Plant and Soil

, Volume 326, Issue 1–2, pp 261–273 | Cite as

DART: a software to analyse root system architecture and development from captured images

  • Jacques Le Bot
  • Valérie Serra
  • José Fabre
  • Xavier Draye
  • Stéphane Adamowicz
  • Loïc Pagès
Regular Article


Image analysis is used in numerous studies of root system architecture (RSA). To date, fully automatic procedures have not been good enough to completely replace alternative manual methods. DART (Data Analysis of Root Tracings) is freeware based on human vision to identify roots, particularly across time-series. Each root is described by a series of ordered links encapsulating specific information and is connected to other roots. The population of links constitutes the RSA. DART creates a comprehensive dataset ready for individual or global analyses and this can display root growth sequences along time. We exemplify here individual tomato root growth response to shortfall in solar radiation and we analyse the global distribution of the inter-root branching distances. DART helps in studying RSA and in producing structured and flexible datasets of individual root growth parameters. It is written in JAVA and relies on manual procedures to minimize the risks of errors and biases in datasets.


Object-oriented computer program Java Digitalization Rhizotron 2D dynamic analysis Length Branching density 



We are grateful to Dr. D. J. Pilbeam (University of Leeds, UK) and Dr. C. Jourdan (CIRAD, France) for their critical reviews and suggestions to improve the manuscript.


