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| DOI: | 10.1002/its2.32 |
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| Web URL(s): | https://onlinelibrary.wiley.com/doi/10.1002/its2.32
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| Publication Type:
| Refereed |
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| Author(s): | Patton, Aaron J.;
Higginbotham, Ross A.;
Law, Quincy D.;
Weisenberger, Daniel V. |
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| Author Affiliation: | Patton, Law, and Weisenberger: Dep. of Horticulture and Landscape Architecture, Purdue Univ., West Lafayette, IN; Higginbotham: Mendoza College of Business, University of Notre Dame, Notre Dame, IN |
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| Title: | Counting dandelion blooms in field plots using an image processing program |
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| Section: | Technology integration in turfgrass management - Short communication
Other records with the "Technology integration in turfgrass management - Short communication" Section
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| Source: | International Turfgrass Society Research Journal. Vol. 14, No. 1, June 2022, p. 390-396. |
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| Publishing Information: | s.l.: International Turfgrass Society |
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| # of Pages: | 7 |
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| Abstract/Contents: | "Digital image analysis provides researchers a method to accurately and efficiently analyze turfgrass parameters including cover, color, disease severity, and more. Opportunities for processing images has increased due to the free and open-source nature of many new programs. We developed a macro (set of macroinstructions) within the open-source software ImageJ that is able to count the number and quantify the percent coverage of dandelion (Taraxacum officinale F.H. Wigg.) blooms in field plot images, which allows for collection of objective data on broadleaf weeds. A particle analysis function in ImageJ was used to distinguish dandelion blooms from other yellow objects (e.g. chlorotic turfgrass leaves) based on their size and circularity. We also explored the use of binary watershed segmentation to separate groupings of dandelion blooms into individual blooms that could be counted. To verify the accuracy of the macro, we analyzed 164 images for the number of dandelion blooms with the macro and regressed data against visual counts of dandelion bloom. The resulting linear regression analysis (visual count vs. macro) had a slope of 1.034 and an R2 value of 0.9795. This macro provides researchers with a rapid and accurate method of determining the number and percent coverage of dandelion blooms in field plots using image analysis." |
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| Language: | English |
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| References: | 15 |
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| See Also: | Original version appears in ASA, CSSA and SSSA International Annual Meetings 2015, p. 95491, R=266972. R=266972 |
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| Note: | TIC-hosted web link available 2 years after publication date.
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Patton, A. J., R. A. Higginbotham, Q. D. Law, and D. V. Weisenberger. 2022. Counting dandelion blooms in field plots using an image processing program. Int. Turfgrass Soc. Res. J. 14(1):p. 390-396. |
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| DOI: 10.1002/its2.32 |
| Web URL(s):
https://onlinelibrary.wiley.com/doi/10.1002/its2.32
Last checked: 08/31/2022
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