Relationship of Multispectral Radiometry Data to Qualitative Data in Turfgrass Research

Abstract

Multispectral radiometry provides a method for assessing plant light reflectance in the visible and near‐infrared ranges. Reflectance of narrow wavelength ranges as well as ratios of different ranges have been highly correlated with absorbency of photosynthetically active radiation, leaf area index (LAI), and plant response to stresses. The objectives of this research were to determine if data obtained by multispectral radiometry might accurately correlate with qualitative data (used as rapid estimates of color, density, and uniformity) typically used in turfgrass research. Furthermore, it was our objective to determine whether multispectral radiometry could discriminate between stressed and nonstressed turfgrass plots. This research was conducted in two consecutive trials during 1997 on seven seashore paspalum (Paspalum vaginatum Swartz) ecotypes and three hybrid bermudagrass (Cynodon dactylon L. × C. trunsvaalensis Burtt‐Davy) cultivars established on a native Appling (clayey, kaolinitic, thermic Typic Kanhapludult) soil at the University of Georgia Experiment Station in Griffin, GA. Reflectance at 661 and 813 nm, as well as the ratios normalized difference vegetation index (NDVI, computed as R935‐ R661/R935 + R661), infrared/red (IRIR) (LAI, computed as R935/R661), Stress1 (R706/R760 nd Stress2 (R706/R813) were highly correlated with visual turf quality, shoot density, and shoot tissue injury (STI) ratings, but not with shoot clipping growth. Regression analysis also indicated very strong associations with each of these qualitative variables, but not with shoot growth data. Additionally, spectral measurements at all wavelengths except 559 and 706 nm were able to consistently distinguish between wear‐treated and untreated plots. This methodology may have applications in both turfgrass research and management to provide quantitative measures with physiological significance to traditional visual qualitative estimates of shoot aspects.

Uso de índices de reflectância das folhas para avaliar o nível de nitrogênio em grama-bermuda

“…MA et al (1996) verificaram relação positiva da reflectância com o teor de clorofila em plantas de milho. TRENHOLM et al (1999) obtiveram uma correlação linear positiva entre reflectância e a análise visual em algumas gramíneas. Essa relação pode ser considerada vantagem da utilização de medidores de reflectância em gramas.…”

Precision turfgrass management: challenges and field applications for mapping turfgrass soil and stress

“…These attributes respond to irrigation, fertilizer application, cultivation, climatic stresses, traffic stress and pests; therefore, turfgrass performance may be dynamic over the season or even during a dry-down between irrigation events. Trenholm et al (1999) and Bell and Xiong (2008) reported on the use of NDVI and other plant stress indices for assessing turfgrass performance.…”

“…For spectral reflectance, the normalized difference vegetation index (NDVI) has been the most commonly used plant performance or stress indicator. It correlates well with turfgrass quality (a combination of shoot density, color and uniformity) as affected by quality differences inherent to the species and cultivar, environmental stresses, fertilizer treatments or injury from pests (Trenholm et al 1999;Bell and Xiong 2008). Spectral reflectance can quantify plant response to stress, fertilizer applications or disease pressure, but the actual cause can be known only from a controlled study or by field observation.…”

Spectral Reflectance of Tall Fescue ( Festuca Arundinacea Schreb.) Under Different Irrigation and Nitrogen Conditions

“…In previous research, vegetation indices, calculated by combining band of the reflectance spectrum, were correlated with numerous turfgrass canopy parameters. Trenholm et al (1999), Jiang and Carrow (2007), reported on the utilization of normalized difference vegetation index (NDVI) and other spectral reflectance-based plant stress indices for assessing turfgrass performance, while Bell et al (2004) provided a recent review of optical sensing in turfgrass systems. NDVI was useful for detecting growth differences between species (Caturegli et al, 2014a).…”