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High-Throughput Scoring of Seed Germination

  • Wilco LigterinkEmail author
  • Henk W. M. Hilhorst
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1497)

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.

Key words

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

References

  1. 1.
    Penfield S, King J (2009) Towards a systems biology approach to understanding seed dormancy and germination. Proc R Soc B Biol Sci 276:3561–3569CrossRefGoogle Scholar
  2. 2.
    Ligterink W, Joosen RVL, Hilhorst HWM (2012) Unravelling the complex trait of seed quality: using natural variation through a combination of physiology, genetics and -omics technologies. Seed Sci Res 22:S45–S52CrossRefGoogle Scholar
  3. 3.
    Joosen RVL, Kodde J, Willems LA, Ligterink W, van der Plas LH, Hilhorst HW (2010) Germinator: a software package for high-throughput scoring and curve fitting of Arabidopsis seed germination. Plant J 62:|148–159CrossRefPubMedGoogle Scholar
  4. 4.
    Dell’Aquila A (2009) Digital imaging information technology applied to seed germination testing. A review. Agron Sustain Dev 29:213–221CrossRefGoogle Scholar
  5. 7.
    Wagner M-H, Demilly D, Ducournau S, Dürr C, Léchappé J (2011) Computer vision for monitoring seed germination from dry state to young seedlings. Seed Sci 142:49–51Google Scholar
  6. 8.
    El-Kassaby YA, Moss I, Kolotelo D, Stoehr M (2008) Seed germination: mathematical representation and parameters extraction. Forest Sci 54:220–227Google Scholar
  7. 9.
    Nguyen T-P, Keizer P, van Eeuwijk F, Smeekens S, Bentsink L (2012) Natural variation for seed longevity and seed dormancy are negatively correlated in Arabidopsis thaliana. Plant Physiol 160(4):2083–2092CrossRefPubMedPubMedCentralGoogle Scholar
  8. 10.
    Joosen RVL, Arends D, Willems LAJ, Ligterink W, Jansen RC, Hilhorst HWM (2012) Visualizing the genetic landscape of Arabidopsis seed performance. Plant Physiol 158:570–589CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Wageningen Seed Lab, Laboratory of Plant PhysiologyWageningen UniversityWageningenThe Netherlands

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