Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, PR China.
Appl Spectrosc. 2011 Jul;65(7):820-4. doi: 10.1366/11-06265.
The use of multiple calibration sets in partial least squares (PLS) regression was proposed to improve the quantitative determination of NH(3) over wide concentration ranges from open-path Fourier transform infrared (OP/FT-IR) spectra. The spectra were measured near animal farms, where the path-integrated concentration of NH(3) can fluctuate from nearly zero to as high as approximately 1000 ppm-m. PLS regression with a single calibration set did not cover such a large concentration range effectively, and the quantitative accuracy was degraded due to the nonlinear relationship between concentration and absorbance for spectra measured at low resolution (1 cm(-1) and poorer.) In PLS regression with multiple calibration sets, each calibration set covers a part of the entire concentration range, which significantly decreases the serious nonlinearity problem in PLS regression occurring when only a single calibration set is used. The relative error was reduced from approximately 6% to below 2%, and the best results were obtained with four calibration sets, each covering one quarter of the entire concentration range. It was also found that it was possible to build the multiple calibration sets easily and efficiently without extra measurements.
使用多个校准集在偏最小二乘法（PLS）回归中被提出，以改善从开路傅里叶变换红外（OP / FT-IR）光谱宽浓度范围内定量测定 NH（3）。该光谱是在动物养殖场附近测量的，其中 NH（3）的路径积分浓度可以从几乎为零波动到高达约 1000 ppm-m。单一校准集的 PLS 回归不能有效地覆盖如此大的浓度范围，并且由于在低分辨率（1 cm（-1）和较差的情况下测量的光谱的浓度与吸光度之间的非线性关系，定量精度降低。在具有多个校准集的 PLS 回归中，每个校准集覆盖整个浓度范围的一部分，这大大降低了当仅使用单个校准集时在 PLS 回归中发生的严重非线性问题。相对误差从大约 6％降低到 2％以下，并且使用四个校准集获得了最佳结果，每个校准集覆盖整个浓度范围的四分之一。还发现，无需额外测量即可轻松有效地构建多个校准集。
