期刊论文

Near Infrared Spectral Hybrid Model Quantitative Analysis on Samples with Different Physical States

Bin Jun

中文

分析化学

0253-3820

2017

45

7

958-964

10.11895/j.issn.0253.3820.160923

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [21275164]

本校为第一且通讯机构

近红外光谱(NIRS)以漫反射模式对非均质样本进行测量时,由于其光谱散射和吸收系数差异较大,建立的校正模型准确性和稳健性较低,因此,本研究提出了一种基于均质样本和模型转移方法建立混合模型的策略,解决非均质样本近红外光谱检测的问题。以烟叶样本为研究对象,分别建立了基于Shenk专利算法(Shenk's) 、分段直接标准化(PDS)和基于典型相关分析的模型转移算法(CTCCA)的烟粉+烟丝、烟粉+烟片混合模型,用于烟丝和烟片样本中烟碱含量的预测。结果表明,混合模型对烟丝和烟片样本的预测均方误差(RMSEP)较直接建模分别降低了1.39%和2.73%,预测结果有一定的改善,稳健性提高,3种方法中CTCCA表现最优。因此...

While the near infrared spectroscopy (NIRS) is used to measure the inhomogeneous samples with diffuse reflection mode, the accuracy and robustness of the calibration model is not quite good for the variation of spectrum scattering and absorption coefficient in those samples. Therefore, an establishment strategy of hybrid model based on homogeneous sample and calibration transfer method was proposed to solve the problem of detection inhomogeneous samples by NIRS. This work was focused on the tobacco leaf samples aspect. Three common calibration transfer methods, including Shenk's patented algor...