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相关概念视频

Olfaction01:25

Olfaction

44.2K
The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
The olfactory receptors are embedded in the cilia of the...
44.2K
Physiology of Smell and Olfactory Pathway01:20

Physiology of Smell and Olfactory Pathway

8.1K
Humans detect odors with the help of specialized cells located in the upper part of the nasal cavity, called olfactory receptor neurons (ORNs). ORNs possess hair-like structures called cilia, which are receptive to sensations from the inhaled air. When an odorant molecule binds to a specific receptor on the cell of the cilia, it leads to a series of events that ultimately cause the ORN to send electrical signals to the olfactory bulb in the brain through the olfactory nerves.
The olfactory...
8.1K

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相关实验视频

Updated: Jun 10, 2025

Fruit Volatile Analysis Using an Electronic Nose
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Fruit Volatile Analysis Using an Electronic Nose

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用CelluMOFs制成的嗅觉可视化传感阵列,使用深度学习来预测水果成熟度.

Mingming Zhao1,2, Huizi Lu1,2, Zhiheng You1,2

  • 1School of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, P. R. China.

ACS applied materials & interfaces
|October 15, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了一种新的人工气味系统,使用灵活的染料/CelluMOFs传感器阵列和DenseNet来准确检测水果成熟度. 该系统在识别水果香味指纹和预测成熟度水平方面达到99.09%的准确性.

关键词:
颜值测量传感器阵列的颜色测量.密集连接的卷积网络密集连接的卷积网络果实成熟度分类的果实成熟度分类金属-有机的框架.挥发性有机化合物 挥发性有机化合物

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In vivo Ca2+- Imaging of Mushroom Body Neurons During Olfactory Learning in the Honey Bee
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科学领域:

  • 材料科学 材料科学 材料科学
  • 化学传感器 化学传感器
  • 人工智能的人工智能

背景情况:

  • 开发敏感和准确的人工气味系统来检测水果的成熟度是一项挑战.
  • 现有的方法往往缺乏现场评估所需的灵敏度和模式识别能力.
  • 基于测色仪的系统具有潜力,但需要提高灵敏度和与先进算法的集成.

研究的目的:

  • 构建基于染料/CelluMOFs的灵活传感器阵列,用于高灵敏度检测水果挥发性化合物.
  • 整合一个密集连接的卷积网络 (DenseNet),以准确识别水果气味指纹.
  • 通过嗅觉视觉感知系统来实现果实成熟度的精确分类.

主要方法:

  • 在纸上通过g-cyclodextrin金属有机框架 (g-CD-MOFs) 的现场生长合成CelluMOFs.
  • 制造一种灵活的,多孔的染料/CelluMOFs敏感膜,具有增强的染料负载能力.
  • 将DenseNet模型与色度传感器阵列集成,用于模式识别和分类.
  • 检测特有的水果气味,包括2-hexenal,并评估传感器的稳定性.

主要成果:

  • 与过纸相比,CelluMOFs膜的特定表面积增加了62倍,染料负载能力增加了3倍.
  • 传感器阵列表现出高灵敏度,低气体检测值为2-hexenal (8-1500 ppm).
  • 综合系统在验证集上实现了99.09%的分类准确度,用于果实成熟度预测.

结论:

  • 一个新的,灵活的染料/CelluMOFs传感器阵列与DenseNet相结合,可实现灵敏而准确的水果成熟度检测.
  • 嗅觉视觉传感系统有效地识别独特的气味指纹,用于高精度的水果分类.
  • 这种方法为果实质量的现场,非破坏性评估提供了一个有希望的解决方案.