Useful Image-Based Techniques for Manual and Automatic Counting Using ImageJ for Horticultural Research
Counts (e.g., number of leaves, fruits, seeds, or plants) are a common type of data gathered in horticultural research. In many instances, using ImageJ can increase the ease and accuracy of gathering count data. When image processing can easily separate objects of interest from the background, auto...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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The University of Florida George A. Smathers Libraries
2021-01-01
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| Series: | EDIS |
| Subjects: | |
| Online Access: | https://ojs.test.flvc.org/edis/article/view/125670 |
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| Summary: | Counts (e.g., number of leaves, fruits, seeds, or plants) are a common type of data gathered in horticultural research. In many instances, using ImageJ can increase the ease and accuracy of gathering count data. When image processing can easily separate objects of interest from the background, automatic counting with ImageJ can eliminate tedious manual counting processes. Furthermore, additional plant growth data, such as leaf area, plant width, and canopy area, can be collected from the same image. The image processing and analysis techniques introduced in this article are easily accessible and simple to use and thus can be adopted not only by researchers, but also by Extension agents and students. This new 10-page publication of the UF/IFAS Horticultural Sciences Department is part of a series introducing various image-based measurements with ImageJ for horticultural research. Written by Lillian Pride and Shinsuke Agehara.
https://edis.ifas.ufl.edu/hs1405
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| ISSN: | 2576-0009 |