Literature DB >> 35895197

High-Throughput Extraction of Seed Traits Using Image Acquisition and Analysis.

Chongyuan Zhang1, Sindhuja Sankaran2.   

Abstract

Seed traits can easily be assessed using image processing tools to evaluate differences in crop variety performances in response to environment and stress. In this chapter, we describe a protocol to measure seed traits that can be applied to crops with small grains, including legume grains with little modification. The imaging processing tool can be applied to process a batch of images without human intervention. The method allows evaluation of geometric and color features, and currently extracts 11 seed traits that include number of seeds, seed area, major axis, minor axis, eccentricity, and mean and standard deviation of reflectance in red, green, and blue channels from seed images. Protocols or methods, including the one described in this chapter, facilitate phenotyping seed traits in a high-throughput and automated manner, which can be applied in plant breeding programs and food processing industry to evaluate seed quality.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Feature extraction; Image processing, Grains; Seed phenotyping

Mesh:

Year:  2022        PMID: 35895197     DOI: 10.1007/978-1-0716-2537-8_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  PlantCV v2: Image analysis software for high-throughput plant phenotyping.

Authors:  Malia A Gehan; Noah Fahlgren; Arash Abbasi; Jeffrey C Berry; Steven T Callen; Leonardo Chavez; Andrew N Doust; Max J Feldman; Kerrigan B Gilbert; John G Hodge; J Steen Hoyer; Andy Lin; Suxing Liu; César Lizárraga; Argelia Lorence; Michael Miller; Eric Platon; Monica Tessman; Tony Sax
Journal:  PeerJ       Date:  2017-12-01       Impact factor: 2.984

2.  Advanced Imaging for Quantitative Evaluation of Aphanomyces Root Rot Resistance in Lentil.

Authors:  Afef Marzougui; Yu Ma; Chongyuan Zhang; Rebecca J McGee; Clarice J Coyne; Dorrie Main; Sindhuja Sankaran
Journal:  Front Plant Sci       Date:  2019-04-16       Impact factor: 5.753

  2 in total

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