Effects of water stress on spectral reflectance of bermudagrass.

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.

Reflectance, absorbance and transmittance spectra of bermudagrass and manilagrass turfgrass canopies.

Leaves act as a primary organ for the interception of solar radiation and their spatial arrangement determines how the plant canopy interacts with light. Many studies have been carried out on the penetration of radiation into crops however to date, few results are available on turfgrasses, mainly due to the difficulties of introducing sensors into the turf without disturbing the natural position of the leaves. In the present research two warm season turfgrasses, hybrid bermudagrass (Cynodon dactylon × transvaalensis) 'Patriot' and manilagrass (Zoysia matrella) 'Zeon', were studied. The aim was to describe their canopy architecture grown with minimal disturbance to the natural arrangement of the leaves and stems, and to determine the potential effects of canopy architecture on light penetration and reflectance. Radiometric measurements were carried out at eight different profile levels of turfgrasses that were up to 12 cm tall. A LI-COR 1800 spectroradiometer with an optical fiber cable and a 7 mm diameter sensor was used. Measurements were carried out in the 390-1100 nm region at 5 nm intervals. The LAI value was higher for the manilagrass (9.0) than for the hybrid bermudagrass (5.6). The transmitted radiation was found to be closely dependent on downward cumulative LAI. Despite a more upright habit (mean insertion angle of 22.4° ±3.4), Zoysia matrella showed a higher NIR reflectance compared to Cdxt, which has a horizontal leaf arrangement (mean insertion angle 62.1° ± 9.6). The species studied showed substantial differences both in terms of phytometric characteristics and in the capacity to attenuate solar radiation.

Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses.

Spectral reflectance data originating from Unmanned Aerial Vehicle (UAV) imagery is a valuable tool to monitor plant nutrition, reduce nitrogen (N) application to real needs, thus producing both economic and environmental benefits. The objectives of the trial were i) to compare the spectral reflectance of 3 turfgrasses acquired via UAV and by a ground-based instrument; ii) to test the sensitivity of the 2 data acquisition sources in detecting induced variation in N levels. N application gradients from 0 to 250 kg ha-1 were created on 3 different turfgrass species: Cynodon dactylon x transvaalensis (Cdxt) 'Patriot', Zoysia matrella (Zm) 'Zeon' and Paspalum vaginatum (Pv) 'Salam'. Proximity and remote-sensed reflectance measurements were acquired using a GreenSeeker handheld crop sensor and a UAV with onboard a multispectral sensor, to determine Normalized Difference Vegetation Index (NDVI). Proximity-sensed NDVI is highly correlated with data acquired from UAV with r values ranging from 0.83 (Zm) to 0.97 (Cdxt). Relating NDVI-UAV with clippings N, the highest r is for Cdxt (0.95). The most reactive species to N fertilization is Cdxt with a clippings N% ranging from 1.2% to 4.1%. UAV imagery can adequately assess the N status of turfgrasses and its spatial variability within a species, so for large areas, such as golf courses, sod farms or race courses, UAV acquired data can optimize turf management. For relatively small green areas, a hand-held crop sensor can be a less expensive and more practical option.