Journal Article FZJ-2017-03169

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An evaluation of inexpensive methods for root image acquisition when using rhizotrons

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2017
BioMed Central London

Plant methods 13(1), 11 () [10.1186/s13007-017-0160-z]

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Abstract: Background: Belowground processes play an essential role in ecosystem nutrient cycling and the global carbon budget cycle. Quantifying fine root growth is crucial to the understanding of ecosystem structure and function and in predicting how ecosystems respond to climate variability. A better understanding of root system growth is necessary, but choosing the best method of observation is complex, especially in the natural soil environment. Here, we compare five methods of root image acquisition using inexpensive technology that is currently available on the market: flatbed scanner, handheld scanner, manual tracing, a smartphone application scanner and a time-lapse camera. Using the five methods, root elongation rate (RER) was measured for three months, on roots of hybrid walnut (Juglans nigra × Juglans regia L.) in rhizotrons installed in agroforests.ResultsWhen all methods were compared together, there were no significant differences in relative cumulative root length. However, the time-lapse camera and the manual tracing method significantly overestimated the relative mean diameter of roots compared to the three scanning methods. The smartphone scanning application was found to perform best overall when considering image quality and ease of use in the field. The automatic time-lapse camera was useful for measuring RER over several months without any human intervention.ConclusionOur results show that inexpensive scanning and automated methods provide correct measurements of root elongation and length (but not diameter when using the time-lapse camera). These methods are capable of detecting fine roots to a diameter of 0.1 mm and can therefore be selected by the user depending on the data required.

Classification:

Contributing Institute(s):
  1. Agrosphäre (IBG-3)
Research Program(s):
  1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2017
Database coverage:
Medline ; Creative Commons Attribution CC BY 4.0 ; DOAJ ; OpenAccess ; BIOSIS Previews ; Current Contents - Agriculture, Biology and Environmental Sciences ; Current Contents - Life Sciences ; DOAJ Seal ; Ebsco Academic Search ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; SCOPUS ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection
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Dokumenttypen > Aufsätze > Zeitschriftenaufsätze
Institutssammlungen > IBG > IBG-3
Workflowsammlungen > Öffentliche Einträge
Publikationsdatenbank
Open Access

 Datensatz erzeugt am 2017-04-20, letzte Änderung am 2021-01-29


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