全球数据集用于评估主要田间作物物种中使用无人机成像评估与有关的植物特征
Diogo Castilho1,2, Danilo Tedesco3, Carlos Hernandez3
1Graduate Program in Agronomy, Federal University of Goiás, Goiânia, Goiás, Brazil. diogocastilho6@hotmail.com.
Scientific data
|June 5, 2024
概括
使用无人机图像的快速植物表型是作物产量的关键. 本综述综合了41项关于植被指数和植物特征研究的数据,确定了加强作物监测和最大限度地提高农业产量的关键工具.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 植物生物学 植物生物学
背景情况:
- 植物特征如生物质和含量的快速表型化对于作物监测和产量最大化至关重要.
- 基于无人机的植被指数 (VIs) 显示出评估植物特征的前景,但可访问的数据集有限.
- 一项系统性审查解决了无人机植物特征评估数据可用性的差距.
研究的目的:
- 系统地审查和综合基于无人机的植物特征评估的全球数据.
- 识别关键植被指数 (VIs),与各种作物种和生长阶段的关键植物特征相关.
- 建立一个基础数据集,以促进快速表型化和提高产量增长.
主要方法:
- 进行了系统的文献审查,以收集基于无人机的植物特征评估的全球数据.
- 从41篇同行评审论文中编制了一个数据集,包括13个国家的11个主要作物物种的11189个观察结果.
- 专注于不同表象阶段的植物特征和VI之间的关系.
主要成果:
- 综合数据集为表型化植物基本特征提供了关键VI的基础知识.
- 在当前数据中确定了11种主要作物种和13个国家.
- 突出了植物特征与VI在不同生长阶段的关联.
结论:
- 建立的数据集为有效的植物表型化提供了对VI的关键见解.
- 未来的更新将包含新的开放数据集,以扩大覆盖范围并促进合作.
- 目标是加速表型化方面的进步,以随着时间的推移提高作物产量.
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