A global dataset for assessing nitrogen-related plant traits using drone imagery in major field crop species

Abstract

Abstract 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.

Plant phenotyping relevance

ドローン画像と植生指数に基づく作物形質評価研究を体系的に収集・統合したデータセットであり、植物フェノタイピングの再利用可能な資源が中心です。

Code and data availability

The paper's own dataset (Dataset.xlsx with UAV_dataset, sensor info, and quantitative analysis tabs) plus authors' analysis code (R scripts and Jupyter notebook for Figs. 2-4) are publicly deposited on figshare at https://doi.org/10.6084/m9.figshare.22938797.v4.