REAL‐t1, an Effective Approach for t1‐Noise Suppression in NMR Spectroscopy Based on Resampling Algorithm,Chinese Journal of Chemistry

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REAL‐t1, an Effective Approach for t1‐Noise Suppression in NMR Spectroscopy Based on Resampling Algorithm
Chinese Journal of Chemistry ( IF 5.5 ) Pub Date : 2019-12-03 , DOI: 10.1002/cjoc.201900389
Linhong Song _{1,

2} , Jiannan Wang _{1,

2} , Xuncheng Su ₃ , Xu Zhang _{1,

2} , Conggang Li _{1,

2} , Xin Zhou _{1,

2} , Daiwen Yang ₄ , Bin Jiang _{1,

2} , Maili Liu _{1,

2}

Affiliation

In multidimensional (nD) NMR spectroscopy, t₁ noise usually appears as ridges along indirect dimensions, and affects observation of weak signals. The main source of t₁ noise is instrumental instability, which causes random variation of FID amplitude during data acquisitions and introduces random noise‐like peaks into spectrum after Fourier transformation. A number of efforts have been devoted, in order to develop new method or to improve existing approaches for suppressing t₁ noise. Herein, we propose a novel t₁ noise suppression method based on resampling algorithm for data processing, shortened as REAL‐t₁. The method was verified using simulated 2D spectra, and NOESY spectra of sucrose and protein GB1, showing that the spectral quality was improved in all cases. The performance of REAL‐t₁ was also compared with another recently proposed method, which showed that these two methods provided similar performance while REAL‐t₁ cost much shorter experimental time.

中文翻译：

REAL‐t1，一种基于重采样算法的NMR光谱中t1噪声抑制的有效方法

在多维（n D）NMR光谱中，t ₁噪声通常沿间接维以脊状出现，并影响微弱信号的观察。t ₁噪声的主要来源是仪器的不稳定性，它导致数据采集过程中FID振幅的随机变化，并在傅立叶变换后将类似随机噪声的峰值引入频谱。为了开发新的方法或改进现有的用于抑制t ₁噪声的方法，已经进行了许多努力。本文中，我们提出了一种基于重采样算法的t ₁噪声抑制方法，用于数据处理，简称为REAL‐ t ₁。使用模拟的2D光谱和蔗糖和蛋白质GB1的NOESY光谱对方法进行了验证，表明在所有情况下光谱质量均得到改善。的现实性能吨₁也与另一个最近提出的方法，这表明，这两种方法提供了类似的性能，而实相比吨₁成本短得多实验时间。

更新日期：2019-12-03

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