Abstract
In the south-central Italy, during summer rainfall does not supply a sufficient amount of water. Therefore, irrigation management during dry periods is important for maintaining turf quality. The hybrid bermudagrass (Cynodon dactylon (L.) Pers. × Cynodon transvaalensis Burtt–Davy) is known to represent the dominant warm-season turfgrass in warm to temperate climatic regions and its drought tolerance make bermudagrass a competitive turfgrass. A greenhouse experiment was conducted using uniform cores of hybrid bermudagrass, which were secured in a polyvinyl chloride cylinders and watered by constant sub-irrigation. The objectives of the present research were to measure the spectral reflectance with a new generation handheld spectroradiometer on hybrid bermudagrass and to explore various vegetation indices to be used as future detecting tool to study water stress in bermudagrass. Moreover, the potential uses of multivariate processing techniques for discriminating different water stress conditions in turfgrass has been investigated. Besides spectral indices, multivariate methods, although performed on a data set limited in terms of sample size, have shown a great potential for water stress monitoring in turfgrass and surely deserve further investigations. There are different indices that use distinct water absorption features independent of chlorophyll concentration, such as water index (WI = R900/R970) that has been reported to be a robust index of canopy water content and is used as an active indicator of changes in Leaf Relative Water Content (LRWC). Also, the ratio of WI with NDVI (WI/NDVI = (R900/R970)/((R800 − R680)/(R800 + R680)]) was found to be an effective indicator of water stress. Another vegetation index to detect water features is normalized difference water index (NDWI), designed to maximize reflectance of water by using green wavelengths. In our trial in bermudagrass the relationships studied, suggest that WI (900/970) and WI/NDVI, among the indices studied, are the more effective indicators of water stress. In fact, lower values of WI indicate higher water stress, while higher values of WI/NDVI indicate higher water stress levels.
Highlights
In the south-central Italy, during summer rainfall does not supply a sufficient amount of water
The major difference is the increase of reflectance at all wavelengths at 16 days without watering, where Leaf Relative Water Content (LRWC) was at about 18% (Fig. 2), with respect to the other two spectral reflectance curves
It is so evident from the three different curves that in the Near-infrared (NIR 750–1,300 nm) and Short-wavelength infrared (SWIR 1,300–2,500 nm) four major absorption troughs are present
Summary
In the south-central Italy, during summer rainfall does not supply a sufficient amount of water. × Cynodon transvaalensis Burtt–Davy) is known to represent the dominant warm-season turfgrass in warm to temperate climatic regions and its drought tolerance make bermudagrass a competitive turfgrass. The objectives of the present research were to measure the spectral reflectance with a new generation handheld spectroradiometer on hybrid bermudagrass and to explore various vegetation indices to be used as future detecting tool to study water stress in bermudagrass. The ratio of WI with NDVI (WI/NDVI = (R900/R970)/((R800 − R680)/(R800 + R680)]) was found to be an effective indicator of water stress Another vegetation index to detect water features is normalized difference water index (NDWI), designed to maximize reflectance of water by using green wavelengths. Irrigation management during dry periods is important for maintaining turf quality[1], in addition to an optimal turfgrass mowing management[2]. The analysis of the radiation reflected from the canopies can provide information about the water status of the vegetation that generated it and can be used in remote sensing to determine a possible water d eficiency[16]
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