The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
New phenotyping methods for screening wheat and barley for beneficial responses to water deficit
Open accessAbstract
This review considers stomatal conductance as an indicator of genotypic differences in the growth response to water stress. The benefits of using stomatal conductance are compared with photosynthetic rate and other indicators of genetic variation in water stress tolerance, along with the use of modern phenomics technologies. Various treatments for screening for genetic diversity in response to water deficit in controlled environments are considered. There is no perfect medium: there are pitfalls in using soil in pots, and in using hydroponics with ionic and non-ionic osmotica. Use of mixed salts or NaCl is recommended over non-ionic osmotica. Developments in infrared thermography provide new and feasible screening methods for detecting genetic variation in the stomatal response to water deficit in controlled environments and in the field.
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Cites
Comparative physiology of salt and water stress
Munns, R. (2002) · Plant, Cell & Environment · doi:10.1046/j.0016-8025.2001.00808.x · Cited by 6,331
Self-citationChlorophyll Fluorescence: A Probe of Photosynthesis In Vivo
Baker, N. R. (2008) · Annual Review of Plant Biology · doi:10.1146/annurev.arplant.59.032607.092759 · Cited by 4,639
Baker, N. R. (2004) · Journal of Experimental Botany · doi:10.1093/jxb/erh196 · Cited by 1,638
Tardieu, F. (1998) · Journal of Experimental Botany · doi:10.1093/jexbot/49.suppl_1.419 · Cited by 1,329
Solute Movement in the Soil-Root System
Nye, P. H., Tinker, P. B., & Boast, C. W. (1979) · Soil Science · doi:10.1097/00010694-197904000-00015 · Cited by 975
Fischer, R. A., Rees, D., Sayre, K. D., Lu, Z. ‐., Condon, A. G., & Saavedra, A. L. (1998) · Crop Science · doi:10.2135/cropsci1998.0011183x003800060011x · Cited by 887
Screening methods for salinity tolerance: a case study with tetraploid wheat
Munns, R., & James, R. A. (2003) · Plant and Soil · doi:10.1023/a:1024553303144 · Cited by 829
Self-citationJones, H. G., Serraj, R., Loveys, B. R., Xiong, L., Wheaton, A., & Price, A. H. (2009) · Functional Plant Biology · doi:10.1071/fp09123 · Cited by 577
Self-citationUse of infrared thermography for monitoring stomatal closure in the field: application to grapevine
Jones, H. G. (2002) · Journal of Experimental Botany · doi:10.1093/jxb/erf083 · Cited by 541
Self-citationQuantifying the three main components of salinity tolerance in cereals
RAJENDRAN, K., TESTER, M., & ROY, S. J. (2009) · Plant, Cell & Environment · doi:10.1111/j.1365-3040.2008.01916.x · Cited by 458
Cited by
Remote sensing for agricultural applications: A meta-review
Weiss, M., Jacob, F., & Duveiller, G. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111402 · Cited by 1,877
Field high-throughput phenotyping: the new crop breeding frontier
Araus, J. L., & Cairns, J. E. (2014) · Trends in Plant Science · doi:10.1016/j.tplants.2013.09.008 · Cited by 1,817
Yang, W., Feng, H., Zhang, X., Zhang, J., Doonan, J. H., Batchelor, W. D., Xiong, L., & Yan, J. (2020) · Molecular Plant · doi:10.1016/j.molp.2020.01.008 · Cited by 961
Achieving yield gains in wheat
REYNOLDS, M., FOULKES, J., FURBANK, R., GRIFFITHS, S., KING, J., MURCHIE, E., PARRY, M., & SLAFER, G. (2012) · Plant, Cell & Environment · doi:10.1111/j.1365-3040.2012.02588.x · Cited by 607
Self-citationLow-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: A review
Sankaran, S., Khot, L. R., Espinoza, C. Z., Jarolmasjed, S., Sathuvalli, V. R., Vandemark, G. J., Miklas, P. N., Carter, A. H., Pumphrey, M. O., Knowles, N. R., et al. (2015) · European Journal of Agronomy · doi:10.1016/j.eja.2015.07.004 · Cited by 507
Metadata
- Authors
- Munns, R., James, R. A., Sirault, X. R. R., Furbank, R. T., & Jones, H. G.
- Venue
- Journal of Experimental Botany
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-07-06
- Volume
- 61
- Issue
- 13
- Pages
- 3499-3507
- ISSN
- 0022-0957 (ISSN-L)
- 1460-2431
- OpenAlex
- W2131621476
- Cited by
- 422
- References
- 48
- FWCI
- 30.56
- Type
- journal article
- Language
- en
- Open access
- green
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- Munns, R., James, R. A., Sirault, X. R. R., Furbank, R. T., & Jones, H. G. (2010). New phenotyping methods for screening wheat and barley for beneficial responses to water deficit. Journal of Experimental Botany. https://doi.org/10.1093/jxb/erq199
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
