| 表型检测中用于小麦株型研究的快速三维重建方法 |
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| 引用本文： | 方伟,冯慧,杨万能,刘谦.表型检测中用于小麦株型研究的快速三维重建方法[J].中国农业科技导报,2016,18(2):95-101. |
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| 作者姓名： | 方伟 冯慧 杨万能 刘谦 |
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| 作者单位： | 1.华中科技大学生命科学与技术学院, 武汉光电国家实验室, Britton Chance生物医学光子学研究中心, 武汉 430074,2.华中农业大学工程学院, 武汉 430070 |
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| 基金项目： | 国家863计划项目（2013AA102403）；新世纪优秀人才支持计划（NCET-10-0386）资助。 |
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| 摘 要： | 植物表型自动化检测技术在农业研究和作物育种的过程中发挥了重要作用,但目前受限于二维技术三维特征很难被提取。株型是影响多分蘖作物产量的重要表型特征之一,它包括分蘖数、分蘖角、和茎粗等参数。传统方法中获取这些特征参数需要大量的人工测量,而人工测量具有耗时,主观性强,不准确等缺陷,因此用人工的方法进行大批量的表型分析是不现实的。为了使作物育种研究中株型参数提取实现自动化,提出一种用于高通量植株株型性状参数获取的快速三维重建方法,为了提高重建效率,研究中使用了图形处理单元(GPU)并行处理技术,在统一计算设备架构(CUDA)下进行重建的并行计算,使单株重建时间缩减到10秒左右,适合使用于高通量表型检测平台。
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| 关 键 词： | 3D 体素重建 株型 GPU 高通量 |
A fast 3D Reconstruction for Wheat Plant Architecture Studies in Phenotyping |
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| FANG Wei,FENG Hui,YANG Wan-neng,LIU Qian.A fast 3D Reconstruction for Wheat Plant Architecture Studies in Phenotyping[J].Journal of Agricultural Science and Technology,2016,18(2):95-101. |
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| Authors: | FANG Wei FENG Hui YANG Wan-neng LIU Qian |
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| Institution: | 1.Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics| College of Life Science and Technology, Huazhong University Science and Technology,Wuhan 430074| 2.College of Engineering, Huazhong Agricultural University, Wuhan 430070, China |
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| Abstract: | The automatic detection technology for plant phenotype plays an important role in agricultural reaserch and crop breeding. However, many 3D features cannot be extracted by 2D technology. Plant architecture (PA), including number of tillers, tiller angle and stem diameter, significantly affects the crop yield for many tillering crops. To acquire these characteristics parameters, traditional method needs huge manual labors, time-consuming, subjective and inaccurate. Therefore, it is impractical to perform manual phenotypic analysis. In order to automate PA parameters collection in crop breeding, a fast 3D reconstruction method was proposed to acquire high throughput PA characteristics parameters. To improve the reconstruction efficiency, parallel computing technique was used on a graphics processing unit (GPU). The processing time was approxemately 10 s of per plant on the Compute Unified Device Architecture (CUDA). This methodology was suitable for a high-throughput phenotyp testing platform. |
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| Keywords: | 3D volumetric reconstruction plant architecture GPU high throughput |
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