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相关概念视频

NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
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¹H NMR Signal Integration: Overview00:58

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The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...
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量化光谱测量误差,以指导预处理方法的选择:关于在多个NIR仪器中对大麻素预测的案例研究.

Jokin Ezenarro1, Daniel Schorn-García2, Marçal Plans3

  • 1Universitat Rovira i Virgili, ChemoSens group, Department of Analytical Chemistry and Organic Chemistry, Campus Sescelades, 43007, Tarragona, (Catalonia), Spain.

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概括

光谱测量错误影响近红外 (NIR) 光谱学准确度,用于大麻素预测. 新型整体错误相关指数 (IECI) 有助于优化预处理,以获得更可靠的结果.

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科学领域:

  • 分析化学 分析化学
  • 频谱学是一种光谱学.
  • 化学测量 化学测量 化学测量

背景情况:

  • 近红外 (NIR) 光谱对于预测化学含量至关重要.
  • 在NIR光谱中测量错误可能会损害预测的准确性.
  • 了解错误结构对于强大的多变量模型至关重要.

研究的目的:

  • 调查用于大麻素预测的NIR光谱中的光谱测量错误.
  • 为了评估不同NIR工具的错误变化.
  • 引入一种用于量化错误相关性和指导预处理的新型指标.

主要方法:

  • 使用NeoSpectra小型化光谱仪的案例研究.
  • 对错误来源,共变率和相关性模式的分析.
  • 开发和应用综合错误相关指数 (IECI).
  • 评估预处理方法对错误相关性和部分最小方程 (PLS) 模型性能的影响.

主要成果:

  • 光谱测量错误显著影响NIR预测的准确性.
  • 该IECI指标有效量化了测量误差相关性.
  • 降低IECI值的预处理方法可以提高PLS模型的性能.
  • 较低的IECI值与简化和更准确的预测模型相关.

结论:

  • 优化基于IECI的预处理提高了NIR光谱学对大麻素确定性的可靠性.
  • IECI为管理各种测量错误提供了一个框架.
  • 这项研究完善了分析化学中的多变量预测建模.