吸光度
透射率
校准
偏最小二乘回归
乘法函数
信号(编程语言)
化学
二阶导数
分析物
谱线
红外线的
散射
近红外光谱
光学
分析化学(期刊)
数学
物理
统计
数学分析
计算机科学
色谱法
物理化学
程序设计语言
天文
作者
Dorthe Kjær Pedersen,Harald Martens,Jens Peter Nielsen,Søren Balling Engelsen
标识
DOI:10.1366/000370202760295467
摘要
A new extended method for separating, e.g., scattering from absorbance in spectroscopic measurements, extended inverted signal correction (EISC), is presented and compared to multiplicative signal correction (MSC) and existing modifications of this. EISC preprocessing is applied to near-infrared transmittance (NIT) spectra of single wheat kernels with the aim of improving the multivariate calibration for protein content by partial least-squares regression (PLSR). The primary justification of the EISC method is to facilitate removal of spectral artifacts and interferences that are uncorrelated to target analyte concentration. In this study, EISC is applied in a general form, including additive terms, multiplicative terms, wavelength dependency of the light scatter coefficient, and simple polynomial terms. It is compared to conventional MSC and derivative methods for spectral preprocessing. Performance of the EISC was found to be comparable to a more complex dual-transformation model obtained by first calculating the second derivative NIT spectra followed by MSC. The calibration model based on EISC preprocessing performed better than models based on the raw data, second derivatives, MSC, and MSC followed by second derivatives.
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