Hauptseite > Publikationsdatenbank > An evaluation of inexpensive methods for root image acquisition when using rhizotrons > print

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005     20210129230306.0
024 7 _ |a 10.1186/s13007-017-0160-z
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037 _ _ |a FZJ-2017-03169
082 _ _ |a 580
100 1 _ |a Mohamed, Awaz
|0 0000-0002-6130-9496
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245 _ _ |a An evaluation of inexpensive methods for root image acquisition when using rhizotrons
260 _ _ |a London
|c 2017
|b BioMed Central
336 7 _ |a article
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520 _ _ |a 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.
536 _ _ |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
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700 1 _ |a Monnier, Yogan
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700 1 _ |a Mao, Zhun
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700 1 _ |a Lobet, Guillaume
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700 1 _ |a Maeght, Jean-Luc
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700 1 _ |a Ramel, Merlin
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700 1 _ |a Stokes, Alexia
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773 _ _ |a 10.1186/s13007-017-0160-z
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