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SeedExtractor: An Open-Source GUI for Seed Image Analysis.

Feiyu Zhu1, Puneet Paul2, Waseem Hussain2

  • 1Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States.

Frontiers in Plant Science
|February 18, 2021
PubMed
Summary
This summary is machine-generated.

SeedExtractor is a new open-source software for accurately measuring seed size and shape. This tool accelerates crop trait discovery by enabling rapid, high-throughput analysis of seed phenotypes.

Keywords:
GWASgenome wide analysisimage analysisriceseed colorseed size

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Area of Science:

  • Plant science
  • Bioinformatics
  • Agricultural technology

Background:

  • Accurate seed size and shape measurements are crucial for crop yield improvement and understanding genetic regulation.
  • Existing methods for seed phenotyping can be time-consuming and lack efficiency for large-scale studies.

Purpose of the Study:

  • To develop and validate an open-source software, SeedExtractor, for high-throughput seed size and shape analysis.
  • To demonstrate the software's adaptability across multiple crops and its utility in genetic studies.

Main Methods:

  • Development of a graphical user interface (GUI) software, SeedExtractor, for automated measurement of seed parameters (area, perimeter, length, width, circularity, centroid) and color.
  • Rapid image analysis with processing time of approximately 2 seconds per image.
  • Validation using scanned seeds from diverse crops and mature rice seeds from 231 accessions.

Main Results:

  • SeedExtractor efficiently processes a large number of images in a time-efficient manner.
  • The software demonstrated adaptability across various crop species.
  • Genome-wide association analysis using SeedExtractor-derived traits in rice identified known seed size regulatory loci (GS3, qSW5/GW5).

Conclusions:

  • SeedExtractor is a publicly available, open-source application for determining key yield-related seed traits.
  • The software accurately extracts seed phenotypes, facilitating accelerated trait discovery in plant breeding and genetics.
  • Its speed and adaptability make it a valuable tool for researchers studying crop improvement.