Department of Analytical Chemistry, University of Valencia, 50th Dr. Moliner, 46100 Burjassot, Spain.
Appl Spectrosc. 2009 Dec;63(12):1363-9. doi: 10.1366/000370209790108914.
This paper describes a partial least squares (PLS) based automatic procedure to correct for changes in the spectral contribution of the solvent or solvent mixtures from solute spectra recorded in these solvents. The procedure was developed for successful on-line Fourier transform infrared (FT-IR) detection in gradient high-performance liquid chromatography (HPLC) separations. It requires a reference FT-IR data set containing all possible combinations of the expected variation in solvent composition. Furthermore, a spectral region (A) in these spectra is required where the solvents show absorption but the analytes do not. This is the case for the system ACN:H(2)O, an often-applied solvent mixture in gradient HPLC, in the spectral region from 2300-2400 cm(-1). By focusing on (A) the developed numerical method selects an appropriate background spectrum from the reference data set, which is then subtracted from the analyte spectra. The method was programmed in Matlab and tested on different isocratic and gradient on-line reversed phase liquid chromatography-Fourier transform infrared spectrometry (LC-FT-IR) data sets. This work describes a successful method to perform eluent correction in on-line coupling of FT-IR spectrometry with gradient LC.
本文描述了一种基于偏最小二乘法（PLS）的自动程序，用于校正溶剂或溶剂混合物的光谱贡献变化，这些变化来自于在这些溶剂中记录的溶质光谱。该程序是为成功进行在线傅里叶变换红外（FT-IR）检测梯度高效液相色谱（HPLC）分离而开发的。它需要一个参考 FT-IR 数据集，其中包含溶剂组成预期变化的所有可能组合。此外，这些光谱中还需要一个光谱区域（A），在该区域中溶剂具有吸收但分析物没有。对于 ACN:H(2)O 系统（梯度 HPLC 中常用的溶剂混合物），在 2300-2400 cm(-1) 的光谱区域中就是这种情况。通过关注（A），开发的数值方法从参考数据集中选择一个合适的背景光谱，然后从分析物光谱中减去该背景光谱。该方法是在 Matlab 中编程并在不同的等度和梯度在线反相液相色谱-傅里叶变换红外光谱（LC-FT-IR）数据集上进行测试的。这项工作描述了一种成功的方法，用于执行在线傅里叶变换红外光谱与梯度 LC 耦合中的洗脱剂校正。
