Advertisement

Measuring Plant Root Traits Under Controlled and Field Conditions: Step-by-Step Procedures

  • Benjamin M. DeloryEmail author
  • Emanuela W. A. Weidlich
  • Richard van Duijnen
  • Loïc Pagès
  • Vicky M. Temperton
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1761)

Abstract

In this chapter, we present methods that we routinely use to measure plant root traits in the field and under controlled environmental conditions (using rhizoboxes). We describe procedures to (1) collect, wash, and store root samples, (2) acquire images of washed root samples, and (3) measure root traits using image analysis. In addition, we also describe sampling methods for studying belowground productivity, soil exploration, and root distribution in the first soil layers at the community level (soil coring and ingrowth core method). Because the use of rhizoboxes allows a nondestructive and dynamic measurement of traits hardly accessible in the field, a section of this chapter is devoted to the acquisition and analysis of images of roots growing in rhizoboxes.

Key words

Root traits Phenotyping Rhizobox Soil coring Ingrowth core method Root washing Root staining Image analysis 

Notes

Acknowledgments

We would like to thank Dr. Thomas Niemeyer (Leuphana University, Germany) for its excellent technical support. We are also thankful to Dr. Guillaume Lobet for providing some images used in this book chapter. This research was funded by CNPq Brazil (Ciência Sem Fronteiras Program) with the PhD scholarship of Emanuela W.A. Weidlich, BMBF in Germany for the INPLAMINT PhD project of Richard van Duijnen within the BonaRes soils programme, as well as by the Chair of Ecosystem Functioning and Services, Leuphana University, Lüneburg, Germany.

