Multi-year aboveground data of minirhizotron facilities in Selhausen.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
22 Jun 2024
22 Jun 2024
Historique:
received:
19
02
2024
accepted:
17
06
2024
medline:
23
6
2024
pubmed:
23
6
2024
entrez:
22
6
2024
Statut:
epublish
Résumé
Improved understanding of crops' response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO
Identifiants
pubmed: 38909019
doi: 10.1038/s41597-024-03535-2
pii: 10.1038/s41597-024-03535-2
doi:
Substances chimiques
Soil
0
Water
059QF0KO0R
Carbon Dioxide
142M471B3J
Types de publication
Journal Article
Dataset
Langues
eng
Sous-ensembles de citation
IM
Pagination
674Subventions
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : DETECT - CRC 1502
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : DETECT - CRC 1502
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : DETECT - CRC 1502
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC-2070 - 375 390732324
Organisme : Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research)
ID : 031B0170B
Informations de copyright
© 2024. The Author(s).
Références
Chaves, M. M., Maroco, J. P. & Pereira, J. S. Understanding plant responses to drought — from genes to whole plant. Funct. Plant Biol. 30, 239–264 (2003).
doi: 10.1071/FP02076
pubmed: 32689007
Lee, E., Felzer, B. S. & Kothavala, Z. Effects of nitrogen limitation on hydrological processes in CLM4-CN. J. Adv. Model. Earth Syst. 5, 741–754 (2013).
doi: 10.1002/jame.20046
Levis, S. et al. Interactive Crop Management in the Community Earth System Model (CESM1): Seasonal influences on land-atmosphere fluxes. J. Clim. 25, 4839–4859 (2012).
doi: 10.1175/JCLI-D-11-00446.1
Novick, K. A. et al. Confronting the water potential information gap. Nat. Geosci. 15, 158–164 (2022).
doi: 10.1038/s41561-022-00909-2
pubmed: 35300262
pmcid: 8923290
Kannenberg, S. et al. Opportunities challenges and pitfalls in characterizing plant water‐use strategies. Funct. Ecol. https://doi.org/10.1111/1365-2435.13945 (2021).
Jones, J. W. et al. Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science. Agric. Syst. 155, 269–288 (2017).
doi: 10.1016/j.agsy.2016.09.021
pubmed: 28701818
pmcid: 5485672
Kennedy, D. et al. Implementing Plant Hydraulics in the Community Land Model, Version 5. J. Adv. Model. Earth Syst. 11, 485–513 (2019).
doi: 10.1029/2018MS001500
Sulis, M. et al. Incorporating a root water uptake model based on the hydraulic architecture approach in terrestrial systems simulations. Agric. For. Meteorol. 269–270, 28–45 (2019).
doi: 10.1016/j.agrformet.2019.01.034
Wang, N., Gao, J. & Zhang, S. Overcompensation or limitation to photosynthesis and root hydraulic conductance altered by rehydration in seedlings of sorghum and maize. Crop J. 5, 337–344 (2017).
doi: 10.1016/j.cj.2017.01.005
Sunita, C., Sinclair, T. R., Messina, C. D. & Cooper, M. Hydraulic conductance of maize hybrids differing in transpiration response to vapor pressure deficit. Crop Sci. 54, 1147–1152 (2014).
doi: 10.2135/cropsci2013.05.0303
Meunier, F. et al. Hydraulic conductivity of soil-grown lupine and maize unbranched roots and maize root-shoot junctions. J. Plant Physiol. 227, 31–44 (2018).
doi: 10.1016/j.jplph.2017.12.019
pubmed: 29395124
Cai, G. et al. Transpiration response to soil drying and vapor pressure deficit is soil texture specific. Plant Soil, https://doi.org/10.1007/s11104-022-05818-2 (2022).
Müllers, Y., Postma, J. A., Poorter, H. & van Dusschoten, D. Stomatal conductance tracks soil-to-leaf hydraulic conductance in faba bean and maize during soil drying. Plant Physiol., https://doi.org/10.1093/plphys/kiac422 (2022).
