近红外漫反射光谱法快速测定混合炸药组分含量

研究了近红外漫反射技术快速测定混合炸药组分含量的新方法.以偏最小二乘法建立了混合炸药中HMX(A)、复合黏结剂(氟橡胶B 塑料C)、聚四氟乙烯(D)、石蜡(E)5个组分的定标模型,并对模型进行了内部交互验证和外部检验.结果表明,5种模型准确度和精度较高,交互验证相关系数(R)为0.931 1～0.987 4,交互验证均方根(RMSECV)为0.100 ～0.582,预测标准偏差(SEP)为0.069～0.371;t检验也表明新方法与化学法无显著差异.新方法快速、无损,结果可靠.     

近红外漫反射光谱法快速测定金银花中水分含量

用近红外光谱仪采集中药金银花粉末的近红外漫反射光谱,运用偏最小二乘回归(PLSR)分析建立了金银花中水分含量定量模型,对金银花中的水分含量进行快速测定。该定量模型的相关系数为0.999 12、校正标准差为0.243、预测标准差为0.450;对建立的金银花中水分含量定量模型进行交叉验证,标准差为0.777;采用近红外漫反射光谱法和红外水分仪测定的金银花中水分含量经t检验无显著差异。该方法简便、快速、安全、实用,适用于中药水分含量的快速测定。     

火药吸收药中硝化棉含量快速检测方法

为了快速检测火药吸收药中硝化棉的含量,采用光纤探头采集吸收药混合液体系的近红外光谱图,通过分析纯NC和吸收药混合体系的光谱图特性,选择5 965~6 340cm-1和7 665~9 193cm-1为建模区域,用偏最小二乘法对NC组分建立了定量校正模型。结果表明,模型的决定系数R2为0.988 1,预测根方差RMSEP为0.223 8,预测集样本的预测平均相对误差为1.23%,检测时间小于20s,能够满足火药连续自动化生产的需要。     

近红外漫反射光谱法快速测定混合炸药中HMX的含量

建立了近红外漫反射光谱快速测定混合炸药中HMX含量的新方法。以不同谱图预处理方法与扫描谱区各波段的组合建立了HMX的定量校正模型,并通过模型内部交互验证和外部检验确定最优模型的交互验证相关系数R为0.9709,交叉验证均方根误差RMSECV为0.551%,预测标准偏差SEP为0.294%,表明所建模型具有较好的可靠性和稳健性。     

硝化棉含氮量测定方法的研究

使用意大利ＣＡＲＬＯＥＲＢＡ公司生产的ＮＡ－１５００元素分析仪，研究了硝化棉含氮量的测定方法，并与五管法和干涉仪法进行对比实验，元素分析法是测定硝化棉含氮量的一种很好的方法。     

近红外光谱法快速测定高含量精制甘油中的甘油含量

采用偏最小二乘法（PLS）建立了快速测定高含量精制甘油中甘油含量的近红外光谱校正模型,该模型主因子数为4,相关系数（R2）为99.12%,校正标准偏差（RMSECV）为0.027;以预测集对模型进行验证,结果表明,R2为99.17%,预测标准偏差（RMSEP）为0.023,对同一样品预测值的相对标准偏差（RSD）为0.04%。     

近红外光谱法测定HMX中α-HMX杂质晶型的含量

为了快速检测HMX中杂质晶型α-HMX的含量,在制备建模样品的基础上,利用近红外光谱技术,采用偏最小二乘法建立了HMX光谱与其α-HMX杂质晶型含量的计算模型。讨论了建模样品的代表性、模型光谱范围的选择及模型的优化过程。结果表明,模型具有广泛代表性,最佳光谱范围为6 476~6 446cm-1和4 602~4 424cm-1,交互验证决定系数(R2)为0.996,参考值交互验证残差均方根(RMSECV)为0.20%;外部验证的残差均方根(RMSEP)为0.27%;该法误差均小于0.13%,标准偏差为0.1%;近红外光谱法操作简单、快速、无损、绿色环保,可用于HMX中α-HMX杂质晶型含量的检测。     