References

  1. 1.
    Bardgett RD, Mommer L, De Vries FT (2014) Going underground: root traits as drivers of ecosystem processes. Trends Ecol Evol 29:692–699CrossRefPubMedGoogle Scholar
  2. 2.
    Lynch JP (2013) Steep, cheap and deep: an ideotype to optimize water and N acquisition by maize root systems. Ann Bot 112:347–357CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Pagès L (2016) Branching patterns of root systems: comparison of monocotyledonous and dicotyledonous species. Ann Bot 118:1337–1346CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Delory BM, Delaplace P, Fauconnier M-L et al (2016) Root-emitted volatile organic compounds: can they mediate belowground plant-plant interactions? Plant Soil 402:1–26CrossRefGoogle Scholar
  5. 5.
    Mommer L, Kirkegaard J, van Ruijven J (2016) Root–root interactions: towards a rhizosphere framework. Trends Plant Sci 21:209–217CrossRefPubMedGoogle Scholar
  6. 6.
    Lynch J (1995) Root architecture and plant productivity. Plant Physiol 109:7–13CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Faucon M-P, Houben D, Lambers H (2017) Plant functional traits: soil and ecosystem services. Trends Plant Sci 22(5):385–394CrossRefPubMedGoogle Scholar
  8. 8.
    Pérez-Harguindeguy N, Díaz S, Garnier E et al (2013) New handbook for standardized measurement of plant functional traits worldwide. Aust J Bot 61:167–234CrossRefGoogle Scholar
  9. 9.
    Nagel KA, Putz A, Gilmer F et al (2012) GROWSCREEN-Rhizo is a novel phenotyping robot enabling simultaneous measurements of root and shoot growth for plants grown in soil-filled rhizotrons. Funct Plant Biol 39:891–904CrossRefGoogle Scholar
  10. 10.
    Faget M, Nagel KA, Walter A et al (2013) Root-root interactions: extending our perspective to be more inclusive of the range of theories in ecology and agriculture using in-vivo analyses. Ann Bot 112:253–266CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Lobet G, Draye X (2013) Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems. Plant Methods 9:1–10CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Oburger E, Schmidt H (2016) New methods to unravel rhizosphere processes. Trends Plant Sci 21:243–255CrossRefPubMedGoogle Scholar
  13. 13.
    Faget M, Blossfeld S, von Gillhaussen P et al (2013) Disentangling who is who during rhizosphere acidification in root interactions: combining fluorescence with optode techniques. Front Plant Sci 4:1–8CrossRefGoogle Scholar
  14. 14.
    Blossfeld S (2013) Light for the dark side of plant life: planar optodes visualizing rhizosphere processes. Plant Soil 369:29–32CrossRefGoogle Scholar
  15. 15.
    Blossfeld S, Schreiber CM, Liebsch G et al (2013) Quantitative imaging of rhizosphere pH and CO2 dynamics with planar optodes. Ann Bot 112:267–276CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Maeght J, Rewald B, Pierret A et al (2013) How to study deep roots - and why it matters. Front Plant Sci 4:299CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Steingrobe B, Schmid H, Claassen N (2000) The use of the ingrowth core method for measuring root production of arable crops - influence of soil conditions inside the ingrowth core on root growth. J Plant Nutr Soil Sci 163:617–622CrossRefGoogle Scholar
  18. 18.
    Steingrobe B, Schmid H, Gutser R et al (2001) Root production and root mortality of winter wheat grown on sandy and loamy soils in different farming systems. Biol Fertil Soils 33:331–339CrossRefGoogle Scholar
  19. 19.
    Chen S, Lin S, Reinsch T et al (2015) Comparison of ingrowth core and sequential soil core methods for estimating belowground net primary production in grass-clover swards. Grass Forage Sci 71:515–528CrossRefGoogle Scholar
  20. 20.
    Bouma TJ, Nielsen KL, Koutstaal B (2000) Sample preparation and scanning protocol for computerised analysis of root length and diameter. Plant Soil 218:185–196CrossRefGoogle Scholar
  21. 21.
    Delory BM, Weidlich EWA, Meder L et al (2017) Accuracy and bias of methods used for root length measurements in functional root research. Methods Ecol Evol 8(11):1594–1606CrossRefGoogle Scholar
  22. 22.
    Mohamed A, Monnier Y, Mao Z et al (2017) An evaluation of inexpensive methods for root image acquisition when using rhizotrons. Plant Methods 13:11CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Mommer L, Wagemaker CAM, De Kroon H et al (2008) Unravelling below-ground plant distributions: a real-time polymerase chain reaction method for quantifying species proportions in mixed root samples. Mol Ecol Resour 8:947–953CrossRefPubMedGoogle Scholar
  24. 24.
    Lobet G, Draye X, Périlleux C (2013) An online database for plant image analysis software tools. Plant Methods 9:1–7CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Schindelin J, Arganda-carreras I, Frise E et al (2012) Fiji - an open source platform for biological image analysis. Nat Methods 9:676–682CrossRefPubMedGoogle Scholar
  26. 26.
    Lobet G, Pound MP, Diener J et al (2015) Root system markup language: toward an unified root architecture description language. Plant Physiol 167:617–627CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Lobet G, Pagès L, Draye X (2011) A novel image-analysis toolbox enabling quantitative analysis of root system architecture. Plant Physiol 157:29–39CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Pound MP, French AP, Atkinson JA et al (2013) RootNav: navigating images of complex root architectures. Plant Physiol 162:1802–1814CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Diener J, Nacry P, Périn C et al (2013) An automated image-processing pipeline for high-throughput analysis of root architecture in OpenAlea. In: 7th International conference on functional-structural plant models, Saariselkä, Finland, pp. 85–87Google Scholar
  30. 30.
    Leitner D, Felderer B, Vontobel P et al (2014) Recovering root system traits using image analysis exemplified by two-dimensional neutron radiography images of lupine. Plant Physiol 164:24–35CrossRefPubMedGoogle Scholar
  31. 31.
    Mairhofer S, Zappala S, Tracy SR et al (2012) RooTrak: automated recovery of three-dimensional plant root architecture in soil from X-ray microcomputed tomography images using visual tracking. Plant Physiol 158:561–569CrossRefPubMedGoogle Scholar
  32. 32.
    Armengaud P, Zambaux K, Hills A et al (2009) EZ-Rhizo: integrated software for the fast and accurate measurement of root system architecture. Plant J 57:945–956CrossRefPubMedGoogle Scholar
  33. 33.
    Rellán-Álvarez R, Lobet G, Lindner H et al (2015) GLO-roots: an imaging platform enabling multidimensional characterization of soil-grown root systems. elife 4:1–26CrossRefGoogle Scholar
  34. 34.
    Delory BM, Baudson C, Brostaux Y et al (2016) archiDART: an R package for the automated computation of plant root architectural traits. Plant Soil 398:351–365CrossRefGoogle Scholar
  35. 35.
    Le Bot J, Serra V, Fabre J et al (2010) DART: a software to analyse root system architecture and development from captured images. Plant Soil 326:261–273CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2018

Authors and Affiliations

  • Benjamin M. Delory
    • 1
    Email author
  • Emanuela W. A. Weidlich
    • 1
  • Richard van Duijnen
    • 1
  • Loïc Pagès
    • 2
  • Vicky M. Temperton
    • 1
  1. 1.Ecosystem Functioning and Services, Institute of EcologyLeuphana UniversityLüneburgGermany
  2. 2.INRA, Centre PACA, UR 1115 PSHAvignon Cedex 9France

Personalised recommendations