The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Toward a “Green Revolution” for Soybean
Open accessAbstract
In the last several decades, benefiting from the 'green revolution', considerable progress has been made on boosting the yield increases in the three staple food crops: rice, wheat, and maize. Soybean (Glycine max) is an important economic crop, which is one of the major sources of plant proteins and oils. However, soybean yield has not been increased significantly compared with the three staple food crops. There is an increasing demand for soybean production nowadays. Owing to the rapid development of crop breeding technologies, it is time to think of a 'green revolution' in soybean. Here, we briefly summarize the history of crop breeding and 'green revolutions' in other crops. We then discuss the possible directions and potential approaches toward achieving a 'green revolution' in soybean. Collectively, we provide views and perspectives on breeding new soybean varieties that may promote soybean production.
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Cites
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Self-citationYield trends are insufficient to double global crop production by 2050
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Meng, A., Luan, B., Zhang, W., Zheng, Y., Guo, B., & Zhang, B. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.132911 · Cited by 51
Tapping into the plasticity of plant architecture for increased stress resilience
Rahmati Ishka, M., & Julkowska, M. (2023) · F1000Research · doi:10.12688/f1000research.140649.1 · Cited by 9
Metadata
- Authors
- Liu, S., Zhang, M., Feng, F., & Tian, Z.
- Venue
- Molecular Plant
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 13
- Issue
- 5
- Pages
- 688-697
- ISSN
- 1674-2052 (ISSN-L)
- OpenAlex
- W3010962528
- Cited by
- 365
- References
- 73
- FWCI
- 23.40
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