近红外漫反射分析技术在测定聚丙烯粉料中二甲苯可溶物方面的应用

文章探讨了利用近红外分析技术快速判断聚丙烯粉料中的二甲苯可溶物含量的应用。用近红外漫反射法收集了样品的近红外光谱图。参照化学计量学分析方法测定聚丙烯样品的二甲苯可溶物含量。利用偏最小二乘法线性回归法建立了聚丙烯二甲苯可溶物的近红外光谱预测模型。将近红外法测定结果与化学分析方法测定结果进行了比较,对光谱测量的重复性进行了考察。结果表明,利用近红外光谱法与化学分析法的测定结果无显著差异。     

近红外光谱法测定银杏叶提取液中总黄酮含量

应用近红外光谱技术建立了快速测定银杏叶提取液中总黄酮含量的方法.将高效液相色谱法测定的总黄酮含量作为参考标准值用于建模,考察预测残差平方和(Predictive residual error sum of square,PRESS)与主成分之间的关系,主成分数为2时得到PRESS最小;用偏最小二乘法(PLS)进行回归分析得到的回归系数为0.98206、交叉验证结果的回归系数为0.96322,表明预测模型具有良好的稳定性.高效液相色谱法测定的银杏叶提取液中总黄酮含量与本方法的预测值之间存在良好的线性关系,t-检验结果表明,两种方法测得的总黄酮含量无显著性差异.本方法快速、简便,能准确地预测银杏叶提取液中总黄酮的含量.     

用偏光显微镜检测硝化棉的含氮量

建立了偏光显微镜测定硝化棉含氮量的新方法.采用色那蒙法测定了平均光程差.结果表明,当硝化棉含氮量为11.0%～13.8%时,光程差与含氮量线性相关,线性回归方程为ω＝-0.0466λ+12.388,线性相关系数R＝0.9993.用硝化棉标准物质对新方法检测结果进行了验证,回收率为99.7%～100.2%,变异系数为0....     

近红外光谱分析技术的发展和应用

介绍了近红外光谱分析技术的发展历史、常用化学计量学方法及其实际应用情况。     

近红外光谱法测定聚合反应液中的水含量

探讨了用近红外光谱法测定四氢呋喃聚合反应液中水含量的可行性，采用微库仑法测定聚合反应液中的水含量作为建立数学模型的标准数据。近红外光谱经一阶导数法预处理后，方法的灵敏度和准确性都有较大的改善，可以获得较好的定量结果。试验结果表明近红外光谱法与标准方法测定结果的相对偏差小于5％，成对t检验结果表明这2种分析方法之间无显著性差异，具有较好的重复性和准确性，适用于工业现场的在线检测。     

Estimation of Protein and Fatty Acid Composition in Shell-Intact Cottonseed by Near Infrared Reflectance Spectroscopy

Rapid and accurate analysis of cottonseed protein content and the composition of fatty acids (especially, saturated fatty acids) is often required in cotton production and breeding programs. This study aimed to establish a set of effective estimation models for these parameters. Near infrared reflectance spectroscopy (NIRS) calibration equations using partial least-squares regression for protein concentration, oil concentration, and five fatty acids of shell-intact cottonseeds were established based on 90 varieties, and the prediction abilities of the calibration models were verified using 45 other varieties. The prediction abilities of the NIRS calibration equations were basically consistent with external validation results. Each equation was assessed based on the ratio of performance to deviation (RPD_p). Protein content and seed total fatty acid (STA) content had high RPD_p values (3.687 and 3.530, respectively), whereas cottonseed kernel total fatty acid (KTA) content, linoleic acid (18:2), stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) exhibited relatively high RPD_p (2.866, 2.836, 2.697, 2.676, and 2.506, respectively). The calibration model for oleic acid (18:1) had a low RPD_p (1.945). The results indicated that NIRS can be used to rapidly determine contents of STA, KTA, protein, stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) in shell-intact cottonseed.     

Measurement of Infrared Spectra of Dense Ceramics by Specular Reflectance Spectroscopy

It is shown that high-quality IR specular reflectance spectra can be obtained from polished surfaces of dense ceramics. The reflectance spectra can be deconvoluted by the Kramers-Kronig transformation to yield absorption spectra or the real and imaginary parts of the dielectric function. IR line shapes and peak wavenumbers are comparable to single-crystal data providing that the particle size is small compared with the IR wavelengths of interest. For noncubic structures, the spectra are a superposition of polarization components. Modes separated by less than a bandwidth are merged into a single band, thus limiting the resolution of the measurement procedure. Grain size effects were modeled using the spectra of single-crystal and polycrystalline quartz as an example.     

