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相关概念视频

Mass Spectrometry: Aromatic Compound Fragmentation01:23

Mass Spectrometry: Aromatic Compound Fragmentation

1.6K
Upon ionization, aromatic compounds generate a molecular ion that is observed as a prominent peak in their mass spectra. For example, the molecular ion peak for benzene appears at a mass-to-charge ratio of 78, while toluene is observed at a mass-to-charge ratio of 92. The molecular ion benzene is highly stable and does not readily undergo further fragmentation due to the significant amount of energy required to disrupt the aromatic stability of the benzene ring. In contrast, the molecular ion...
1.6K
Mass Spectrometry: Aldehyde and Ketone Fragmentation01:09

Mass Spectrometry: Aldehyde and Ketone Fragmentation

3.1K
In mass spectrometry, the fragmentation of aliphatic aldehydes and ketones generally occurs through three key mechanisms: α-cleavage, inductive cleavage, and the McLafferty rearrangement.
3.1K
Mass Spectrometry: Alcohol Fragmentation01:03

Mass Spectrometry: Alcohol Fragmentation

3.3K
Alcohols (R-OH) ionize to lose one non-bonded electron from the oxygen atom, forming molecular ions. Due to their tendency to fragment rapidly, the intensity of the molecular ion peak in the mass spectrum is weak or sometimes absent. The fragmentation patterns for alcohols occur in two ways, i.e. ⍺-cleavage and dehydration. During ⍺-cleavage, the bond at the ⍺-position adjacent to the hydroxyl group cleaves to give a resonance-stabilized cation and a radical. However,...
3.3K
NMR Spectroscopy of Aromatic Compounds01:14

NMR Spectroscopy of Aromatic Compounds

4.5K
Aromatic compounds can be identified or analyzed using proton NMR and carbon‐13 NMR. Typically, aromatic hydrogens or hydrogens directly bonded to the aromatic rings are strongly deshielded by the aromatic ring current. Therefore, they absorb in the range of 6.5–8.0 ppm in proton NMR spectra. For instance, aromatic hydrogens directly bonded to the benzene ring absorb at 7.3 ppm. However, aromatic hydrogens of larger rings absorb farther upfield or downfield than the ideal range.
4.5K
Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

2.9K
The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
One type of fragmentation pattern is the cleavage of a single bond in the molecular ion. The cleavage leads to a radical and a cation. The cleavage can...
2.9K
Molecular Models02:00

Molecular Models

37.9K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
37.9K

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相关实验视频

Updated: Jun 5, 2025

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

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FlavorMiner:一种机器学习平台,可以从结构数据中提取分子风味配置文件.

Fabio Herrera-Rocha1,2, Miguel Fernández-Niño2,3, Jorge Duitama4

  • 1Grupo de Diseño de Productos y Procesos (GDPP), Department of Chemical and Food Engineering, Universidad de los Andes, 111711, Bogotá, Colombia.

Journal of cheminformatics
|December 10, 2024
PubMed
概括

机器学习工具FlavorMiner准确预测食品中的分子风味化合物. 这种方法加快了风味分析,为复杂的食物代谢提供了洞察力,并帮助了食品行业.

关键词:
可可可可可可可可可可可可可可可可可可可可可可可可可可可可可可深度学习是一种深度学习.味道化学 味道化学分子机器学习是指分子机器学习.分子表示的分子表示.

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PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
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PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

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Author Spotlight: Exploring Tea Aroma Using Solvent-Assisted Flavor Evaporation Technique
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Author Spotlight: Exploring Tea Aroma Using Solvent-Assisted Flavor Evaporation Technique

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相关实验视频

Last Updated: Jun 5, 2025

Fruit Volatile Analysis Using an Electronic Nose
11:02

Fruit Volatile Analysis Using an Electronic Nose

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PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
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Author Spotlight: Exploring Tea Aroma Using Solvent-Assisted Flavor Evaporation Technique
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Author Spotlight: Exploring Tea Aroma Using Solvent-Assisted Flavor Evaporation Technique

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科学领域:

  • 食品科学 食品科学 食品科学
  • 计算化学计算化学
  • 生物信息学是一种生物信息学.

背景情况:

  • 消费者对食品的接受主要取决于味道.
  • 在复杂的食物矩阵中识别风味化合物是具有挑战性和昂贵的.
  • 机器学习 (ML) 为预测味道特征提供了一个有希望的替代方案.

研究的目的:

  • 开发和验证FlavorMiner,一种基于ML的多标签预测器,用于分子风味特征.
  • 通过评估算法和表示组合来优化ML方法进行风味预测.
  • 为了解决风味数据集中的类失衡问题.

主要方法:

  • FlavorMiner集成了各种ML算法 (随机森林,K-最近邻居) 与分子描述器 (扩展连接指纹,RDKit).
  • 使用了类平衡策略,包括重新抽样和重量平衡.
  • 模型的性能使用ROC AUC得分进行评估.

主要成果:

  • FlavorMiner的平均ROC AUC得分为0.88,这表明它的预测准确度很高.
  • 随机森林/K-最近邻居与扩展连接指纹/RDKit描述符的组合表现最好.
  • 在减轻阶级不平衡方面,重新抽样策略比权重平衡更有效.

结论:

  • "FlavorMiner"为预测分子风味特征提供了一个准确而高效的方法.
  • 该工具可以分析复杂的食物代谢学数据,例如可可.
  • "FlavorMiner"提供了一种可扩展的解决方案,用于在各种食品中挖掘风味,从而推进食品科学和行业实践.