近红外光谱微量分析方法研究
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摘要
近红外光谱分析方法具有高效、快速、成本低、无污染且不破坏样品等优点。它不仅可用于实验室内分析,而且在现场快速检测和实时在线分析方面也发挥着重要的作用。近红外光谱谱峰较宽且重叠严重,必须借助化学计量学方法建立校正模型才能进行定性定量分析。然而,在校正过程中,需要收集大量代表性样品进行化学分析,提供其组分或性质已知的数据来建立和维护模型。此外,近红外光谱产生于分子振动光谱的倍频和合频吸收,主要记录含氢基团(C-H,O-H,N-H,S-H)的吸收信息,吸收较弱,因此该方法的检测灵敏度较低。这些问题严重阻碍着近红外光谱分析方法的发展和应用。本文针对近红外光谱建模时校正样本的设计问题,开展了近红外光谱简约定量分析模型的构建方法研究并用于复杂样品的定量分析;针对近红外光谱分析方法检测灵敏度较低的问题,开展了样品吸附富集预处理结合近红外漫反射光谱用于提高近红外光谱分析方法检测灵敏度的研究。
1.针对复杂样品近红外光谱分析中校正集的设计问题,探讨了标准样品参与复杂样品建模的可行性。通过标准样品和复杂基质样品共同构建的偏最小二乘(partial least squares,PLS)模型,考察了波段筛选和建模参数对预测结果的影响。结果表明,采用PLS方法建立定量模型时,校正集样品性质应该尽量与预测集样品相似,当样品的性质相差较大时,适当增加校正集样品的差异性可以使模型具有较强的预测能力。同时,波段优选对提高预测结果的准确性具有重要意义。
2.为了对烟草中绿原酸含量实现快速准确的定量分析,采用近红外光谱分析方法对烟草提取液和绿原酸标准溶液组成的混合样品集进行PLS回归分析,通过选用不同的建模样品,讨论了提取液中共存组分对绿原酸定量模型的影响。选用不同的光谱预处理技术,结合间隔偏最小二乘(interval partial least squares,iPLS)对绿原酸的建模区域进行优选,建立了绿原酸的近红外光谱分析模型。结果表明,波段筛选有效地消除了共存组分的干扰,绿原酸标准溶液样品结合部分烟草提取液样品可以建立准确、稳健的分析模型。该方法可以作为烟草行业分析绿原酸的有效手段。
3.为了改善近红外光谱分析方法灵敏度较低的弱点,在使用近红外光谱对目标组分进行检测时,引入了吸附富集的样品预处理方法。以饮料中低含量的苯甲酸和山梨酸为分析对象,以氧化铝为吸附材料对两种目标物进行吸附,吸附后氧化铝的漫反射光谱用于建模和预测。结果表明,通过采用吸附富集的样品预处理方法,可以极大地提高近红外光谱的检测灵敏度,采用PLS回归的多元校正方法可以消除吸附剂表面共吸组分对目标组分的干扰。
4.低浓度水体有机污染物的快速定量分析是分析化学的研究热点之一。为了实现水体中低浓度有机污染物的同时快速分析,选取大孔吸附树脂为吸附剂,对废水中的苯酚和对硝基苯酚进行吸附富集,采用近红外漫反射光谱分析方法对其进行定量分析。研究结果表明,树脂吸附结合近红外漫反射光谱分析方法实现了低浓度苯酚和对硝基苯酚的同时定量分析,为水体中低含量组分的近红外光谱快速分析提供了新思路。同时,该工作也说明了树脂吸附预富集是一种有效地提高近红外光谱分析灵敏度的方法。
5.为了对复杂体系中低浓度氨基酸进行定量分析,以氨基酸混合物标准溶液以及合成饮料中的氨基酸和氨基态氮为研究对象,采用凝胶型阳离子交换树脂和大孔阳离子交换树脂对其进行吸附富集预处理,结合近红外漫反射光谱分析方法进行定量分析,探讨了不同离子交换树脂对定量结果的影响,比较了最小二乘支持向量回归(least squares support vector regression,LS-SVR)和偏最小二乘回归(partial least squares regression,PLSR)的预测结果。结果表明,树脂吸附富集预处理方法的引入,实现了近红外光谱分析法定量分析低浓度氨基态氮的目标,而对每种氨基酸单独进行定量分析的结果较差;离子交换树脂的颜色、孔径以及类型对氨基态氮的定量结果没有影响;LS-SVR的多元校正方法的预测结果略优于PLSR的预测结果,合成氨基酸饮料中复杂基质的存在不会影响氨基态氮的预测结果。
Near infrared (NIR) spectroscopy analytical method is efficient, rapid, noninvasive, environmental friendly, and it can be run at low costs. It is not only suitable for laboratory analysis, but also in-field fast measurement and real-time on-line analysis. However, NIR spectral bands are relatively weak and highly overlapping. Therefore, chemometrical methods are commonly used for building calibration model for qualitative and quantitative analysis. However, in order to constructing and maintaining models, large numbers of representative samples are collected for wet chemical analysis, and providing data information of components and characters. NIR spectrum is based on measurement of the overtone and combination frequencies of the vibrations of chemical bonds, and mainly records the absorption information of C-H, O-H, N-H and S-H, which make its relatively weak spectral bands and high detection limit. Up to now, these problems have not been solved thoroughly, which obstruct further development and application of NIR spectroscopy analytical method. In the dissertation, the design of calibration samples and improvement of quantitative determination ability for low concentration analytes were investigated for the quantitative analysis of complex samples.
The main research contents of the dissertation involve:
