近红外光谱在无机微量成分分析中的应用

由于近红外光谱的独特优势, 在实际复杂样品分析中发挥了重要作用. 但由于近红外光谱的信号相对较弱, 无机离子在近红外光谱中一般没有响应, 因此难以用于微量成分特别是无机微量组分的测定. 总结了近红外光谱技术在环境、土壤、植物及生物样品分析中的应用, 说明了近红外光谱用于无机微量成分分析的原理. 由于近红外光谱技术一般通过多元校正方法进行定性定量分析, 利用组分间的相互作用或组分含量之间的相关性可以实现微量组分或无光谱响应组分的定量分析. 还总结了富集技术在近红外光谱分析中的应用, 利用富集技术可实现稀溶液中金属离子含量的快速测定, 并可以改善分析的灵敏度和检测限.     

近红外光谱法快速测定化橘红中柚皮苷的含量

利用近红外光谱快速测定技术,建立化橘红药材中柚皮苷含量测定模型;用高效液相色谱法(HPLC)测定44批不同产地的化橘红中柚皮苷的含量作为参考值,使用2350～2199 nm、1750～1600 nm和1301～1150 nm波长范围的近红外光谱检测技术,利用偏最小二乘回归分析结合交叉验证法,建立快速测定化橘红中柚皮苷含量的模型;结果表明,所建立的校正模型的相关系数和内部交叉验证均方差分别为:R~2=0.978,RMSECV=0.997,预测结果良好。该法的建立证明了近红外光谱技术应用于化橘红药材中柚皮苷含量测定的可行性;近红外光谱结合偏最小二乘法(NIR-PLS)可以快速评估化橘红药材中柚皮苷的含量,可以应用于大批化橘红药材中柚皮苷的含量测定。     

近红外光谱法测定成品汽油中的芳烃和烯烃含量

介绍了近红外光谱测定90#汽油及93#汽油中芳烃和烯烃含量。选择1100～1300nm的近红外光谱域,在荧光指示剂吸附法的基础上,采用偏最小二乘法建立了适合测定90#汽油及93#汽油中芳烃和烯烃含量的分析模型,通过大量试验对所建分析模型的可靠性进行了验证。近红外光谱法的测定结果与荧光指示剂吸附法的测定结果具有很好的一致性。与荧光指示剂吸附法相比,近红外光谱法可以提高分析效率,降低分析成本,具有较高的分析精密度。     

近红外光谱法快速测定再造烟叶成品小片中主要化学成分

提出了近红外光谱法快速测定再造烟叶成品小片中烟碱、总糖、还原糖、总氮、钾、氯等6种主要化学成分的方法。直接采集再造烟叶成品小片,结合偏最小二乘回归算法建立了近红外光谱的分析模型。结果表明:再造烟叶成品小片的近红外光谱能真实、有效地表征待测样品的内在化学物质组成与含量信息;除总氮外,其余5种成分的再造烟叶成品小片近红外光谱分析模型的相关系数均大于0.90;烟碱、总糖、还原糖、总氮、钾、氯等6种成分的预测误差分别为0.024 3,0.399 1,0.270 3,0.059 9,0.050 3,0.031 1。小片光谱分析模型效果与粉末光谱模型较接近,可以替代粉末模型用于再造烟叶成品小片化学成分含量的测定。     

应用近红外透射光谱法测定稻米淀粉消减值的研究

以183份稻米为样品,利用近红外透射光谱分析仪,对样品进行光谱扫描,并用快速黏度分析仪测定黏滞特性值消减值.采用多种计量数学处理方法和不同的回归统计方法进行定标曲线的开发和比较,得到了稻米消减值测定的近红外分析数学模型,数学模型的定标标准偏差(SEC)、交叉检验标准误差(SECV)和定标决定系数(RSQ)分别为:18.69,19.08和O.949 7.相关性达极显著水平,内部交叉验证和外部验证结果表明近红外定量分析消减值有很高的准确度.该研究利用近红外透射光谱技术为快速准确无损测定黏滞特性指标提供了一条新途径.     

近红外光谱用于过氧化氢含量的定量分析研究

用长波近红外光谱仪（傅里叶变换,InGaAs检测器）和短波近红外光谱仪（光栅分光,CCD检测器）对比研究了25％～30％过氧化氢水溶液中过氧化氢含量的定量分析方法。结果表明,应用短波近红外光谱结合长光程样品池对25％-30％过氧化氢水溶液样品中过氧化氢含量进行定量分析,可以显著减少过氧化氢分解对定量分析的干扰,使定量分析的准确度和重复性显著提高。短波近红外光谱定量分析模型RMSECV和RMSEP分别为0．06和0．05;长波近红外光谱定量分析模型RMSECV和RMSEP分别为0．10和0．09。     

温度限制串联相关网络-近红外光谱法用于药物甲硝唑的质量控制

近红外漫反射光谱是一种简便、快速的有机物分析方法,样品不需处理即可直接测量,易于实现固态样非破坏测定.近红外漫反射光谱分析技术广泛应用于农业、食品、化妆品、烟草和石油等方面的组分分用近红外漫反射光谱法进行药品的非破坏性分析正成为国际热门课题.但近红外漫反射光谱的光谱范宽,吸收强度很弱,且组分间光谱严重重叠,给非破坏性分析带来了困难.而近红外漫反射光谱法与化量学相结合,能有效地解决光谱重叠带来的问题[1～3].     

