Shao Limin, Griffiths Peter R
Department of Chemistry, University of Idaho, Moscow, ID 83844-2343, USA.
Environ Sci Technol. 2007 Oct 15;41(20):7054-9. doi: 10.1021/es062188d.
A technique for automatically correcting the baseline of open-path Fourier transform infrared spectra is described in which the spectra are decomposed into high-frequency (details) and low-frequency (discrete approximations) information using a wavelet transform. After an appropriate number of iterations, n, the discrete approximation simulates the baseline of the spectrum. By setting the nth approximation to zero and reversing this process, the reconstructed signal contains only the high-frequency components in the original signal on a baseline that is approximately flat and at zero absorbance. When small molecules such as NH3 and CH4 are quantified by partial least-squares (PLS) regression, this process decreases the number of eigenvectors required for the analysis by two or three, increasing the ruggedness of the prediction. The baseline that is calculated is approximately the same for spectra measured at resolutions of 1, 2, 4, 8, and 16 cm(-1). Surprisingly, the baseline that is calculated is not totally smooth, with artifacts that are caused by the analyte. The amplitude of the artifacts is directly proportional to the concentration of the analyte, so the accuracy of PLS regression is not degraded.
描述了一种自动校正开放路径傅里叶变换红外光谱基线的技术，其中使用小波变换将光谱分解为高频（细节）和低频（离散近似）信息。经过适当数量的迭代n后，离散近似模拟光谱的基线。通过将第n次近似设置为零并反转此过程，重建信号在近似平坦且吸光度为零的基线上仅包含原始信号中的高频分量。当通过偏最小二乘（PLS）回归对诸如NH3和CH4等小分子进行定量时，此过程将分析所需的特征向量数量减少两到三个，提高了预测的稳定性。对于在1、2、4、8和16 cm(-1)分辨率下测量的光谱，计算出的基线大致相同。令人惊讶的是，计算出的基线并非完全平滑，存在由分析物引起的伪影。伪影的幅度与分析物的浓度成正比，因此PLS回归的准确性不会降低。
