2025-08-28 中国科学院（CAS）
The flowchart of LeafPoseNet-based flag leaf angle phenotyping in wheat. (Image by IGDB)
＜関連情報＞
- https://english.cas.cn/newsroom/research_news/life/202508/t20250828_1051636.shtml
- https://www.sciencedirect.com/science/article/pii/S2214514125001734
LeafPoseNet：小麦の旗葉角度を推定する低コスト・高精度手法 LeafPoseNet: A low-cost, high-accuracy method for estimating flag leaf angle in wheat
Qi Wang, Fujun Sun, Yi Qiao, Zongyang Li, Shusong Zheng, Hong-Qing Ling, Ni Jiang
The Crop Journal Available online: 25 July 2025
DOI:https://doi.org/10.1016/j.cj.2025.07.002
Abstract
Flag leaf angle (FLANG) is one of the key traits in wheat breeding due to its impact on plant architecture, light interception, and yield potential. An image-based method of measuring FLANG in wheat would reduce the labor and error of manual measurement of this trait. We describe a method for acquiring in-field FLANG images and a lightweight deep learning model named LeafPoseNet that incorporates a spatial attention mechanism for FLANG estimation. In a test dataset with wheat varieties exhibiting diverse FLANG, LeafPoseNet achieved high accuracy in predicting the FLANG, with a mean absolute error (MAE) of 1.75°, a root mean square error (RMSE) of 2.17°, and a coefficient of determination (R2) of 0.998, significantly outperforming established models such as YOLO12x-pose, YOLO11x-pose, HigherHRNet, Lightweight-OpenPose, and LitePose. We performed phenotyping and genome-wide association study to identify the genomic regions associated with FLANG in a panel of 221 diverse bread wheat genotypes, and identified 10 quantitative trait loci. Among them, qFLANG2B.2 was found to harbor a potential causal gene, TraesCS2B01G313700, which may regulate FLANG formation by modulating brassinosteroid levels. This method provides a low-cost, high-accuracy solution for in-field phenotyping of wheat FLANG, facilitating both wheat FLANG genetic studies and ideal plant type breeding.