  1. Armengaud P, Zambaux K, Hills A, Sulpice R, Pattison RJ, Blatt MR, Amtmann A (2009) EZ-RHIZO: integrated software for the fast and accurate measurement of root system architecture. Plant J 57:945–956. doi: 10.1111/j.1365-313X.2008.03739.x CrossRefPubMedGoogle Scholar
  2. Berntson GM (1997) Topological scaling and plant root system architecture: developmental and functional hierarchies. New Phytol 135:621–634. doi: 10.1046/j.1469-8137.1997.00687.x CrossRefGoogle Scholar
  3. Boukcim H, Pagès L, Mousain D (2006) Local NO3- or NH4+ supply modifies the root system architecture of Cedrus atlantica seedlings grown in a split-root device. J Plant Physiol 163:1293–1304. doi: 10.1016/j.jplph.2005.08.011 CrossRefPubMedGoogle Scholar
  4. Bouma TJ, Nielsen KL, Koutstaal B (2000) Sample preparation and scanning protocol for computerised analysis of root length and diameter. Plant Soil 218:185–196. doi: 10.1023/A:1014905104017 CrossRefGoogle Scholar
  5. Cahn MD, Zobel RW, Bouldin DR (1989) Relationship between root elongation rate and diameter and duration of growth of lateral roots of maize. Plant Soil 119:271–279. doi: 10.1007/BF02370419 CrossRefGoogle Scholar
  6. Cheng W, Coleman DC, Box JE Jr (1991) Measuring root turnover using the minirhizotron technique. Agric Ecosyst Environ 34:261–267. doi: 10.1016/0167-8809(91)90113-C CrossRefGoogle Scholar
  7. Colin-Belgrand M, Joannes H, Dreyer E, Pagès L, suppl (1989) A new data processing system for root growth and ramification analysis: description of methods. Ann Sci For 46:305s–309s. doi: 10.1051/forest:19890570 CrossRefGoogle Scholar
  8. Costa C, Dwyer LM, Hamel C, Muamba DF, Wang XL, Nantais L, Smith DL (2001) Root contrast enhancement for measurement with optical scanner-based image analysis. Can J Botany-Revue Canadienne Botanique 79:23–29. doi: 10.1139/cjb-79-1-23 CrossRefGoogle Scholar
  9. Danjon F, Reubens B (2008) Assessing and analyzing 3D architecture of woody root systems, a review of methods and applications in tree and soil stability, resource acquisition and allocation. Plant Soil 303:1–34. doi: 10.1007/s11104-007-9470-7 CrossRefGoogle Scholar
  10. Devienne-Baret F, Richard-Molard C, Chelle M, Maury O, Ney B (2006) Ara-rhizotron: An effective culture system to study simultaneously root and shoot development of Arabidopsis. Plant Soil 280:253–266. doi: 10.1007/s11104-005-3224-1 CrossRefGoogle Scholar
  11. Fitter AH (1986) The topology and geometry of plant-root systems - influence of watering rate on root-system topology in Trifolium pratense. Ann Bot (Lond) 58:91–101Google Scholar
  12. Fitter AH (1987) An architectural approach to the comparative ecology of plant root systems. New Phytol 106:61–77Google Scholar
  13. Fitter AH, Stickland TR, Harvey ML, Wilson GW (1991) Architectural analysis of plant-root systems. 1. Architectural correlates of exploitation efficiency. New Phytol 118:375–382. doi: 10.1111/j.1469-8137.1991.tb00018.x CrossRefGoogle Scholar
  14. Godin C (2000) Representing and encoding plant architecture: a review. Ann Sci For 57:413–438. doi: 10.1051/forest:2000132 CrossRefGoogle Scholar
  15. Himmelbauer ML, Loiskandl W, Kastanek F (2004) Estimating length, average diameter and surface area of roots using two different Image analyses systems. Plant Soil 260:111–120. doi: 10.1023/B:PLSO.0000030171.28821.55 CrossRefGoogle Scholar
  16. Iijima M, Oribe Y, Horibe Y, Kono Y (1998) Time lapse analysis of root elongation rates of rice and sorghum during day and night. Ann Bot (Lond) 81:603–607. doi: 10.1006/anbo.1998.0611 CrossRefGoogle Scholar
  17. Ingram KT, Leers GA (2001) Software for Measuring Root Characters from Digital Images. Agron J 93:918–922CrossRefGoogle Scholar
  18. Johnson MG, Tingey DT, Phillips DL, Storm MJ (2001) Advancing fine root research with minirhizotrons. Environ Exp Bot 45:263–289. doi: 10.1016/S0098-8472(01)00077-6 CrossRefPubMedGoogle Scholar
  19. Kimura K, Kikuchi S, Yamasaki S (1999) Accurate root length measurement by image analysis. Plant Soil 216:117–127. doi: 10.1023/A:1004778925316 CrossRefGoogle Scholar
  20. Lecompte F, Pagès L (2007) Apical diameter and branching density affect lateral root elongation rates in banana. Environ Exp Bot 59:243–251. doi: 10.1016/j.envexpbot.2006.01.002 CrossRefGoogle Scholar
  21. McCrady RL, Comerford NB (1998) Morphological and anatomical relationships of loblolly pine fine roots. Trees-Structure Funct 12:431–437Google Scholar
  22. Ortiz-Ribbing LM, Eastburn DM (2003) Evaluation of digital image acquisition methods for determining soybean root characteristics. Crop Management, 1-9Google Scholar
  23. Pagès L (1995) Growth-patterns of the lateral roots of young oak (Quercus robur) tree seedlings - Relationship with apical diameter. New Phytol 130:503–509. doi: 10.1111/j.1469-8137.1995.tb04327.x CrossRefGoogle Scholar
  24. Pagès L, Bengough AG (1997) Modelling minirhizotron observations to test experimental procedures. Plant Soil 189:81–89. doi: 10.1023/A:1004288430467 CrossRefGoogle Scholar
  25. Pagès L, Vercambre G, Drouet JL, Lecompte F, Collet C, Le Bot J (2004) Root Typ: a generic model to depict and analyse the root system architecture. Plant Soil 258:103–119. doi: 10.1023/B:PLSO.0000016540.47134.03 CrossRefGoogle Scholar
  26. Russ JC (1999) The image processing handbook. CRC Press, IEEE Press, Boca Raton, Florida, USA. pp. 771Google Scholar
  27. Ryser P (2006) The mysterious root length. Plant Soil 286:1–6. doi: 10.1007/s11104-006-9096-1 CrossRefGoogle Scholar
  28. Shabala SN, Newman IA (1997) Root nutation modelled by two ion flux-linked growth waves around the root. Physiol Plant 101:770–776. doi: 10.1111/j.1399-3054.1997.tb01062.x CrossRefGoogle Scholar
  29. Smit AL, Zuin A (1996) Root growth dynamics of Brussels sprouts (Brassica olearacea var gemmifera) and leeks (Allium porrum L) as reflected by root length, root colour and UV fluorescence. Plant Soil 185:271–280. doi: 10.1007/BF02257533 CrossRefGoogle Scholar
  30. Smit AL, Bengough AG, Engels C, van Noordwijk M, Pellerin S, van de Geijn SC (2000) Root methods: a handbook. Springer-Verlag, Berlin, Heidelberg, New York, London, Paris, Tokyo, Hong Kong, p 587Google Scholar
  31. Taub DR, Goldberg D (1996) Root system topology of plants from habitats differing in soil resource availability. Funct Ecol 10:258–264. doi: 10.2307/2389851 CrossRefGoogle Scholar
  32. Vamerali T, Ganis A, Bona S, Mosca G (1999) An approach to minirhizotron root image analysis. Plant Soil 217:183–193. doi: 10.1023/A:1004616217070 CrossRefGoogle Scholar
  33. Vamerali T, Guarise M, Ganis A, Bona S, Mosca G (2003) Analysis of root images from auger sampling with a fast procedure: a case of application to sugar beet. Plant Soil 255:387–397. doi: 10.1023/A:1026147607879 CrossRefGoogle Scholar
  34. Walter A, Spies H, Terjung S, Küsters R, Kirchgebner N, Schurr U (2002) Spatio-temporal dynamics of expansion growth in roots: automatic quantification of diurnal course and temperature response by digital image sequence processing. J Exp Bot 53:689–698. doi: 10.1093/jexbot/53.369.689 CrossRefPubMedGoogle Scholar
  35. Zeng G, Birchfield ST, Wells CE (2008) Automatic discrimination of fine roots in minirhizotron images. New Phytol 177:549–557PubMedGoogle Scholar
  36. Zobel RW (2003) Sensitivity analysis of computer-based diameter measurement from digital images. Crop Sci 43:583–591Google Scholar
  37. Zobel RW (2008) Hardware and software efficacy in assessment of fine root diameter distributions. Comput Electron Agric 60:178–189CrossRefGoogle Scholar
  38. Zobel RW, Kinraide TB, Baligar VC (2007) Fine root diameters can change in response to changes in nutrient concentrations. Plant Soil 297:243–254CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Jacques Le Bot
    • 1
  • Valérie Serra
    • 1
  • José Fabre
    • 1
  • Xavier Draye
    • 2
  • Stéphane Adamowicz
    • 1
  • Loïc Pagès
    • 1
  1. 1.INRA, UR 1115 Plantes et Systèmes de culture HorticolesAvignonFrance
  2. 2.Unité d’écophysiologie et d’amélioration végétale (AGRO/BAPA/ECAV), Faculté d’ingénierie biologique, agronomique et environnementaleUniversité catholique de LouvainLouvain-la-NeuveBelgique

Personalised recommendations