Accuracy and bias of methods used for root length measurements in functional root research

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

Functional root traits are becoming a key measure in plant ecology, and root length measurements are needed for the calculation of root traits. Several methods are used to estimate the total root length (TRL) of washed root samples [e.g. modified line intersect (LI) method, WinRHIZOTM and IJ_Rhizo], but no standardized comparison of methods exists. We used a set of digital images of unstained root samples to compare measurements given by the LI method and automated methods provided by WinRHIZOTM and IJ_Rhizo. Linear regression models were used to detect bias. Both linear regression models and the Bland-Altmans` method of differences were used to evaluate the accuracy of eight methods (1 manual, 2 semi-automated and 5 automated) in comparison with a reference method that avoided root detection errors. Length measurements were highly correlated, but did not exactly agree with each other in 11 of 12 method comparisons. All tested methods tended to underestimate the TRL of unstained root samples. The accuracy of WinRHIZOTM was influenced by the thresholding method and the root length density (RLD) in the pictures. For the other methods, no linear relationship was found between accuracy and RLD. With WinRHIZOTM (global thresholding + pixel reclassification; RLD = 1 cm cm-2), the Regent's method and the Tennant's method underestimated the TRL by 7·0 ± 6·2% and 4·7 ± 7·9%, respectively. The LI method gave satisfactory results on average (underestimation: 4·2 ± 6·0%), but our results suggest that it can lead to inaccurate estimations for single images. In IJ_Rhizo, the Kimura method was the best and underestimated the TRL by 5·4 ± 6·1%. Our results showed that care must be taken when comparing measurements acquired with different methods because they can lead to different results. When acquiring root images, we advise to (i) increase the contrast between fine roots and background by staining the roots, and (ii) avoid overlapping roots by not exceeding a RLD of 1 cm cm-2. Under these conditions, good length estimates can be obtained with WinRHIZOTM (global thresholding + pixel reclassification). The Kimura method in IJ_Rhizo can be an alternative to WinRHIZOTM.
Original languageEnglish
JournalMethods in Ecology and Evolution
Volume8
Issue number11
Pages (from-to)1594-1606
Number of pages13
DOIs
Publication statusPublished - 11.2017

    Research areas

  • Ecosystems Research - IJ_Rhizo, Winrhizo TM, Functional ecology, ImageJ, Line intersect method, Root length, Washed root samples

DOI

Recently viewed

Publications

  1. Timing matters: Distinct effects of nitrogen and phosphorus fertilizer application timing on root system architecture responses
  2. Combining SMC and MTPA Using an EKF to estimate parameters and states of an interior PMSM
  3. Design of Reliable Remobilisation Finger Implants with Geometry Elements of a Triple Periodic Minimal Surface Structure via Additive Manufacturing of Silicon Nitride
  4. Enhanced Calculation Procedures for Material and Energy Flow Oriented EMIS
  5. Gamen
  6. The Application of Extended Producer Responsibility in Germany
  7. A Graphic Language for Business Application Systems to Improve Communication Concerning Requirements Specification with the User
  8. "Learning by doing"
  9. Pathways of Data-driven Business Model Design and Realization
  10. Simulation of SARS-CoV-2 pandemic in Germany with ordinary differential equations in MATLAB
  11. Local responses to global technological change.
  12. Finding the Best Match — a Case Study on the (Text‑) Feature and Model Choice in Digital Mental Health Interventions
  13. The role of supervisor support for dealing with customer verbal aggression. Differences between ethnic minority and ethnic majority workers
  14. Sustainable Wireless Sensor Networks for Railway Systems Powered by Energy Harvesting from Vibration
  15. Portuguese part-of-speech tagging with large margin structure learning
  16. As cast microstructures on the mechanical and corrosion behaviour of ZK40 modified with Gd and Nd additions
  17. Corrigendum to ‘Likelihood‐based cointegration tests in heterogeneous panels’
(Larsson R., J. Lyhagen and M. Löthgren, Econometrics Journal, 4, 2001, 109–142)
  18. Mining for critical stock price movements using temporal power laws and integrated autoregressive models
  19. Challenging the status quo of accelerator research: Concluding remarks
  20. A microsystem for growth inhibition test of Enterococcus faecalis based on impedance measurement
  21. CSR
  22. Digital language teaching after COVID-19: what can we learn from the crisis?
  23. Log in and breathe out: cost-effectiveness of internet-based recreation training for better sleep in stressed employees
  24. Do consumers prefer pasture-raised dual-purpose cattle when considering meat products? A hypothetical discrete choice experiment for the case of minced beef
  25. Coupling ordination techniques and GAM to spatially predict vegetation assemblages along a climatic gradient in an ENSO-affected region of extremely high climate variability
  26. A dissociation between two classes of spatial abilities in elementary school children
  27. A Note on Pensions and Firm Performance
  28. Three schools of transformation thinking
  29. Precision Denoising in Medical Imaging via Generative Adversarial Network-Aided Low-Noise Discriminator Technique
  30. Do abundance distributions and species aggregation correctly predict macroecological biodiversity patterns in tropical forests?
  31. How many organic compounds are graph-theoretically nonplanar?
  32. Identifying determinants of teachers' judgment (in)accuracy regarding students' school-related motivations using a Bayesian cross-classified multi-level model