Design strategies for enhanced sustainable green revolution productivity in rice.

IF 6.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Shuoxun Wang, Jie Hu, Wenzhen Song, Qiaoling Zhang, Chenchen Wu, Jiangyi Zhou, Lindong Yang, Yunzhe Wu, Yafeng Ye, Weishu Fan, Xiangdong Fu, Kun Wu
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引用次数: 0

Abstract

Modern agriculture relies heavily on resource-intensive and environmentally harmful inputs, while the increasing global population and decreasing arable land demand new strategies to improve sustainable productivity of cereal crops, particularly reducing inorganic nitrogen fertilizer use while simultaneously increasing photosynthesis and grain yield in rice. To improve rice productivity, it is essential to improve photosynthetic nitrogen assimilation and optimize the translocation of carbon and nitrogen products from source to sink tissues. In this review, we first summarize recent advances in the genetic basis for improving grain yield by enhancing photosynthetic carbon and nitrogen assimilation. We then discuss progress in modulating the source-sink relationships to achieve higher yield and improved harvest index. Finally, we explore the necessary optimizations for adapting rice to high-density planting. These advancements are driving the development of sustainable green revolution varieties through the rational design of multi-gene pyramids and artificial intelligence (AI)-driven protein engineering.

提高水稻可持续绿色革命生产力的设计策略。
现代农业严重依赖资源密集型和对环境有害的投入,而全球人口的增加和耕地的减少需要新的战略来提高谷类作物的可持续生产力,特别是减少无机氮肥的使用,同时增加水稻的光合作用和粮食产量。提高水稻产量,必须改善光合氮同化,优化碳氮产物从源组织向汇组织的转运。本文首先综述了通过提高光合作用下碳氮同化提高籽粒产量的遗传基础的研究进展。然后,我们讨论了调制源汇关系以实现更高产量和改善收获指数的进展。最后,探讨了水稻适应高密度种植的必要优化措施。这些进步通过合理设计多基因金字塔和人工智能驱动的蛋白质工程,推动了可持续绿色革命品种的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Genetics and Genomics
Journal of Genetics and Genomics 生物-生化与分子生物学
CiteScore
8.20
自引率
3.40%
发文量
4756
审稿时长
14 days
期刊介绍: The Journal of Genetics and Genomics (JGG, formerly known as Acta Genetica Sinica ) is an international journal publishing peer-reviewed articles of novel and significant discoveries in the fields of genetics and genomics. Topics of particular interest include but are not limited to molecular genetics, developmental genetics, cytogenetics, epigenetics, medical genetics, population and evolutionary genetics, genomics and functional genomics as well as bioinformatics and computational biology.
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