Poorter, H. et al. Pampered inside, pestered outside? Differences and similarities between plants growing in controlled conditions and in the field. New Phytol. 212, 838–855 (2016).
doi: 10.1111/nph.14243
pubmed: 27783423
Passioura, J. B. The perils of pot experiments. Funct. Plant Biol. 33, 1075–1079 (2006).
doi: 10.1071/FP06223
pubmed: 32689318
Li, H., Testerink, C. & Zhang, Y. How roots and shoots communicate through stressful times. Trends Plant Sci. 26, 940–952 (2021).
doi: 10.1016/j.tplants.2021.03.005
pubmed: 33896687
Tardieu, F. Too many partners in root – shoot signals. Does hydraulics qualify as the only signal that feeds back over time for reliable stomatal. New Phytol. 212, 802–804 (2016).
doi: 10.1111/nph.14292
pubmed: 27874989
Nguyen, T. H. et al. Expansion and evaluation of two coupled root–shoot models in simulating CO2 and H2O fluxes and growth of maize. Vadose Zo. J. 21, 1–31 (2022).
Nguyen, T. H. et al. Comparison of root water uptake models in simulating CO2 and H2O fluxes and growth of wheat. Hydrol. Earth Syst. Sci. 4943–4969, https://doi.org/10.5194/hess-24-4943-2020 (2020).
Nguyen, T. H. et al. Responses of winter wheat and maize to varying soil moisture: From leaf to canopy. Agric. For. Meteorol. 314, 108803 (2022).
doi: 10.1016/j.agrformet.2021.108803
Tardieu, F., Draye, X. & Javaux, M. Root Water Uptake and Ideotypes of the Root System: Whole-Plant Controls Matter. Vadose Zo. J. 16, 0 (2017).
Hochberg, U., Rockwell, F. E., Holbrook, N. M. & Cochard, H. Iso/Anisohydry: A Plant–Environment Interaction Rather Than a Simple Hydraulic Trait. Trends Plant Sci. 23, 112–120 (2018).
doi: 10.1016/j.tplants.2017.11.002
pubmed: 29223922
Vilà-Guerau De Arellano, J. et al. CloudRoots: Integration of advanced instrumental techniques and process modelling of sub-hourly and sub-kilometre land-Atmosphere interactions. Biogeosciences 17, 4375–4404 (2020).
doi: 10.5194/bg-17-4375-2020
Tardieu, F., Simonneau, T. & Muller, B. The Physiological Basis of Drought Tolerance in Crop Plants: A Scenario-Dependent Probabilistic Approach. Annu. Rev. Plant Biol. 69, 733–759 (2018).
doi: 10.1146/annurev-arplant-042817-040218
pubmed: 29553801
Damour, G., Simonneau, T., Cochard, H. & Urban, L. An overview of models of stomatal conductance at the leaf level. Plant, Cell Environ. 33, 1419–1438 (2010).
pubmed: 20545879
Carminati, A. & Javaux, M. Soil Rather Than Xylem Vulnerability Controls Stomatal Response to Drought. Trends Plant Sci. 25, 868–880 (2020).
doi: 10.1016/j.tplants.2020.04.003
pubmed: 32376085
Bartletta, M. K., Klein, T., Jansen, S., Choat, B. & Sack, L. The correlations and sequence of plant stomatal, hydraulic, and wilting responses to drought. Proc. Natl. Acad. Sci. USA 113, 13098–13103 (2016).
doi: 10.1073/pnas.1604088113
Jorda, H. et al. Field scale plant water relation of maize (Zea mays) under drought – impact of root hairs and soil texture. Plant Soil 478, 59–84 (2022).
doi: 10.1007/s11104-022-05685-x
Roman, D. T. et al. The role of isohydric and anisohydric species in determining ecosystem-scale response to severe drought. Oecologia 179, 641–654 (2015).
