The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Identifying target traits and molecular mechanisms for wheat breeding under a changing climate
Open accessAbstract
Global warming is causing changes in temperature at a rate unmatched by any temperature change over the last 50 million years. Crop cultivars have been selected for optimal performance under the current climatic conditions. With global warming, characterized by shifts in weather patterns and increases in frequency and magnitude of extreme weather events, new ideotypes will be required with a different set of physiological traits. Severe pressure has been placed on breeders to produce new crop cultivars for a future, rapidly-changing environment that can only be predicted with a great degree of uncertainty and is not available in the present day for direct experiments or field trials. Mathematical modelling, therefore, in conjunction with crop genetics, represents a powerful tool to assist in the breeding process. In this review, drought and high temperature are considered as key stress factors with a high potential impact on crop yield that are associated with global warming, focusing on their effects on wheat. Modelling techniques are described which can help to quantify future threats to wheat growth under climate change and simple component traits that are amenable to genetic analysis are identified. This approach could be used to support breeding programmes for new wheat cultivars suitable for future environments brought about by the changing climate.
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Cites
Trehalose accumulation in rice plants confers high tolerance levels to different abiotic stresses
Garg, A. K., Kim, J.-K., Owens, T. G., Ranwala, A. P., Choi, Y. D., Kochian, L. V., & Wu, R. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.252637799 · Cited by 1,346
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 · cited 1×
“The reported range of genetic variations for flag leaf area under unlimited water and nitrogen supplies is up to 40% (Fischer et al., 1998; Shearman et al., 2005).”
BackgroundQuantitative Trait Loci and Crop Performance under Abiotic Stress: Where Do We Stand?: Table I.
Collins, N. C., Tardieu, F., & Tuberosa, R. (2008) · PLANT PHYSIOLOGY · doi:10.1104/pp.108.118117 · Cited by 559
Models for navigating biological complexity in breeding improved crop plants
Hammer, G., Cooper, M., Tardieu, F., Welch, S., Walsh, B., van Eeuwijk, F., Chapman, S., & Podlich, D. (2006) · Trends in Plant Science · doi:10.1016/j.tplants.2006.10.006 · Cited by 415
Gene-to-phenotype models and complex trait genetics
Cooper, M., Podlich, D. W., & Smith, O. S. (2005) · Australian Journal of Agricultural Research · doi:10.1071/ar05154 · Cited by 104
Tardieu, F., Reymond, M., Muller, B., Granier, C., Simonneau, T., Sadok, W., & Welcker, C. (2005) · Australian Journal of Agricultural Research · doi:10.1071/ar05156 · Cited by 71
Cited by
Physiological, Biochemical, and Molecular Mechanisms of Heat Stress Tolerance in Plants
Hasanuzzaman, M., Nahar, K., Alam, M., Roychowdhury, R., & Fujita, M. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms14059643 · Cited by 2,313
Photosynthesis: response to high temperature stress.
Mathur, S., Agrawal, D., & Jajoo, A. (2014) · Journal of Photochemistry and Photobiology B: Biology · doi:10.1016/j.jphotobiol.2014.01.010 · Cited by 879
The impact of climate change in wheat and barley yields in the Iberian Peninsula
Bento, V. A., Ribeiro, A. F. S., Russo, A., Gouveia, C. M., Cardoso, R. M., & Soares, P. M. M. (2021) · Scientific Reports · doi:10.1038/s41598-021-95014-6 · Cited by 72
Metadata
- Authors
- Semenov, M. A., & Halford, N. G.
- Venue
- Journal of Experimental Botany
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-06-01
- Volume
- 60
- Issue
- 10
- Pages
- 2791-2804
- ISSN
- 0022-0957 (ISSN-L)
- 1460-2431
- OpenAlex
- W2165138654
- Cited by
- 192
- References
- 6
- FWCI
- 14.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
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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.
