color, can be objectively quantified using color indices developed from digital visual photography.  In this study, the effects of several different stresses and treatments were evaluated using multiple forms of digital image analysis.  Infrared thermal imaging was used in conjunction with several micrometeorological parameters to assess turfgrass quality via vapor pressure deficit measurements.  Both visual and near-infrared (NIR) imagery systems were used to correlate turfgrass quality and resistance to drought and heat stresses.  In addition, a simple algorithm to quantify percentage of leaf firing was developed based on visual digital analysis, serving as an indirect, objective estimate of turfgrass visual quality.  This algorithm was highly correlated (R² = 0.79) with subjective visual estimates.  A Light Red Color Index (LRCI) was also developed to correlate relative water status of several different turfgrass species using NIR technology, which quantified statistical differences between drought-stressed turfgrass and controls.  Other results will be discussed.