1. The design of calibration samples is often used to improve the cost-effectiveness of near-infrared (NIR) spectral analysis. A feasibility of constructing a parsimonious multivariate calibration model for NIR spectral analysis was demonstrated by constructing partial least squares (PLS) models with both standard and complex samples. Waveband selection algorithm and other parameters were also be discussed for improve predictive ability of models. The results indicate when constructing quantitative analysis PLS model, the calibration samples should be as similar as possible to the prediction samples. When there is a big difference in the properties of samples between calibration and prediction sets, it can improve the predictive ability of the models by extending the difference of calibration set samples. At the same time, it is very important to adopt waveband selection algorithms before modeling for improving the predictive ability of models.
2. A method for quantitative analysis of chlorogenic acid in tobacco extracts was developed by using near infrared spectroscopy (NIRS) and PLS regression. Effects of the coexistence solutes on PLS model were discussed by constructing different models with standard solutions and real tobacco extracts. Results show that standard samples can be used as a part of the calibration samples when there are not enough real samples, and the interference of the coexistence solutes can be eliminated by selection of suitable wavelength regions. The proposed approach appears to be a valid alternative for fast analysis of chlorogenic acid in tobacco industry.
3. Near-infrared diffuse reflectance spectroscopy (NIRDRS) has been proved to be a convenient and fast quantitative method for complex samples. The high detection limit or the low sensitivity of the method, however, is a big problem obstructing its application in the analysis of low concentration samples. A strategy for quantitative determination of low concentration samples was developed by using NIRDRS. Taking benzoic and sorbic acids as the analyzing targets and the alumina as the adsorbent, PLS model is built from the NIRDRS of the adsorbates. The results show that the detection limit can be improved by using adsorption preconcentration, and the interferences of co-adsorbates can be eliminated by using multivariate calibration method.
4. Organic pollutants in water are one of the major water quality pollution. A method for quantitative determination of low concentration phenol and p-nitrophenol from wastewater was developed by using NIRDRS and a preconcentration procedure of resin adsorption. In the method, the analytes were firstly adsorbed onto NKA-II resin for preconcentration, and then NIRDRS of the resin is measured for quantitative analysis. The results show that both the phenolic compounds can be immobilized onto the adsorbent and directly measured by NIRDRS. The method provides new opportunities for analyzing low concentration components in aqueous solutions. At the same time, the proposed method may be an effective way for improving the detection ability of the NIRDRS for quantitative analysis of low concentration analytes.
