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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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The primary organs of vascular plants are roots, stems, and leaves, but these structures can be highly variable, adapted for the specific needs and environment of different plant species.
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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
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Plant Tissues01:18

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Plants are multicellular eukaryotes with tissue systems made of various cell types that carry out specific functions. Different tissues work together to perform a unique function and form an organ. Organs working together form organ systems. Vascular plants have two distinct organ systems: a shoot system and a root system. The shoot system consists of two portions: the vegetative (non-reproductive) parts of the plant, such as the leaves and the stems, and the reproductive parts of the plant,...
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相关实验视频

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LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement
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一个自发的关键点连接算法为叶子植物的骨架化和表型提取.

Zhen Wang1, Xiangnan He1, Yuting Wang1

  • 1Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China.

Frontiers in plant science
|November 10, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的,无需培训的叶子骨架化方法,消除了手动标签和计算成本. 该方法精确地从叶子骨架中提取植物表型,从而实现高效,高通量植物表型.

关键词:
角度差的门值是指缩小曲率的最小化方法关键点连接连接的关键点叶子 骨架化的叶子现型提取 现型提取

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相关实验视频

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科学领域:

  • 植物科学 植物科学
  • 计算机视觉 计算机视觉
  • 计算生物学 计算生物学

背景情况:

  • 叶子表型对于评估植物生长至关重要.
  • 目前用于叶子骨架化的深度学习方法需要广泛的手动标签,长时间的培训时间和预定义的关键点,这阻碍了可扩展性.
  • 需要有效和可扩展的自动化方法来进行叶子骨架和表型提取.

研究的目的:

  • 开发一种没有培训和标签的方法,可以从叶子植物的图像中生成叶子骨.
  • 为了从生成的叶片骨架中精确计算几何植物表型.
  • 为了减少与传统的叶子骨架化方法相关的注释工作和计算开销.

主要方法:

  • 该方法涉及随机种子点生成和自适应关键点连接.
  • 它使用一个角度差的门,用于植物随机的叶形态和规则的叶形态的曲率最小化.
  • 对兰花和玉米图像数据集进行了验证.

主要成果:

  • 该方法在兰花图像上实现了0.12的平均曲率拟合误差和92%的叶子回忆.
  • 从兰花叶骨架中精确提取了五个表型参数.
  • 在玉米上证明了有效的骨架化,表明跨物种适用性.

结论:

  • 没有培训和没有标签的方法显著减少了叶子骨架化对注释和计算的要求.
  • 该方法允许精确的几何表型计算,适用于高通量植物表型.
  • 它在各种叶形态 (随机和正规) 上的有效性突显了它在植物科学研究中的广泛适用性.