visual-grain-analyzer

Visual Grain Analyzer (VGA) is a user-friendly ImageJ macro, which has utilized ImageJ/or Fiji facilities to provide a simple tool for grain analysis, seed technology, and phenomics studies.

https://github.com/haqueshenas/visual-grain-analyzer

Science Score: 57.0%

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    Found 2 DOI reference(s) in README
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    Low similarity (14.7%) to scientific vocabulary
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Repository

Visual Grain Analyzer (VGA) is a user-friendly ImageJ macro, which has utilized ImageJ/or Fiji facilities to provide a simple tool for grain analysis, seed technology, and phenomics studies.

Basic Info
  • Host: GitHub
  • Owner: haqueshenas
  • License: mit
  • Language: ImageJ Macro
  • Default Branch: main
  • Homepage:
  • Size: 5.96 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 2
Created about 4 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

Visual Grain Analyzer (VGA)

Version 1.0

Visual Grain Analyzer (VGA) is a user-friendly ImageJ macro, which has utilized ImageJ/or Fiji facilities to provide a simple tool for grain analysis, seed technology, and phenomics studies. This macro:

A) Simulates the processing and calculations reported in the manuscript: Haghshenas, A., Emam, Y., & Jafarizadeh, S. (2021). Wheat grain width: A clue for re-exploring visual indicators of grain weight. bioRxiv, 2021.2010.2013.464205. https://doi.org/10.1101/2021.10.13.464205

In particular, as reported in the paper, VGA provides various estimations of wheat grain weight, based on the image-derived indices.

B) Also, VGA might be used for other phenotyping purposes such as size & shape analyses of grains of other species, leaf area measurement, etc.


How to run?

Important: Choosing higher values of "Resolution Enhancement Factor" could increase the processing time considerably, and also make large output images. Thus, it is highly recommendable that if the input images have high quality, set the enhancement factor to 1 (by default, and only for processing the sample images published with the VGA, it has been set to 10). Besides, this quality enhancement approach cannot be an alternative for acquisition of high-quality images.

For running this user-friendly macro, no scriptwriting or image processing skills are required. Just follow the below steps to process your own images, and extract the quantitative information:

1) Download the free and open-source Fiji (or ImageJ) software from: https://imagej.net/software/fiji/downloads 2) Create two input and output folders, and put your images in the input folder. 3) Open the VGA.ijm macro in the Fiji. For this, you can either drag & drop the file into the Fiji head, or follow: File> Open. 4) In the macro editor, click “Run” (if the Run button is hidden, you can follow Run> Run from the top bar). 5) Follow the successive pop-up dialog windows of the macro, to initiate the processing. After clicking Ok in the last window, status of processing will be displayed on the Log window. Please wait for the message: “Processing completed successfully”. 6) Find the results in the output folder (you have determined the output path previously in the respective pop-up window).

Note:
If you wisht to add the VGA to the Fiji and use it as a pluging, rename the VGA.ijm file to VGA_.ijm. Then copy it to /Fiji.app/plugins directory, and restart Fiji.

Inputs

• RGB images

Outputs

• Single .csv files: include the quantitative results extracted from the individual images

• “Total mean values .csv” file: provides the mean values of all individual .csv files.

• Drawings: various types of drawings represent the visual output of image processing, including segmentation, ellipse fitting, etc.

• Log: general information about processing and settings are saved in this file.

For more detailed information, please see the PDF version of README.


Copyright

MIT license

Copyright <2022>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Owner

  • Name: Abbas Haghshenas
  • Login: haqueshenas
  • Kind: user

PhD in Crop Production

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Haghshenas
    given-names: Abbas
    orcid: 0000-0001-8193-8962
title: "Visual Grain Analyzer"
version: 1.0.1
doi: 10.5281/zenodo.6369128
date-released: 2022-03-18

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