5. The feasibility of NIRS and adsorption preconcentration procedure for determination of low concentration free amino acids including threonine (Thr), methionine (Met), lysine (Lys) and leucine (Leu) in aqueous solutions and amino nitrogen was investigated. In the method, two ion exchange resins were used for adsorption preconcentration of amino acids, and NIRDRS was used for collecting the spectra of resin after adsorption. The effect of the different kinds of resins on the determination results was investigated. The results obtained by using least-squares support vector regression (LS-SVR) and partial least squares regression (PLSR), which were used to eliminate the interferences resulting from near infrared diffuse reflectance spectra of resin and other coexistence components, were compared. The results show that preconcentration procedure of resin adsorption and NIRDRS were successfully used in determination of low concentration amino nitrogen, while the quantitative result of each amino acid is unsatisfactory. The resins with different colours, apertures and types have no effect on quantitative analysis. The performance of LS-SVR was slightly better than that of PLSR. Complex matrix interferences of co-existence in amino acid beverage can be eliminated by using multivariate calibration method.
1.针对复杂样品近红外光谱分析中校正集的设计问题,探讨了标准样品参与复杂样品建模的可行性。通过标准样品和复杂基质样品共同构建的偏最小二乘(partial least squares,PLS)模型,考察了波段筛选和建模参数对预测结果的影响。结果表明,采用PLS方法建立定量模型时,校正集样品性质应该尽量与预测集样品相似,当样品的性质相差较大时,适当增加校正集样品的差异性可以使模型具有较强的预测能力。同时,波段优选对提高预测结果的准确性具有重要意义。
2.为了对烟草中绿原酸含量实现快速准确的定量分析,采用近红外光谱分析方法对烟草提取液和绿原酸标准溶液组成的混合样品集进行PLS回归分析,通过选用不同的建模样品,讨论了提取液中共存组分对绿原酸定量模型的影响。选用不同的光谱预处理技术,结合间隔偏最小二乘(interval partial least squares,iPLS)对绿原酸的建模区域进行优选,建立了绿原酸的近红外光谱分析模型。结果表明,波段筛选有效地消除了共存组分的干扰,绿原酸标准溶液样品结合部分烟草提取液样品可以建立准确、稳健的分析模型。该方法可以作为烟草行业分析绿原酸的有效手段。
3.为了改善近红外光谱分析方法灵敏度较低的弱点,在使用近红外光谱对目标组分进行检测时,引入了吸附富集的样品预处理方法。以饮料中低含量的苯甲酸和山梨酸为分析对象,以氧化铝为吸附材料对两种目标物进行吸附,吸附后氧化铝的漫反射光谱用于建模和预测。结果表明,通过采用吸附富集的样品预处理方法,可以极大地提高近红外光谱的检测灵敏度,采用PLS回归的多元校正方法可以消除吸附剂表面共吸组分对目标组分的干扰。
4.低浓度水体有机污染物的快速定量分析是分析化学的研究热点之一。为了实现水体中低浓度有机污染物的同时快速分析,选取大孔吸附树脂为吸附剂,对废水中的苯酚和对硝基苯酚进行吸附富集,采用近红外漫反射光谱分析方法对其进行定量分析。研究结果表明,树脂吸附结合近红外漫反射光谱分析方法实现了低浓度苯酚和对硝基苯酚的同时定量分析,为水体中低含量组分的近红外光谱快速分析提供了新思路。同时,该工作也说明了树脂吸附预富集是一种有效地提高近红外光谱分析灵敏度的方法。
5.为了对复杂体系中低浓度氨基酸进行定量分析,以氨基酸混合物标准溶液以及合成饮料中的氨基酸和氨基态氮为研究对象,采用凝胶型阳离子交换树脂和大孔阳离子交换树脂对其进行吸附富集预处理,结合近红外漫反射光谱分析方法进行定量分析,探讨了不同离子交换树脂对定量结果的影响,比较了最小二乘支持向量回归(least squares support vector regression,LS-SVR)和偏最小二乘回归(partial least squares regression,PLSR)的预测结果。结果表明,树脂吸附富集预处理方法的引入,实现了近红外光谱分析法定量分析低浓度氨基态氮的目标,而对每种氨基酸单独进行定量分析的结果较差;离子交换树脂的颜色、孔径以及类型对氨基态氮的定量结果没有影响;LS-SVR的多元校正方法的预测结果略优于PLSR的预测结果,合成氨基酸饮料中复杂基质的存在不会影响氨基态氮的预测结果。
Near infrared (NIR) spectroscopy analytical method is efficient, rapid, noninvasive, environmental friendly, and it can be run at low costs. It is not only suitable for laboratory analysis, but also in-field fast measurement and real-time on-line analysis. However, NIR spectral bands are relatively weak and highly overlapping. Therefore, chemometrical methods are commonly used for building calibration model for qualitative and quantitative analysis. However, in order to constructing and maintaining models, large numbers of representative samples are collected for wet chemical analysis, and providing data information of components and characters. NIR spectrum is based on measurement of the overtone and combination frequencies of the vibrations of chemical bonds, and mainly records the absorption information of C-H, O-H, N-H and S-H, which make its relatively weak spectral bands and high detection limit. Up to now, these problems have not been solved thoroughly, which obstruct further development and application of NIR spectroscopy analytical method. In the dissertation, the design of calibration samples and improvement of quantitative determination ability for low concentration analytes were investigated for the quantitative analysis of complex samples.
