Liu Hai-Jun, Liu Jie, Zhai Zhiwen, Dai Mingqiu, Tian Feng, Wu Yongrui, Tang Jihua, Lu Yanli, Wang Haiyang, Jackson David, Yang Xiaohong, Qin Feng, Xu Mingliang, Fernie Alisdair R, Zhang Zuxin, Yan Jianbing
Yazhouwan National Laboratory, Sanya 572024, China.
National Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China.
Mol Plant. 2025 Feb 3;18(2):313-332. doi: 10.1016/j.molp.2025.01.012. Epub 2025 Jan 17.
Maize, a cornerstone of global food security, has undergone remarkable transformations through breeding, yet further increase in global maize production faces mounting challenges in a changing world. In this Perspective paper, we overview the historical successes of maize breeding that laid the foundation for present opportunities. We examine both the specific and shared breeding goals related to diverse geographies and end-use demands. Achieving these coordinated breeding objectives requires a holistic approach to trait improvement for sustainable agriculture. We discuss cutting-edge solutions, including multi-omics approaches from single-cell analysis to holobionts, smart breeding with advanced technologies and algorithms, and the transformative potential of rational design with synthetic biology approaches. A transition toward a data-driven future is currently underway, with large-scale precision agriculture and autonomous systems poised to revolutionize farming practice. Realizing these futuristic opportunities hinges on collaborative efforts spanning scientific discoveries, technology translations, and socioeconomic considerations in maximizing human and environmental well-being.
玉米作为全球粮食安全的基石，通过育种已发生了显著变革，但在不断变化的世界中，全球玉米产量的进一步提高面临着越来越多的挑战。在这篇观点论文中，我们概述了玉米育种的历史成就，这些成就为当前的机遇奠定了基础。我们研究了与不同地理区域和最终用途需求相关的具体育种目标和共同育种目标。要实现这些协调一致的育种目标，需要采用整体方法来改良性状，以实现可持续农业。我们讨论了前沿解决方案，包括从单细胞分析到全生物的多组学方法、利用先进技术和算法的智能育种，以及合成生物学方法进行理性设计的变革潜力。目前正在向数据驱动的未来过渡，大规模精准农业和自主系统有望彻底改变农业实践。实现这些未来机遇取决于跨科学发现、技术转化以及社会经济考量的协同努力，以最大限度地提高人类福祉和环境福祉。
