Abstract
Background and aims
In order to analyse root system architectures (RSAs) from captured images, a variety of manual (e.g. Data Analysis of Root Tracings, DART), semi-automated and fully automated software packages have been developed. These tools offer complementary approaches to study RSAs and the use of the Root System Markup Language (RSML) to store RSA data makes the comparison of measurements obtained with different (semi-) automated root imaging platforms easier. The throughput of the data analysis process using exported RSA data, however, should benefit greatly from batch analysis in a generic data analysis environment (R software).
Methods
We developed an R package (archiDART) with five functions. It computes global RSA traits, root growth rates, root growth directions and trajectories, and lateral root distribution from DART-generated and/or RSML files. It also has specific plotting functions designed to visualise the dynamics of root system growth.
Results
The results demonstrated the ability of the package’s functions to compute relevant traits for three contrasted RSAs (Brachypodium distachyon [L.] P. Beauv., Hevea brasiliensis Müll. Arg. and Solanum lycopersicum L.).
Conclusions
This work extends the DART software package and other image analysis tools supporting the RSML format, enabling users to easily calculate a number of RSA traits in a generic data analysis environment.
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Acknowledgments
Delory B.M. (Research Fellow) and Lobet G. (Postdoctoral Researcher) are financially supported by the Belgian National Fund for Scientific Research. The authors would like to thank Jacques Le Bot (INRA, Centre PACA, UR 1115 PSH) for providing the vectorized root system of the tomato plant used in this paper, and Pierre Tocquin (University of Liège, PhytoSYSTEMS) and three anonymous reviewers for their helpful comments on the manuscript.
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Delory, B.M., Baudson, C., Brostaux, Y. et al. archiDART: an R package for the automated computation of plant root architectural traits. Plant Soil 398, 351–365 (2016). https://doi.org/10.1007/s11104-015-2673-4
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DOI: https://doi.org/10.1007/s11104-015-2673-4