近红外漫反射分析技术在测定共聚聚丙烯中乙烯含量的应用

文章探讨了利用近红外漫反射分析技术快速判断共聚聚丙烯中的乙烯含量的应用。用近红外漫反射法收集了样品近红外光谱图。利用中红外方法测定共聚聚丙烯样品的乙烯含量。利用偏最小二乘法线性回归法建立了聚丙烯中聚乙烯含量的近红外光谱预测模型。将近红外法测定结果与中红外方法测定结果进行了比较,对光谱测量的重复性进行了考察。结果表明,利用近红外光谱法与中红外方法的测定结果无显著差异,近红外法具有准确,快速,操作简便和低成本等特点。     

近红外光谱分析技术及应用进展

近红外光谱技术是近年来用于分析测试行业的一门新技术。对近红外光谱分析技术的概况、原理、特点进行了论述,介绍了该技术在石油化工行业中的应用,探讨了近红外光谱分析技术在炼油企业中的应用前景。     

利用全自动定氮仪测定硝化棉的含氮量

采用自行研制的全自动定氮仪测定硝化棉的含氮量,研究了样品前处理条件、全自动定氮仪实验参数对检测结果的影响;讨论了实验的准确性与重复性,对全自动定氮仪法与传统合金还原法进行了比较。结果表明,样品前处理采用石墨炉加热,梯度升温的皂化模式;最佳实验参数为:蒸汽体积分数80%、预热30s、还原反应7min、硼酸体积35mL、蒸馏时间8min;与传统合金还原法相比,采用全自动定氮仪检测硝化棉含氮量的方法用时少、操作简单,自动化程度高,减少了人为误差的影响,可保证结果的精度和准确性。     

近红外透反射光谱用于掺假牛奶的快速识别初探

为快速识别掺加违禁物质的假牛奶,在市售纯奶基础上按不同比例添加水+糊精、水+糊精+三聚氰胺(硝酸铵、尿素)的溶液,配制掺假牛奶,测试真、假牛奶样品的近红外透反射光谱,分别采用PLS-DA、KNN、LDA、改进与简化的KNN(IS-KNN)模式识别方法和不同光谱预处理方法进行真、假牛奶的识别。各模式识别方法在不同预处理光谱下对真、假两类牛奶的识别正确率最高为95.12%和96.34%并且在最高正确率下对所有掺假牛奶均能正确识别。表明采取适宜的近红外光谱预处理方法和模式识别方法,可以良好地对纯奶和掺假牛奶进行区分。     

Non-destructive Determination of High Oleic Acid Content in Single Soybean Seeds by Near Infrared Reflectance Spectroscopy

Soybean [Glycine max (L.) Merr] with increased oleic acid is desirable to improve oxidative stability and functionality of soybean seed oil. Recently, soybean genotypes with high oleic acid (≥70 %) were developed by breeding programs. Efficient and effective identification of high oleic acid soybean genotypes using non-destructive near infrared reflectance (NIR) on whole seeds would greatly enhance progress in breeding programs. The objective of this study was to develop a calibration equation for NIR determination of high oleic acid from single soybean seeds. A total of 600 intact, single F₂ seeds were scanned by NIR. Spectral data were collected between 400 and 2,500 nm at 2 nm intervals. The relationship between NIR spectral patterns of each soybean seed and its oleic acid content was examined. The best predicted equations for oleic acid were selected on the basis of minimizing the standard error of cross-validation and increasing the coefficient of determination. Validation demonstrated that the equations for determining total oleic acid and over 50 % oleic acid content had high predictive ability (r ² = 0.91 and r ² = 0.99, respectively). To validate the newly developed equation, F₂ seeds from a different genetic background were tested. Again, high oleic acid from single soybean seeds was accurately predicted from various genetic backgrounds. Therefore, applying the calibration equations to NIR will be useful to rapidly and efficiently select high oleic acid soybean genotypes in breeding programs.