近红外光谱法测定端羟基环氧乙烷-四氢呋喃共聚醚的羟值

提出了用近红外光谱测定端羟基环氧乙烷-四氢呋喃共聚醚(PET)的羟值,结合主成分回归和偏最小二乘法建立了PET羟值与其近红外光谱之间的关联模型。结果表明,近红外光谱法与化学分析法的测定结果一致;近红外光谱法测定PET羟值的相对误差在5%以内;利用遗传算法选择部分波长建立校正可以降低模型的预测误差。     

CCD近红外光谱快速测定喷气燃料的冰点

从化学计量学角度研究了近红外光谱技术测定航空燃料冰点的原理．使用偏最小二乘法分别建立了短波近红外和长波近红外的航空燃料冰点快速测定模型．将近红外法冰点测定结果和标准方法（ＧＢ ２４３０—８１）测定结果进行了比较，两种结果吻合得很好（标准偏差为１．４７℃。），近红外光谱法具有分析精度高（标准偏差为０．５３℃），快速（单个样品分析时间为 ｌｍｉｎ）和操作方便的优点．实际分析结果表明，石油化工科学研究院研制的ＣＣＤ短波近红外光谱仪分析性能达到进口傅立叶近红外光谱仪水平。     

光谱采集方式对AOTF-近红外光谱技术分析烟草主要化学成分的影响

初步探讨了不同光谱采集方式对AOTF-近红外光谱技术检测烟草主要化学成分及建模的影响。结果表明,以旋转方式采集光谱可以得到更多的样品信息,所建立的模型精度较高。从模型的各项指标来看,总糖、还原糖和总烟碱的相关系数很高,说明化学成分含量数据和光谱数据间有较好的相关性。实验结果表明AOTF-近红外光谱技术可用于烟草样品主要化学成分的常规分析。     

用近红外光谱仪快速测定调和汽油中芳烃、烯烃的含量

介绍了带有CCD检测器的近红光普仪在调和汽油分析中的应用，并与标准测定方法测定的数据对比，验证了近红外光谱法测定汽油性质的可靠性，同时表明该方法具有分析速度快，重现性好等特点。     

近红外光谱仪的研制

采用电荷耦合器件（ＣＣＤ）为检测器研制了近红外光谱仪,该仪器具有结构简单,无可移动光学部件,性能稳定和扫描速度快的特点,主要技术性能指标如重复性,分辨率,波长准确性和噪音都可以满意常规分析的要求。并配有基于化学计量学的分析软件。已有多家炼油厂中应用,其分析结果符合标准分析方法的要求。     

LapRLSR for NIR spectral modeling and its application to online monitoring of the column separation of Salvianolate

A novel near infrared (NIR) modeling method—Laplacian regularized least squares regression (LapRLSR) was presented, which can take the advantage of many unlabeled spectra to promote the prediction performance of the model even if there are only few calibration samples. Using LapRLSR modeling, NIR spectral analysis was applied to the online monitoring of the concentration of salvia acid B in the column separation of Salvianolate. The results demonstrated that LapRLSR outperformed partial least squares (PLS) significantly, and NIR online analysis was applicable.     

火焰原子吸收光谱法测定高铋铅中的铜

建立了火焰原子吸收光谱法测定高铋铅中铜含量的方法。研究了多种溶样方法,最终采用硝酸-酒石酸溶解试样,在硝酸(10%)介质中以火焰原子吸收光谱法测定溶液中的铜量,加标回收率在99.4%~105%,相对标准偏差(RSD,n=7)小于3.5%。方法操作过程简单,精密度高,回收率良好,能够较好地满足分析检测的要求。     

Nir-chemical imaging study of acetylsalicylic acid in commercial tablets

Near Infrared Chemical Imaging (NIR-CI) is demonstrating an increasing interest in pharmaceutical research since it meets the challenging analytical needs of pharmaceutical quality and may serve as a versatile adjunct to conventional NIR spectroscopy in many fields.The direct analysis of samples by using hyperspectral imaging techniques, which provide a NIR spectrum in each pixel of the image, generates a big amount of information from one sample. Focusing the interest in pharmaceutical research, several chemometric algorithms are demonstrating their usefulness extracting the relevant information (i.e. quantitative determination of the component in one sample) in tablets with only one sample and without damaging it.In this work, a quantitative method to analyze different commercial Acetylsalicylic acid tablets is proposed by using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) method to the hyperspectral image and without any previous calibration model. For this purpose, a large concentration range of active pharmaceutical ingredient (ASA, Acetylsalicylic acid in this work), between 82% and 12%, was covered depending on the manufacturer. MCR-ALS allowed obtaining a concentration maps for acetylsalicylic acid and therefore, consequent analysis of the ASA distribution in the tablet was developed by using the histograms of the distribution of concentration.Results certified the good distribution of ASA despite the different origins of the tablets. Moreover, the obtained values of concentration showed a very good concordance with the nominal value of ASA. As a matter of fact, the quality of the results demonstrated the useful of encompassing NIR-CI techniques with MCR-ALS and, consequently, the well development on the production of Acetylsalicylic acid tablets.     

