Full TGIF Record # 333405
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Web URL(s):https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/149767
    Last checked: 12/01/2023
Publication Type:
Content Type:Abstract or Summary only
Author(s):McLoughlin, Patrick; Schiavon, Marco; Kaddoura, Youssef
Author Affiliation:McLoughlin: Presenting Author and University of Florida, Davie, FL; Schiavon: Environmental Horticulture, University of Florida, Davie, FL; Kaddoura: Geomatics, University of Florida, Davie, FL
Title:RGB vegetation indices in comparison to NDVI to evaluate the performance of warm-season turfgrass
Section:Turf management and ecology poster (includes student competition)
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C05 turfgrass science
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Meeting Info.:St. Louis, Missouri: October 29-November 1, 2023
Source:ASA, CSSA, SSSA International Annual Meeting. 2023, p. 149767.
Publishing Information:[Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America]
# of Pages:1
Abstract/Contents:"Across the United States and much of the globe, turfgrass is managed at a multitude of scales and requires new technology for efficient monitoring and management. Currently, handheld devices allow for the collection of normalized differences vegetation index (NDVI) which is considered commonplace when conducting research on plants such as turfgrass. The introduction of unmanned aerial systems (UAS) provides researchers with readily available red, green blue (RGB) cameras with high resolution capabilities, which may add considerable value to researchers and producers when assessing turfgrass performance. A study was conducted at the Ft. Lauderdale Research and Extension Center (FLREC) in Davie, FL in the Spring (Feb-April) of 2023 to evaluate the performance of RGB vegetation indices on 'Celebration' bermudagrass [Cynodon. dactylon (L.) Pers.] and 'CitraBlue' St. Augustinegrass [(Stenotaphrum secundatum) Walt.]. This research looked to compare the efficiency of RGB indices to multispectral indices such as NDVI. The study site for this experiment overlaps with an ongoing study evaluating reclaim water irrigation and provides a wide range of nutrient exposure to research plots. Images were obtained by an RGB camera coupled to a remotely piloted Parrot ANAFI Thermal drone capturing images with 75% overlap. Green leaf index (GLI) and green chromatic coordinate (GCC) were found to correlate similarly (r = .63 and .62, respectively) to visual quality ratings when compared to normalized difference vegetation index (NDVI) values (r = .62) in bermudagrass plots. Interestingly, normalized green red difference index (NGRDI) and modified green red vegetation index (MGRVI) (r = .66) were both found to outperform NDVI in bermudagrass but were significantly uncorrelated (r = .58 and .57) to visual ratings in St. Augustinegrass. NDVI (r = .83) was the most correlated to visual quality in St. Augustinegrass, with GCC and GLI having similar correlations (r = .80 and .79)."
Note:This item is an abstract only!
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
McLoughlin, P., M. Schiavon, and Y. Kaddoura. 2023. RGB vegetation indices in comparison to NDVI to evaluate the performance of warm-season turfgrass. Agron. Abr. p. 149767.
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    Last checked: 12/01/2023
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