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Microbial Growth Measurement: Indirect Methods01:27

Microbial Growth Measurement: Indirect Methods

Estimating microbial growth is essential for understanding population dynamics and environmental adaptations. Indirect methods provide valuable insights by measuring parameters such as turbidity, metabolic activity, and biomass, enabling efficient and reproducible assessments.During exponential growth, microbial cells scatter light proportionally to their biomass, a principle used in turbidity measurements. About one million cells per milliliter produce detectable scattering, which a...

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相关实验视频

Updated: Jun 21, 2026

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
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用低成本视觉系统监测海藻生长

Jeroen Gerlo1, Dennis G Kooijman2, Ivo W Wieling3

  • 1InViLab Research Group, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种使用RGB和立体相机的自动水下海藻生长监测系统. 该方法准确地测量了垂直养殖场的海藻大小,即使在可见度低的条件下.

关键词:
水产养殖的水产养殖图像分割 图像细分 图像细分海藻的监测和监测水下立体声成像系统的水下立体声成像

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相关实验视频

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科学领域:

  • 海洋生物学 海洋生物学
  • 农业技术 农业技术
  • 计算机视觉 计算机视觉 计算机视觉

背景情况:

  • 目前的海藻监测依赖于手动或实验室方法.
  • 垂直海藻养殖场的水下监测由于可见性而具有挑战性.
  • 需要自动化系统来实现高效和可扩展的海藻种植.

研究的目的:

  • 开发和验证用于监测海藻生长的自动化水下系统.
  • 为此目的评估使用低成本RGB和立体视觉的可行性.
  • 在垂直农场环境中定量海藻尺寸.

主要方法:

  • 组合低成本的RGB和立体视觉摄像机用于水下成像.
  • 使用深度学习 (DeeplabV3+) 进行基于像素的海藻细分.
  • 利用立体视觉数据将像素测量转换为现实世界尺寸 (m2).

主要成果:

  • 尽管水下可见性差,但实现了高细分精度 (IoU为0.9).
  • 对于海藻大小测量,证明了6%的重复性.
  • 在确定海藻大小时,报告了18%的精度.

结论:

  • 开发的系统为自动化水下海藻生长监测提供了可行的解决方案.
  • 该方法有望提高海藻养殖的效率和可扩展性.
  • 进一步精制可以提高在具有挑战性的水生环境中的精度.