Graduate Program in Agronomy, Federal University of Goiás, Goiânia, Goiás, Brazil.
Brazilian Agricultural Research Corporation (Embrapa Rice and Beans), Santo Antônio de Goiás, Goiás, Brazil.
Sci Data. 2024 Jun 5;11(1):585. doi: 10.1038/s41597-024-03357-2.
Enhancing rapid phenotyping for key plant traits, such as biomass and nitrogen content, is critical for effectively monitoring crop growth and maximizing yield. Studies have explored the relationship between vegetation indices (VIs) and plant traits using drone imagery. However, there is a gap in the literature regarding data availability, accessible datasets. Based on this context, we conducted a systematic review to retrieve relevant data worldwide on the state of the art in drone-based plant trait assessment. The final dataset consists of 41 peer-reviewed papers with 11,189 observations for 11 major crop species distributed across 13 countries. It focuses on the association of plant traits with VIs at different growth/phenological stages. This dataset provides foundational knowledge on the key VIs to focus for phenotyping key plant traits. In addition, future updates to this dataset may include new open datasets. Our goal is to continually update this dataset, encourage collaboration and data inclusion, and thereby facilitate a more rapid advance of phenotyping for critical plant traits to increase yield gains over time.
提高关键植物性状(如生物量和氮含量)的快速表型分析对于有效监测作物生长和最大化产量至关重要。已有研究利用无人机图像探讨了植被指数(VIs)与植物性状之间的关系。然而,在可利用数据、可获取数据集方面,文献中仍存在空白。基于此背景,我们进行了一项系统综述,以检索全球范围内有关基于无人机的植物性状评估最新技术的数据。最终数据集包含 41 篇经过同行评审的论文,涉及 13 个国家的 11 个主要作物物种的 11189 个观测值,重点关注不同生长/物候阶段植物性状与 VIs 的关联。该数据集提供了有关关键 VIs 的基础知识,可用于重点表型分析关键植物性状。此外,未来可能会将新的公开数据集添加到此数据集中。我们的目标是不断更新该数据集,鼓励合作和数据纳入,从而促进关键植物性状的表型分析快速发展,随着时间的推移提高产量。