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相关概念视频

Light Acquisition02:16

Light Acquisition

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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相关实验视频

Updated: Jun 29, 2025

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols
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基于RKM-D点云方法的作物叶表型参数测量.

Weiyi Mu1, Yuanxin Li1, Mingjiang Deng1,2

  • 1School of Water Resources and Hydropower, Xi'an University of Technology, Xi'an 710054, China.

Sensors (Basel, Switzerland)
|March 28, 2024
PubMed
概括
此摘要是机器生成的。

一种新的RKM-D点云方法准确地测量了作物叶子的长度,周长和面积. 这种技术通过克服处理叶点云数据的挑战,改善了作物监测和产量估计.

关键词:
测量方法的测量方法现型参数 现型参数一个点云,一个点云.处理点云的点云处理.

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科学领域:

  • 农业科学 农业科学
  • 计算机视觉 计算机视觉
  • 生物技术是生物技术.

背景情况:

  • 精确测量作物叶子表型参数 (长度,周长,面积) 对于监测生长和估计产量至关重要.
  • 处理叶点云的挑战,包括噪音和不确定性,导致表型参数测量不准确.

研究的目的:

  • 提出并验证RKM-D点云方法,用于精确测量作物叶子表型参数.
  • 为了解决处理复杂的叶点云数据的现有方法的局限性.

主要方法:

  • 通过将随机样本共识与基点移除 (R),K-平均集群 (K),移动最小平方 (M) 和欧几里德距离 (D) 算法集成,开发了RKM-D方法.
  • 使用立体相机捕获的胡叶点云数据跨越了三个生长阶段 (14,28和42天).

主要成果:

  • 在所有测量参数中,RKM-D方法表现出高精度.
  • 叶子长度:R2>0.81,MAE<3.50毫米,MRE<5.93%,RMSE<3.73毫米. 叶子长度:R2>0.81,MAE<3.50毫米,MRE<5.93%,RMSE<3.73毫米. 叶子长度:R2>0.81,MAE<3.50毫米,MRE<5.93%,RMSE<3.73毫米. 叶子长度:R2>0.81,MAE<3.50毫米,MRE<5.93%,RMSE<3.73毫米.
  • 叶子周长:R2>0.82,MAE<7.30毫米,MRE<4.50%,RMSE<8.37毫米. 叶子周长:R2>0.82,MAE<7.30毫米,MRE<4.50%,RMSE<8.37毫米. 叶子周长:R2>0.82,MAE<7.30毫米,MRE<4.50%,RMSE<8.37毫米. 叶子周长:R2>0.82,MAE<7.30毫米,MRE<4.50%,RMSE<8.37毫米.
  • 叶面积:R2 > 0.97,MAE < 64.66 毫米2,MRE < 4.96%,RMSE < 73.06 毫米2.

结论:

  • RKM-D点云方法为测量作物叶子表型参数提供了强大而准确的解决方案.
  • 该方法通过精确的表型数据采集,提高了作物监测和产量估计的可靠性.