doi: 10.1007/s00442-015-3380-9
pubmed: 26130023
Langensiepen, M. et al. Quantifying the uncertainties of transpiration calculations with the Penman-Monteith equation under different climate and optimum water supply conditions. Agric. For. Meteorol. 149, 1063–1072 (2009).
doi: 10.1016/j.agrformet.2009.01.001
Kimball, B. A. et al. Simulation of maize evapotranspiration: An inter-comparison among 29 maize models. Agric. For. Meteorol. 271, 264–284 (2019).
doi: 10.1016/j.agrformet.2019.02.037
Seidel, S. J., Barfus, K., Gaiser, T., Nguyen, T. H. & Lazarovitch, N. The influence of climate variability, soil and sowing date on simulation-based crop coefficient curves and irrigation water demand. Agric. Water Manag. 221, 73–83 (2019).
doi: 10.1016/j.agwat.2019.02.007
Jin, X. et al. High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms. IEEE Geosci. Remote Sens. Mag. 9, 200–231 (2021).
doi: 10.1109/MGRS.2020.2998816
Jenal, A. et al. Investigating the potential of a newly developed uav-mounted vnir/swir imaging system for monitoring crop traits—a case study for winter wheat. Remote Sens. 13, (2021).
Yang, R. et al. Validation of leaf area index measurement system based on wireless sensor network. Sci. Rep. 12, 1–13 (2022).
Damm, A. et al. Response times of remote sensing measured sun-induced chlorophyll fluorescence, surface temperature and vegetation indices to evolving soil water limitation in a crop canopy. Remote Sens. Environ. 273, 112957 (2022).
doi: 10.1016/j.rse.2022.112957
Lärm, L. et al. Multi-year belowground data of minirhizotron facilities in Selhausen. Sci. Data 10, 1–15 (2023).
doi: 10.1038/s41597-023-02570-9
Langensiepen, M., Kupisch, M., Wijk, M. T. & Van Ewert, F. Analyzing transient closed chamber effects on canopy gas exchange for optimizing flux calculation timing. Agric. For. Meteorol. 164, 61–70 (2012).
doi: 10.1016/j.agrformet.2012.05.006
Langensiepen, M., Kupisch, M., Graf, A., Schmidt, M. & Ewert, F. Improving the stem heat balance method for determining sap-flow in wheat. Agric. For. Meteorol. 186, 34–42 (2014).
doi: 10.1016/j.agrformet.2013.11.007
IUSS Working Group WRB. World reference base for soil resources 2006. (2006).
Stadler, A. et al. Quantifying the effects of soil variability on crop growth using apparent soil electrical conductivity measurements. Eur. J. Agron. 64, 8–20 (2015).
doi: 10.1016/j.eja.2014.12.004
Dynamax. Dynagage Sap Flow Sensor User Manual. 106 (2005).
Nguyen, T. et al. Multi-year aboveground data of minirhizotron facilities in Selhausen: Aboveground data. TERENO Database, Sci. Data 1–20, https://doi.org/10.34731/1a9s-ax66 (2024).
LI-COR Biosciences, I. Using the LI-6400 / V e r s i o n 6. Components (2012).
Morandage, S. et al. Root architecture development in stony soils. Vadose Zo. J. 1–17, https://doi.org/10.1002/vzj2.20133 (2021).
Bauer, F. M. et al. Development and Validation of a Deep Learning Based Automated Minirhizotron Image Analysis Pipeline. Plant Phenomics 2022, (2022).
Nguyen, T. et al. Responses of field-grown maize to different soil types, water regimes, and contrasting vapor pressure deficit. Vadose Zone Journal, under review. (2023).
Klotzsche, A. et al. Monitoring Soil Water Content Using Time‐Lapse Horizontal Borehole GPR Data at the field-plot. Vadose Zo. J., https://doi.org/10.2136/vzj2019.05.0044 (2019).
Lärm, L. et al. ‘Linking horizontal crosshole GPR variability with root image information of maize crops’ Vadose Zone Journal, under review. (2023).