首页> 中文期刊> 《分析化学》 >近红外光谱混合模型定量分析不同物理状态样品的研究

近红外光谱混合模型定量分析不同物理状态样品的研究

         

摘要

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 algorithm (Shenk′s), piecewise direct standardization (PDS) and calibration transfer based on canonical correlation analysis (CTCCA), were used to construct two hybrid models of tobacco powder mixed with cut tobacco and tobacco powder mixed with tobacco flake samples to predict nicotine content in the samples of cut tobacco and tobacco flake.Experimental results showed that the hybrid model of adding some cut tobacco and tobacco flake samples to the powder model would get preferred prediction ability.Root mean square errors of cut tobacco and tobacco flake samples were reduced by 1.39% and 2.73%, respectively.This showed that the hybrid model was help for the improvement of the predicted results and the robustness of model.Moreover, CTCCA got the optimal performance between these three calibration transfer methods.Therefore, the scheme of building a hybrid model by NIRS homogeneous model and calibration transfer method to determinate the heterogeneous samples is feasible, which can accelerate the development of on-line near infrared spectroscopy technology and will provide reference for the share of near infrared spectral model.%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,采用近红外光谱均质模型和模型转移方法建立的混合模型对非均质样本的测定具有可行性,有利于在线近红外光谱分析技术的发展,可为近红外光谱模型的共享提供参考.

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