Full TGIF Record # 249162
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DOI:10.2134/agronj14.0088
Web URL(s):https://dl.sciencesocieties.org/publications/aj/pdfs/106/5/1787
    Last checked: 11/04/2016
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https://dl.sciencesocieties.org/publications/aj/articles/106/5/1787
    Last checked: 11/02/2016
    Access conditions: Item is within a limited-access website
Publication Type:
i
Refereed
Author(s):Leinauer, Bernd; VanLeeuwen, Dawn M.; Serena, Matteo; Schiavon, Marco; Sevostianova, Elena
Author Affiliation:Leinauer, Serena, and Sevostianova: Dep. of Extension Plant Sciences; VanLeeuwen: Dep. of Economics, Applied Statistics, and International Business/Agricultural Biometric Service, New Mexico State Univ., Las Cruces, NM; Schiavon: Dep. of Botany & Plant Sciences, Univ. of California-Riverside, Riverside, CA
Title:Digital image analysis and spectral reflectance to determine turfgrass quality
Section:Agronomy, soils & environmental quality
Other records with the "Agronomy, soils & environmental quality" Section
Source:Agronomy Journal. Vol. 106, No. 5, September/October 2014, p. 1787-1794.
Publishing Information:Madison, Wisconsin: American Society of Agronomy
# of Pages:8
Related Web URL:https://dl.sciencesocieties.org/publications/aj/abstracts/106/5/1787
    Last checked: 11/02/2016
    Access conditions: Item is within a limited-access website
    Notes: Abstract only
https://dl.sciencesocieties.org/publications/aj/articles/106/5/1787?show-t-f=tables&wrapper=no
    Last checked: 11/30/2016
    Notes: Tables only
Keywords:TIC Keywords: Color evaluation; Evaluative methods; Image analysis; Normalized Difference Vegetation Index; Turfgrass quality; Visual evaluation
Abstract/Contents:"The limitations of the conventional visual rating system used to assess turfgrass quality include its subjective nature and the need for properly trained observers who can discern differences among treatments or turfgrass varieties. The objective of our study was to investigate if digital image analysis (DIA) and spectral reflectance [normalized difference vegetative index (NDVI)] can be used to evaluate turfgrass varieties. Trials were established at New Mexico State University and visual quality ratings, digital images, and NDVI were collected monthly on three warm-season and three cool-season variety trials and on one cool-season and one warm-season mixed species trial. Correlations among quality, NDVI, dark green color index (DGCI) and percent green cover (PCov) were computed. Multiple regression was used to determine if combining NDVI and DIA improved the association between visual turfgrass quality and other variables. Quality was most strongly associated with NDVI (R2 ranging from 0.37 to 0.65) for most datasets. Additionally, multiple linear regressions identified NDVI as the variable affecting a higher change in R2 when entered to the model than either DGCI or PCov. Visual quality had a weaker association with sampling date than did NDVI or DGCI, which indicates that NDVI may track quality changes more reliably over time. However, a stronger association between variety and visual quality than between variety and NDVI or DGCI indicates that a visual assessment detects varietal differences better. Therefore, it is questionable whether visual assessments can be replaced by NDVI or DIA to characterize the aesthetic appeal of turfgrasses accurately."
Language:English
References:26
See Also:See also related article "I see you doing that" Golf Course Management, 83(3) March 2015, p. 98, R=256294. R=256294
Note:Equations
Tables
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Leinauer, B., D. M. VanLeeuwen, M. Serena, M. Schiavon, and E. Sevostianova. 2014. Digital image analysis and spectral reflectance to determine turfgrass quality. Agron. J. 106(5):p. 1787-1794.
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DOI: 10.2134/agronj14.0088
Web URL(s):
https://dl.sciencesocieties.org/publications/aj/pdfs/106/5/1787
    Last checked: 11/04/2016
    Requires: PDF Reader
    Access conditions: Item is within a limited-access website
https://dl.sciencesocieties.org/publications/aj/articles/106/5/1787
    Last checked: 11/02/2016
    Access conditions: Item is within a limited-access website
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