使用数据分析和信息技术转变植物育种:创新,应用和前景方向
Mohammad Muzahidur Rahman Bhuiyan1, Inshad Rahman Noman2, Md Munna Aziz1
1College of Business, Westcliff University, Irvine, CA 92614, USA.
Frontiers in bioscience (Elite edition)
|March 28, 2025
概括
现代植物育种结合了先进的遗传学和数据科学,以实现更快,更精确的作物改进. 这种数据驱动的方法提高了全球粮食安全的产量,弹性和可持续性.
科学领域:
- 农业科学 农业科学
- 遗传学 是一个遗传学.
- 数据科学数据科学数据科学
背景情况:
- 传统的植物育种方法 (大规模选择,杂交) 在精度和效率方面存在局限性.
- 先进的分子技术和数据分析正在彻底改变作物改良.
- 像机器学习和物联网这样的新兴技术提供实时工厂性能洞察力.
研究的目的:
- 审查植物育种从传统到数据驱动方法的演变.
- 突出信息技术 (IT) 和数据分析在现代植物育种中的作用.
- 讨论未来的趋势和跨学科合作的重要性.
主要方法:
- 传统和分子育种技术的审查.
- 数据分析,IT,机器学习,高通量表型化和物联网应用程序的分析.
- 讨论新兴技术,如人工智能 (AI) 和区块链.
主要成果:
- 数据驱动的育种可以精确选择复杂的特征 (产量,抗病能力,耐压力).
- 信息技术和数据分析的整合增强了可持续农业应用 (作物产量,生物强化,气候适应).
- 技术进步有望提高数据的透明度,协作和可预测性.
结论:
- 数据和基于IT的育种对未来的全球粮食安全和可持续粮食生产至关重要.
- 高性能,资源高效的作物是可持续农业愿景的基础.
- 技术整合对于有弹性的粮食系统至关重要,以应对人口增长和气候变化.
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