Full TGIF Record # 317396
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Web URL(s):https://archive.lib.msu.edu/tic/ressum/2021/2021.pdf#page=174
    Last checked: 04/12/2022
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Author(s):Gaussoin, Roch; Carlson, Michael
Author Affiliation:University of Nebraska-Lincoln
Title:Advancing precision turfgrass management
Section:Integrated turfgrass management
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Ecophysiology: Soil problems
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Source:Mike Davis Program for Advancing Golf Course Management: 2021 Progress Reports. 2021, p. 167-172.
Publishing Information:[New York, New York]: The United States Golf Association Green Section
# of Pages:6
See Also:Other Reports from this USGA research project: 2019-30-700
Note:Previously titled: "Mining GreenKeeper app data to quantify the impact of turf research"
Pictures, color
USGA Summary Points:The relationship among visual quality, growth rate, and NDRE of creeping bentgrass is linear and varies throughout the year. Guided machine learning will be used to create a decision support system tool to determine the rate of nitrogen fertilizer needed to meet visual quality and growth rate goals. Spatial variability of creeping bentgrass fairways were quantified throughout the summer from reflectance measurements to create site-specific management units for precision nutrient management. Variable rate nitrogen fertilizer application based on reflectance thresholds were demonstrated on a working golf course in Lincoln, NE. The NDVI variable rate application reduced variability and nitrogen applied by 30% compared to a constant and NDRE variable rate application methods. Further research is needed to validate the nitrogen fertilizer decision support system and to integrate the models into a user-friendly software for use by golf course superintendents.
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Gaussoin, R., and M. Carlson. 2021. Advancing precision turfgrass management. USGA Turfgrass Environ. Res. Summ. p. 167-172.
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    Last checked: 04/12/2022
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    Notes: Item is within a single large file
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MSU catalog number: b3609415
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