guest ::
| Home > Publications database > In Situ Root System Architecture Extraction from Magnetic Resonance Imaging for Water Uptake Modeling > print |
| Home > Publications database > In Situ Root System Architecture Extraction from Magnetic Resonance Imaging for Water Uptake Modeling > print |
| 001 | 188024 | ||
| 005 | 20210129215121.0 | ||
| 024 | 7 | _ | |a 10.2136/vzj2012.0019 |2 doi |
| 024 | 7 | _ | |a WOS:000317713300007 |2 WOS |
| 037 | _ | _ | |a FZJ-2015-01510 |
| 082 | _ | _ | |a 550 |
| 100 | 1 | _ | |a Stingaciu, Laura |0 P:(DE-Juel1)129542 |b 0 |e Corresponding Author |u fzj |
| 245 | _ | _ | |a In Situ Root System Architecture Extraction from Magnetic Resonance Imaging for Water Uptake Modeling |
| 260 | _ | _ | |a Madison, Wis. |c 2013 |b SSSA |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1424693550_18025 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a article |2 DRIVER |
| 520 | _ | _ | |a The three-dimensional root system architecture (RSA) of a lupin plant is constructed using two methods, an automated procedure based on a three-dimensional MRI image, and a semi-manual method based a 3D virtual reality system. The two results show some differences in connectivity of root segments, which affects the distributions of root water uptake and xylem pressures.An automated method for root system architecture reconstruction from three-dimensional volume data sets obtained from magnetic resonance imaging (MRI) was developed and validated with a three-dimensional semimanual reconstruction using virtual reality and a two-dimensional reconstruction using SmartRoot. It was tested on the basis of an MRI image of a 25-d-old lupin (Lupinus albus L.) grown in natural sand with a resolution of 0.39 by 0.39 by 1.1 mm. The automated reconstruction algorithm was inspired by methods for blood vessel detection in MRI images. It describes the root system by a hierarchical network of nodes, which are connected by segments of defined length and thickness, and also allows the calculation of root parameter profiles such as root length, surface, and apex density The obtained root system architecture (RSA) varied in number of branches, segments, and connectivity of the segments but did not vary in the average diameter of the segments (0.137 cm for semimanual and 0.143 cm for automatic RSA), total root surface (127 cm2 for semimanual and 124 cm2 for automatic RSA), total root length (293 cm for semimanual and 282 cm for automatic RSA), and total root volume (4.7 cm3 for semimanual and 4.7 cm3 for automatic RSA). The difference in performance of the automated and semimanual reconstructions was checked by using the root system as input for water uptake modeling with the Doussan model. Both systems worked well and allowed for continuous water flow. Slight differences in the connectivity appeared to be leading to locally different water flow velocities, which were 30% smaller for the semimanual method. |
| 536 | _ | _ | |a 246 - Modelling and Monitoring Terrestrial Systems: Methods and Technologies (POF2-246) |0 G:(DE-HGF)POF2-246 |c POF2-246 |f POF II |x 0 |
| 536 | _ | _ | |a 41G - Supercomputer Facility (POF2-41G21) |0 G:(DE-HGF)POF2-41G21 |c POF2-41G21 |f POF II |x 1 |
| 588 | _ | _ | |a Dataset connected to CrossRef, juser.fz-juelich.de |
| 700 | 1 | _ | |a Schulz, Hannes |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Pohlmeier, Andreas |0 P:(DE-Juel1)129521 |b 2 |u fzj |
| 700 | 1 | _ | |a Behnke, Sven |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Zilken, Herwig |0 P:(DE-Juel1)132305 |b 4 |u fzj |
| 700 | 1 | _ | |a Javaux, Mathieu |0 P:(DE-Juel1)129477 |b 5 |u fzj |
| 700 | 1 | _ | |a Vereecken, Harry |0 P:(DE-Juel1)129549 |b 6 |u fzj |
| 773 | _ | _ | |a 10.2136/vzj2012.0019 |g Vol. 0, no. 0, p. 0 - |0 PERI:(DE-600)2088189-7 |n 1 |p 9 |t Vadose zone journal |v 12 |y 2013 |x 1539-1663 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/188024/files/FZJ-2015-01510.pdf |y Restricted |
| 909 | C | O | |o oai:juser.fz-juelich.de:188024 |p VDB |p VDB:Earth_Environment |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)129542 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)129521 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)132305 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)129477 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 6 |6 P:(DE-Juel1)129549 |
| 913 | 2 | _ | |a DE-HGF |b Marine, Küsten- und Polare Systeme |l Terrestrische Umwelt |1 G:(DE-HGF)POF3-250 |0 G:(DE-HGF)POF3-255 |2 G:(DE-HGF)POF3-200 |v Terrestrial Systems: From Observation to Prediction |x 0 |
| 913 | 2 | _ | |a DE-HGF |b Key Technologies |l Supercomputing & Big Data |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 1 |
| 913 | 1 | _ | |a DE-HGF |b Erde und Umwelt |l Terrestrische Umwelt |1 G:(DE-HGF)POF2-240 |0 G:(DE-HGF)POF2-246 |2 G:(DE-HGF)POF2-200 |v Modelling and Monitoring Terrestrial Systems: Methods and Technologies |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
| 913 | 1 | _ | |a DE-HGF |b Schlüsseltechnologien |l Supercomputing |1 G:(DE-HGF)POF2-410 |0 G:(DE-HGF)POF2-41G21 |2 G:(DE-HGF)POF2-400 |v Supercomputer Facility |x 1 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
| 914 | 1 | _ | |y 2014 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Thomson Reuters Master Journal List |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1060 |2 StatID |b Current Contents - Agriculture, Biology and Environmental Sciences |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-3-20101118 |k IBG-3 |l Agrosphäre |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 1 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)IBG-3-20101118 |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|