The DOI matches its Crossref record; 97 of the 97 references it cites were found in a registry or an index.
Improving Salinity Tolerance in Cereals
Abstract
Cereals are grown in almost every region of the world and are exposed to a variety of environmental stresses that severely affect their growth and grain yield. Of various abiotic stresses, salinity is one of the more significant threats to cereal crops. To ensure food security, there is a need to adopt strategies to overcome this specific threat. Undoubtedly, plant scientists have been exploiting a variety of approaches to achieve enhanced crop productivity on salt affected soils. Of the various biotic approaches, conventional breeding, marker-assisted selection and genetic engineering to develop salt-tolerant lines/cultivars of cereals all seem plausible. Some success stories have been reported for improvement in salt tolerance of wheat and rice, but are scarce for other cereals. A number of barriers to the development of salt-tolerant cultivars/lines have been identified and include a lack of knowledge about the genetics of crops, their physiological and biochemical behavior, wide variation in environmental conditions, and the complex polygenic nature of the salt tolerance character. This review focuses on how improvements have been made in salt tolerance in cereals through different biotic means, such as conventional breeding, marker assisted selection and genetic engineering.
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Cites
Mechanisms of Salinity Tolerance
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A rice quantitative trait locus for salt tolerance encodes a sodium transporter
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Cited by
Soares, J. C., Santos, C. S., Carvalho, S. M. P., Pintado, M. M., & Vasconcelos, M. W. (2019) · Plant and Soil · doi:10.1007/s11104-019-04229-0 · Cited by 319
Ansari, M., Shekari, F., Mohammadi, M. H., Juhos, K., Végvári, G., & Biró, B. (2019) · Acta Physiologiae Plantarum · doi:10.1007/s11738-019-2988-5 · Cited by 85
Metadata
- Authors
- Shahbaz, M., & Ashraf, M.
- Venue
- Critical Reviews in Plant Sciences
- Publisher
- Informa UK Limited
- Published
- 2013-07-04
- Volume
- 32
- Issue
- 4
- Pages
- 237-249
- ISSN
- 0735-2689 (ISSN-L)
- 1549-7836
- OpenAlex
- W2161608988
- Cited by
- 438
- References
- 97
- FWCI
- 17.20
- Type
- journal article
- Language
- en
- Open access
- closed
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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.