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| DOI: | 10.2135/cropsci2016.04.0285 |
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| Web URL(s): | https://dl.sciencesocieties.org/publications/cs/articles/57/2/550
Last checked: 03/03/2017
Access conditions: Item is within a limited-access website
https://dl.sciencesocieties.org/publications/cs/pdfs/57/2/550
Last checked: 03/03/2017
Requires: PDF Reader
Access conditions: Item is within a limited-access website |
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| Publication Type:
| Refereed |
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| Author(s): | Zhang, Chenxi;
Pinnix, Garland D.;
Zhang, Zheng;
Miller, Grady L.;
Rufty, Thomas W. |
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| Author Affiliation: | C. Zhang, Pinnix, Miller, and Rufty: Dep. of Crop Science, North Carolina State Univ., Raleigh, NC; Z. Zhang: Dep. of Computer Science, North Carolina State Univ., Raleigh, NC |
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| Title: | Evaluation of key methodology for digital image analysis of turfgrass color using open-source software |
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| Section: | European Turfgrass Society Conference
Other records with the "European Turfgrass Society Conference" Section
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| Meeting Info.: | Salgados, Portugal: June 5-8, 2016 |
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| Source: | Crop Science. Vol. 57, No. 2, March/April 2017, p. 550-558. |
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| Publishing Information: | Madison, Wisconsin: Crop Science Society of America |
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| # of Pages: | 9 |
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| Related Web URL: | https://dl.sciencesocieties.org/publications/cs/abstracts/57/2/550
Last checked: 03/08/2017
Notes: Abstract only |
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| Keywords: | TIC Keywords: Agrostis stolonifera; Color evaluation; Festuca arundinacea; Hybrid bermudagrasses; Image analysis; Lolium; Poa pratensis; Software evaluation; Turfgrass quality
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| Trade Names: | ImageJ; SigmaScan Pro |
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| Abstract/Contents: | "Digital image analysis is a frequently used research technique to provide an objective measure of turfgrass color, in addition to the traditional visual rating. A commonly used method relies on commercial software package SigmaScan Pro to quantify mean hue angle, saturation, and brightness values from turf images, and to calculate a dark green color index as the measure of color. To enable turf image analysis to function on an opensource platform, a method was developed within ImageJ to batch process turf images for color parameters. This Java-based ImageJ plugin quantifies hue angle, saturation, and brightness values and calculates a dark green color index. In addition, information on the variability of these color parameters can be simultaneously acquired. This new method was used to quantify color parameters of turf images collected from field plots of tall fescue (Schedonorus arundinacea Shreb. Dumort.), Kentucky bluegrass (Poa pratensis L.), ryegrass (Lolium ssp.), hybrid bermudagrass (Cynodon dactylon (L.) Pers. x C. transvaalensis Burtt-Davy), and creeping bentgrass (Agrostis stolonifera L.). While color parameter values differed little between ImageJ and SigmaScan, the time saved in processing images using ImageJ was considerable. Aside from software, analysis of color parameters acquired from the five turfgrass species indicated that hue angle alone can adequately measure turf color in digital images. Results also demonstrated that, in addition to light source, camera settings should remain fixed during photo capture to avoid introducing errors. The ImageJ plug-in developed in this study is made available at www.turffiles.ncsu.edu." |
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| Language: | English |
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| References: | 21 |
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| Note: | Tables
Graphs |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Zhang, C., G. D. Pinnix, Z. Zhang, G. L. Miller, and T. W. Rufty. 2017. Evaluation of key methodology for digital image analysis of turfgrass color using open-source software. Crop Sci. 57(2):p. 550-558. |
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| DOI: 10.2135/cropsci2016.04.0285 |
| Web URL(s):
https://dl.sciencesocieties.org/publications/cs/articles/57/2/550
Last checked: 03/03/2017
Access conditions: Item is within a limited-access website
https://dl.sciencesocieties.org/publications/cs/pdfs/57/2/550
Last checked: 03/03/2017
Requires: PDF Reader
Access conditions: Item is within a limited-access website |
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MSU catalog number: b2211522a |
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