Literature DB >> 27864758

High-Throughput Scoring of Seed Germination.

Wilco Ligterink1, Henk W M Hilhorst2.   

Abstract

High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very informative as it lacks information about start, rate, and uniformity of germination, which are highly indicative of such traits as dormancy, stress tolerance, and seed longevity. The calculation of cumulative germination curves requires information about germination percentage at various time points. We developed the GERMINATOR package: a simple, highly cost-efficient, and flexible procedure for high-throughput automatic scoring and evaluation of germination that can be implemented without the use of complex robotics. The GERMINATOR package contains three modules: (I) design of experimental setup with various options to replicate and randomize samples; (II) automatic scoring of germination based on the color contrast between the protruding radicle and seed coat on a single image; and (III) curve fitting of cumulative germination data and the extraction, recap, and visualization of the various germination parameters. GERMINATOR is a freely available package that allows the monitoring and analysis of several thousands of germination tests, several times a day by a single person.

Entities:  

Keywords:  Arabidopsis thaliana; Automatic scoring; Curve-fitting; Germination; High-throughput analysis; Image analysis

Mesh:

Year:  2017        PMID: 27864758     DOI: 10.1007/978-1-4939-6469-7_7

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


  1 in total

1.  ScreenSeed as a novel high throughput seed germination phenotyping method.

Authors:  Nicolas Merieux; Pierre Cordier; Marie-Hélène Wagner; Sylvie Ducournau; Sophie Aligon; Dominique Job; Philippe Grappin; Edwin Grappin
Journal:  Sci Rep       Date:  2021-01-14       Impact factor: 4.379

  1 in total

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