The main research contents of the dissertation involve:
1. The design of calibration samples is often used to improve the cost-effectiveness of near-infrared (NIR) spectral analysis. A feasibility of constructing a parsimonious multivariate calibration model for NIR spectral analysis was demonstrated by constructing partial least squares (PLS) models with both standard and complex samples. Waveband selection algorithm and other parameters were also be discussed for improve predictive ability of models. The results indicate when constructing quantitative analysis PLS model, the calibration samples should be as similar as possible to the prediction samples. When there is a big difference in the properties of samples between calibration and prediction sets, it can improve the predictive ability of the models by extending the difference of calibration set samples. At the same time, it is very important to adopt waveband selection algorithms before modeling for improving the predictive ability of models.
2. A method for quantitative analysis of chlorogenic acid in tobacco extracts was developed by using near infrared spectroscopy (NIRS) and PLS regression. Effects of the coexistence solutes on PLS model were discussed by constructing different models with standard solutions and real tobacco extracts. Results show that standard samples can be used as a part of the calibration samples when there are not enough real samples, and the interference of the coexistence solutes can be eliminated by selection of suitable wavelength regions. The proposed approach appears to be a valid alternative for fast analysis of chlorogenic acid in tobacco industry.
3. Near-infrared diffuse reflectance spectroscopy (NIRDRS) has been proved to be a convenient and fast quantitative method for complex samples. The high detection limit or the low sensitivity of the method, however, is a big problem obstructing its application in the analysis of low concentration samples. A strategy for quantitative determination of low concentration samples was developed by using NIRDRS. Taking benzoic and sorbic acids as the analyzing targets and the alumina as the adsorbent, PLS model is built from the NIRDRS of the adsorbates. The results show that the detection limit can be improved by using adsorption preconcentration, and the interferences of co-adsorbates can be eliminated by using multivariate calibration method.
4. Organic pollutants in water are one of the major water quality pollution. A method for quantitative determination of low concentration phenol and p-nitrophenol from wastewater was developed by using NIRDRS and a preconcentration procedure of resin adsorption. In the method, the analytes were firstly adsorbed onto NKA-II resin for preconcentration, and then NIRDRS of the resin is measured for quantitative analysis. The results show that both the phenolic compounds can be immobilized onto the adsorbent and directly measured by NIRDRS. The method provides new opportunities for analyzing low concentration components in aqueous solutions. At the same time, the proposed method may be an effective way for improving the detection ability of the NIRDRS for quantitative analysis of low concentration analytes.
5. The feasibility of NIRS and adsorption preconcentration procedure for determination of low concentration free amino acids including threonine (Thr), methionine (Met), lysine (Lys) and leucine (Leu) in aqueous solutions and amino nitrogen was investigated. In the method, two ion exchange resins were used for adsorption preconcentration of amino acids, and NIRDRS was used for collecting the spectra of resin after adsorption. The effect of the different kinds of resins on the determination results was investigated. The results obtained by using least-squares support vector regression (LS-SVR) and partial least squares regression (PLSR), which were used to eliminate the interferences resulting from near infrared diffuse reflectance spectra of resin and other coexistence components, were compared. The results show that preconcentration procedure of resin adsorption and NIRDRS were successfully used in determination of low concentration amino nitrogen, while the quantitative result of each amino acid is unsatisfactory. The resins with different colours, apertures and types have no effect on quantitative analysis. The performance of LS-SVR was slightly better than that of PLSR. Complex matrix interferences of co-existence in amino acid beverage can be eliminated by using multivariate calibration method.
引文
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