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在模拟智能时代的植物科学
Michiel Stock1, Olivier Pieters2,3, Tom De Swaef3
1KERMIT and Biobix, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium.
Frontiers in plant science
|January 31, 2024
概括
模拟智能为植物和作物科学提供了一种新的方法,集成机械和数据驱动模型. 这种强大的工具可以彻底改变养殖和精准农业,以实现可持续的粮食生产.
科学领域:
- 植物和作物科学 植物和作物科学
- 计算生物学是一种计算生物学.
- 农业技术 农业技术
背景情况:
- 植物和作物科学传统上依赖于机械或统计模型.
- 在整合这些方法用于复杂系统分析方面存在差距.
- 模拟智能成为一个统一的范式.
研究的目的:
- 在植物和作物科学中探索模拟智能的九个动机.
- 突出模拟智能的变革潜力.
- 为了未来的研究,在模拟智能中确定未经探索的领域.
主要方法:
- 模拟智能模式的审查和概念化.
- 动图的应用在各种植物科学问题上,从分子过程到温室控制.
- 讨论现有的和新的模拟情报技术.
主要成果:
- 模拟智能为了解和控制植物和作物系统提供了强大的框架.
- 替代模型和基于代理的建模等动机越来越多地被采用.
- 开放式优化和程序合成等领域需要进一步研究.
结论:
- 模拟智能具有促进植物和作物科学发展的巨大潜力.
- 这种方法可以推动育种和精准农业的创新.
- 采用模拟智能可以促进更可持续的粮食生产.
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