首页> 外文期刊>Applied Spectroscopy: Society for Applied Spectroscopy >Near-Infrared Absorption and Scattering Separated by Extended Inverted Signal Correction (EISC): Analysis of Near-Infrared Transmittance Spectra of Single Wheat Seeds
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Near-Infrared Absorption and Scattering Separated by Extended Inverted Signal Correction (EISC): Analysis of Near-Infrared Transmittance Spectra of Single Wheat Seeds

机译:扩展反相信号校正(EISC)分离的近红外吸收和散射:单粒小麦种子的近红外透射光谱分析

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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-trans-formation 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.
机译:提出了一种新的扩展方法,用于分离光谱测量中的例如吸光度的散射,扩展的倒相信号校正(EISC),并将其与乘性信号校正(MSC)及其现有改进进行比较。 EISC预处理应用于单个小麦籽粒的近红外透射率(NIT)光谱,旨在通过偏最小二乘回归(PLSR)改进蛋白质含量的多变量校准。 EISC方法的主要依据是促进消除与目标分析物浓度无关的光谱伪影和干扰。在这项研究中,EISC以通用形式应用,包括加法项,乘法项,光散射系数的波长依赖性以及简单多项式项。将其与常规MSC和派生方法进行光谱预处理相比。发现EISC的性能可与通过首先计算二阶导数NIT谱,然后计算MSC而获得的更复杂的双转化模型相媲美。基于EISC预处理的校准模型的性能优于基于原始数据,二阶导数,MSC和MSC后跟二阶导数的模型。

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