Full TGIF Record # 305099
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Web URL(s):http://archive.lib.msu.edu/tic/ressum/2018/2018.pdf#page=127
    Last checked: 05/15/2019
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    Notes: Item is within a single large file
Publication Type:
i
Report
Author(s):Wang, Ning; Wu, Yanqi; Moss, Justin; Fontanier, Charles; Fry, Jack; Bremer, Dale
Author Affiliation:Wang, Wu, Moss, and Fontanier: Oklahoma State University; Fry and Bremer: Kansas State University
Title:Smart tools to improve and accelerate the turfgrass evaluation process
Section:Integrated turfgrass management
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Ecophysiology: Grass testing
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Source:Turfgrass and Environmental Research Program: 2018Research Summaries. 2018, p. 119-123.
# of Pages:5
Publishing Information:[New York, New York]: The United States Golf Association Green Section
Keywords:TIC Keywords: Methodology; Software; Species evaluation; Technology; Unmanned aerial vehicles
Language:English
References:0
See Also:Other Reports from this USGA research project: 2017-09-619
Note:Flow chart
Screenshots
Pictures, color
USGA Summary Points:A ground-based platform for turfgrass evaluation was designed and developed, which could easily attached on an off-road vehicle to implement field data acquisition. A human interface was developed for the easy uses during the field operations. An image processing and analysis program was also developed to extract traits of interests. We are currently fine-tune the program. Before the next season comes, we will be ready to conduct field tests with the turfgrass scientists (co-PIs) The UAV-based platform with an RGB camera and a thermal camera was still under constructed. We plan to complete the UAV platform before the end of February 2019 and test it before the next season starts. As we have algorithms developed to process the RGB and thermal images from UAV for another similar project, we will modify them and finalize the data processing algorithms before the next season. The results from the image analysis showed that the green color shades were hard to measure without shade. An alternative design is being developed and will be tested under controlledenvironment conditions in January 2019. Due to an unexpected resign of a graduate student who was assigned to work on this project in May 2018 (move to another university), the progress of this project was affected during the summer 2018. From the end of the August, we reformed the team and made significant progress on the development.
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Wang, N., Y. Wu, J. Moss, C. Fontanier, J. Fry, and D. Bremer. 2018. Smart tools to improve and accelerate the turfgrass evaluation process. USGA Turfgrass Environ. Res. Summ. p. 119-123.
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Web URL(s):
http://archive.lib.msu.edu/tic/ressum/2018/2018.pdf#page=127
    Last checked: 05/15/2019
    Requires: PDF Reader
    Notes: Item is within a single large file
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