LeafPoseNet: A low-cost, high-accuracy method for estimating flag leaf angle in wheat

में बचाया:
ग्रंथसूची विवरण
में प्रकाशित:Crop Journal vol. 13, no. 5 (Oct 2025), p. 1543-1554
मुख्य लेखक: Wang, Qi
अन्य लेखक: Sun, Fujun, Qiao, Yi, Li, Zongyang, Zheng, Shusong, Ling, Hong-Qing, Jiang, Ni
प्रकाशित:
KeAi Publishing Communications Ltd
विषय:
ऑनलाइन पहुंच:Citation/Abstract
Full Text
Full Text - PDF
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LEADER 00000nab a2200000uu 4500
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022 |a 2095-5421 
022 |a 2214-5141 
024 7 |a 10.1016/j.cj.2025.07.002  |2 doi 
035 |a 3270768460 
045 2 |b d20251001  |b d20251031 
100 1 |a Wang, Qi  |u Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China 
245 1 |a LeafPoseNet: A low-cost, high-accuracy method for estimating flag leaf angle in wheat 
260 |b KeAi Publishing Communications Ltd  |c Oct 2025 
513 |a Journal Article 
520 3 |a 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 (К?) 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. 
651 4 |a China 
653 |a Measurement methods 
653 |a Mean square errors 
653 |a Wheat 
653 |a Interception 
653 |a Population 
653 |a Light interception 
653 |a Accuracy 
653 |a Deep learning 
653 |a Genome-wide association studies 
653 |a Smartphones 
653 |a Quantitative trait loci 
653 |a Plant breeding 
653 |a Leaves 
653 |a Genomes 
653 |a Genotypes 
653 |a Gene mapping 
653 |a Phenotyping 
653 |a Agricultural economics 
653 |a Low cost 
653 |a Leaf angle 
653 |a Root-mean-square errors 
653 |a Cloning 
653 |a Chromosomes 
653 |a Image acquisition 
653 |a Algorithms 
653 |a Cultivars 
653 |a Estimation 
700 1 |a Sun, Fujun  |u Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China 
700 1 |a Qiao, Yi  |u Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China 
700 1 |a Li, Zongyang  |u Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China 
700 1 |a Zheng, Shusong  |u Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China 
700 1 |a Ling, Hong-Qing 
700 1 |a Jiang, Ni 
773 0 |t Crop Journal  |g vol. 13, no. 5 (Oct 2025), p. 1543-1554 
786 0 |d ProQuest  |t Agriculture Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3270768460/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3270768460/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3270768460/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch