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Article
License: CC BY NC ND
Data sources: UnpayWall
https://doi.org/10.1101/587329...
Article . 2019 . Peer-reviewed
Data sources: Crossref
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Optimizing root measurements in rhizotrons

Authors: Ytting, NK; Kirkegaard, JA; Thorup-Kristensen, K;

Optimizing root measurements in rhizotrons

Abstract

Abstract Background and Aims The line intersect method is widely used in rhizotron and minirhizotron studies to quantify roots and study cultivar and treatment differences in root growth. We investigated ways to optimize the line intersect method and root depth measurements with respect to data variability and the time spent on counting roots. Methods Root intensity was measured with three different grid patterns and different lengths of counting line on 2 m long transparent tube rhizotrons. Rooting depth was recorded by measuring the depth of the deepest root and by measuring the depth below which 5, 10 and 25 roots were observed. Results For root intensity the coefficient of variation (CV) was reduced 10-50 percentage points for grids that distributed counting lines equally across the measured area compared to using a restricted centralized area. In addition, the CV approached an asymptote of around 40 % when more than 50 root intersections per grid were observed. Further we show that recordings of the deepest root gave the most variance and least difference between means with a p-value of 0.65 for difference between cultivars. In contrast, a significant difference between cultivar rooting depths (p = 0.01) was found when using the depth below which 25 roots were observed. Conclusion We propose the use of grid designs adapted to different root densities to decrease time spent on counting roots at high root intensities, and minimize data variability at low root intensities. Further on rooting depth measurements including more roots may be a more useful parameter statistically to reveal variety or treatment differences in rooting depth.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green