Feasibility of monitoring acetic acid process using near-infrared spectroscopy

Near-infrared (NIR) spectroscopy has been utilized to demonstrate its feasibility for the measurement of major components in the acetic acid process. In order to simulate the acetic acid process, synthetic mixtures were prepared from five different components: acetic acid, methyl acetate, methyl iodide, water, and potassium iodide. Partial least squares (PLS) regression was utilized to differentiate the spectral characteristics as well as to quantify each component for the mixtures. The spectral features of acetic acid, methyl acetate, methyl iodide, and water are noticeably different with each other over the entire NIR region. The quantity of iodide ion, which does not absorb NIR radiation, was determined using the wavelength shift and intensity change of water absorption band caused by the change of iodide ion concentration. The PLS calibration results of the five components show good correlation with reference data. They also demonstrate the technical feasibility of NIR spectroscopy for monitoring important components in the acetic acid process.     

火焰原子吸收光谱法测定铜原矿尾矿中的镉

采用盐酸、氢氟酸、硝酸、高氯酸分步溶解的方式对具有硅、铁含量高等特性的铜原矿尾矿样品进行溶解。在体积分数为5%的盐酸介质中,利用原子吸收光谱法,采用扣除背景方式对样品溶液进行测定。样品溶解较完全,共存元素对镉的测定基本无干扰。方法重现性较好,准确度较高。相对标准偏差在2.3%~8.3%,加标回收率在96.7%~105%,标准样品分析结果与标准值基本一致。能满足日常分析检测的需要。     

汽油族组成的近红外光谱快速测定

以荧光指示剂吸附色谱法（FIA）测定汽油族组成结果为基础，采用近红外光谱和化学计量学方法建立了快速、准确测定催化裂化馏出口汽油族组成（饱和烃、烯烃和芳烃）的分析模型；试验表明，该法分析速度快、重复性好、成本低，特别适用于生产中间控制分析。     

Development of a rapid process monitoring method for dry-coated tableting process by using near-infrared spectroscopy

A nondestructive transmittance near-infrared (NIR) method for detecting off-centered cores in dry-coated (DC) tablets was developed as a monitoring system in the DC tableting process. Caffeine anhydrate was used as a core active pharmaceutical ingredient (API), and DC tablets were made by the direct compression method. NIR spectra were obtained from these intact DC tablets using the transmittance method. The reference assay was performed with HPLC. Calibration models were generated by partial least squares (PLS) regression and principal component regression (PCR) utilizing external validations. Hierarchical cluster analysis (HCA) of the results confirmed that NIR spectroscopy correctly detected off-centered cores in DC tablets. We formulated and used the Centering Index (CI) to evaluate the precision of core alignment and generated an NIR calibration model that could correctly predict this index. The principal component (PC) 1 loading vector of the final calibration model indicated that it could specifically detect the misalignment of tablet cores. The model also had good linearity and accuracy. The CIs of unknown sample tablets predicted by the final calibration model and those calculated through the HPLC analysis were closely parallel with each other. These results demonstrate the validity of the final calibration model and the utility of the transmittance NIR spectroscopic method developed in this study as a monitoring system in DC tableting process.     

中药口服固体制剂原辅料近红外光谱数据库的构建及应用

建立了中药口服固体制剂原辅料近红外(NIR)光谱数据库,采用模式识别方法研究了NIR光谱数据在物料分类和物性预测中的应用。使用便携式近红外光谱仪快速测量149批原辅料粉末的NIR漫反射光谱数据,并录入iTCM数据库。利用主成分分析(PCA)法探究NIR光谱数据对已知结构物料的分类能力,采用偏最小二乘(PLS)法研究了NIR光谱对原辅料物性参数和直接压片片剂性能的预测能力。经标准正态变量变换(SNV)+Savitzky-Golay(SG)平滑+一阶导数处理后的NIR光谱数据对微晶纤维素、乳糖、乙基纤维素、交联聚维酮和羟丙基甲基纤维素这5类辅料的区分能力较好。NIR光谱数据与原辅料粉末粒径、密度和吸湿性的相关性较强。NIR光谱信息作为物料物理性质的补充,可提高粉末直接压片片剂性能预测模型的性能。NIR光谱数据是iTCM数据库物性参数数据的补充,物性参数与NIR光谱数据的结合能更全面地表征原辅料的性质。