The decreasing availability of water has become more of a problem for turf management as a result of regional and localized drought, population growth, and a growing demand for water from competing uses. Improved irrigation management is important for enhancing turf performance during periods of drought stress and for conserving water. Determining plant and soil water content in response to water deficit conditions is beneficial for turfgrass site-specific irrigation management, particularly for locations that show large spatial and temporal variability in drought symptoms. Therefore, rapid and accurate assessment of turfgrass water status along with visual observation is essential for timely and proper irrigation as well as for drought stress management in turfgrass.
Leaf and soil water content and chlorophyll concentration are normally affected by water deficit in turfgrass (DaCosta et al., 2004; Jiang and Huang, 2000). These physiological changes can be measured by evaluating leaf or canopy reflectance without destructive sampling because spectral reflectance in the visible and infrared regions is closely associated with leaf pigment content (Bell et al., 2004; Cater and Spiering, 2002; Stiegler et al., 2005) and water content (Penuelas et al., 1993; Rollin and Milton, 1998). Turf quality, color, and leaf firing under water deficit conditions are highly correlated with spectral reflectance at a specific wavelength and/or with various indices derived from two or more wavelengths (Bell et al., 2002; Jiang and Carrow, 2005). The normalized difference vegetative index (NDVI), defined as (RNIR – Rred)/(RNIR + Rred), is one of the most widely used indices for evaluating turfgrass canopy characteristics (Jiang et al., 2003; Sönmez et al., 2008; Trenholm et al., 1999; Xiong et al., 2007). Once the correlations between canopy reflectance and physiological variables have been identified, relationships among these characteristics can be used to predict turf quality as well as the occurrence of stress and grass tissue water status in different species and cultivars. Furthermore, sensor-based tools may be developed and adapted to provide field mapping of turfgrass stress characteristics. For turfgrass water use, canopy reflectance and related models have been studied to predict soil water content (Dettman-Krues et al., 2008) and tissue moisture content (Baghzouz et al., 2006) as well as to evaluate irrigation programs (Hutto et al., 2006; Sönmez et al., 2008; Xiong et al., 2007) in both cool-season and warm-season turfgrass species. In addition to models developed in different turf species, models have been evaluated and optimized to assess drought responses for individual cultivars within a turfgrass species (Jiang and Carrow, 2007).
Responses of turfgrass to water deficit conditions can also be assessed by leaf or canopy temperature. Leaf temperature will be greater than ambient temperature when grasses are under drought stress as a result of reduced transpiration. The plant canopy temperature–ambient air temperature differential could reflect the water balance of a plant and has been studied as a tool in scheduling irrigation in Kentucky bluegrass (Poa pratensis L.) (Throssell et al.,1987). Significant correlations were found between broadband-based normalized difference vegetation index (NDVI; R600–650; R800–890) and canopy temperature (r = 0.54) and between NDVI and tissue moisture content (r = 0.90) in drought-stressed tall fescue [Schedonorus phoenix (Scop.) Holub] (Fenstermaker-Shaulis et al., 1997). These results provide information for further studying the relationships between canopy temperature and leaf and soil water content in different turfgrass species and cultivars.
Rapid and accurate estimates of plant and soil water content are critical for maximizing irrigation efficiency in turfgrass management. However, laboratory assessment of leaf relative water content is a time-consuming process, especially when a large number of samples are needed. As a result of the potential variations in drought response of turfgrass in the field, the use of multiple remote sensors to detect changes in canopy temperature and reflectance patterns may allow turfgrass performance under water deficit conditions to be more precisely assessed and spatially characterized. However, to date, the potential use of canopy temperature to predict leaf water content and its correlation with reflectance indices under water deficit conditions is not well understood in turfgrass species or cultivars. Although canopy reflectance has been studied as a means to identify relationships between canopy variables and soil moisture conditions, the relationships among spectral reflectance, leaf water content, and canopy temperature have not been studied extensively in turfgrass species. It is not clear if the changes in NDVI reflect the changes in leaf water content. A knowledge of the correlations among leaf relative water content (RWC), NDVI, and canopy temperature could aid irrigation management in improving turf quality. Perennial ryegrass (Lolium perenne L.) is a commonly used turfgrass species on golf course fairways, where spatial variations in drought stress often occur. Therefore, the objective of this study was to identify the changes and correlations among the canopy reflectance, canopy temperature, and RWC of perennial ryegrass under water deficit conditions.
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