001     840437
005     20210129231833.0
024 7 _ |a 10.2136/vzj2017.05.0107
|2 doi
024 7 _ |a 2128/16069
|2 Handle
024 7 _ |a WOS:000413428800005
|2 WOS
024 7 _ |a altmetric:25228411
|2 altmetric
037 _ _ |a FZJ-2017-07954
082 _ _ |a 550
100 1 _ |a Tardieu, Francois
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a Root Water Uptake and Ideotypes of the Root System: Whole-Plant Controls Matter
260 _ _ |a Madison, Wis.
|c 2017
|b SSSA
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1512377142_12599
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Simulations of plant water uptake in soil science are based on the interplay between soil and root properties, with an imposed flux or water potential at the stem base. The dialogue between roots and shoots is important in water uptake. The threshold soil water potential for water uptake represents the soil water potential at which stomatal control stops transpiration over 24 h. Measurements show that it has a large variability among species and cultivars. Isohydric plants prevent low leaf water potentials via stomatal control, so their threshold soil water potential is high. Anisohydric plants allow low leaf water potentials, resulting in lower thresholds. These behaviors have a genetic control and can be simulated via whole-plant models. In studied species, the hydraulic conductance in roots and shoots depends on the whole-plant transpiration rate. In particular, there is a “dialogue” between the daily alternations in the transpiration rate and the circadian oscillations in root hydraulic conductance that affect the hydraulic conductance of the rhizosphere, with appreciable consequences on water uptake. Root traits such as length, branching, or depth interact with shoot traits such as leaf area or stomatal control, thereby generating feedbacks. As a consequence, optimum root systems for water uptake at a given time are not always those associated with the best yields. Models that take these whole-plant results into account bring an extra level of complication but are probably indispensable whenever the aim is to optimize root traits in view of improved drought tolerance.
536 _ _ |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
|0 G:(DE-HGF)POF3-255
|c POF3-255
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Draye, Xavier
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Javaux, Mathieu
|0 P:(DE-Juel1)129477
|b 2
773 _ _ |a 10.2136/vzj2017.05.0107
|g Vol. 16, no. 9, p. 0 -
|0 PERI:(DE-600)2088189-7
|n 9
|p
|t Vadose zone journal
|v 16
|y 2017
|x 1539-1663
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/840437/files/vzj-16-9-vzj2017.05.0107.pdf
856 4 _ |y OpenAccess
|x icon
|u https://juser.fz-juelich.de/record/840437/files/vzj-16-9-vzj2017.05.0107.gif?subformat=icon
856 4 _ |y OpenAccess
|x icon-1440
|u https://juser.fz-juelich.de/record/840437/files/vzj-16-9-vzj2017.05.0107.jpg?subformat=icon-1440
856 4 _ |y OpenAccess
|x icon-180
|u https://juser.fz-juelich.de/record/840437/files/vzj-16-9-vzj2017.05.0107.jpg?subformat=icon-180
856 4 _ |y OpenAccess
|x icon-640
|u https://juser.fz-juelich.de/record/840437/files/vzj-16-9-vzj2017.05.0107.jpg?subformat=icon-640
856 4 _ |y OpenAccess
|x pdfa
|u https://juser.fz-juelich.de/record/840437/files/vzj-16-9-vzj2017.05.0107.pdf?subformat=pdfa
909 C O |o oai:juser.fz-juelich.de:840437
|p openaire
|p open_access
|p driver
|p VDB:Earth_Environment
|p VDB
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)129477
913 1 _ |a DE-HGF
|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
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Erde und Umwelt
914 1 _ |y 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0
|0 LIC:(DE-HGF)CCBYNCND4
|2 HGFVOC
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b VADOSE ZONE J : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1060
|2 StatID
|b Current Contents - Agriculture, Biology and Environmental Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
920 1 _ |0 I:(DE-Juel1)IBG-3-20101118
|k IBG-3
|l Agrosphäre
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IBG-3-20101118
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21