红外、近红外光谱-簇类的独立软模式方法识别植物调和油脂

用IR,NIR光谱法结合簇类的独立软模式(SIMCA)识别方法对植物油脂进行分类识别,建立了识别二元、三元植物调和油脂的测定方法。应用NIRCal5.2软件的SIMCA技术,分别为所制备的植物调和油脂建立了IR和NIR识别模型,并讨论了光谱处理和数据处理方法来提高模型的分类识别效果。分别以各种植物调和油脂的IR和NIR光谱为变量,随机抽取2/3的样本作训练集,建立了各个调和油的主成分分析(Princi-pal component analysis,PCA)模型;1/3作验证集,对所建模型进行验证识别。用聚类分析-主成分分析(CLU-PCA)方法考察调和油的IR,NIR光谱信息与其纯油的主成分分布。结果显示,在4000～10000cm-1光谱范围内,SIMCA可以对15种二元调和油和2种三元调和油的NIR光谱分别聚类并识别;并对10种二元调和油和2种三元调和油的IR光谱分别聚类并识别。IR以4个波数1099,1119,1746与2855cm-1的吸收值作为分析基础,选择不同的主成分数及数据预处理方法。各种油脂的SIMCA分析的分类精度均为100%,调和油的验证识别准确率100%,最低识别比例为1%,且IR识别灵敏度高于NIR。     

基于近红外光谱技术与优化光谱预处理的陈皮产地鉴别研究

采集不同产地陈皮内侧和外侧的近红外光谱,采用不同光谱预处理方法进行预处理,筛选得到最佳光谱预处理方法,结合主成分分析法建立了陈皮产地的鉴别模型.实验发现,陈皮原始光谱中存在明显的基线漂移与背景干扰.使用单一光谱预处理可在一定程度上消除干扰的影响.经标准正态变量变换、多元散射校正、一阶导数、二阶导数与连续小波变换预处理后...     

近红外光谱技术结合主成分分析法用于子宫内膜癌的诊断

应用近红外光谱技术结合化学计量学方法研究了子宫内膜癌组织近红外光谱特征提取和早期诊断的可行性. 测定了154 例子宫内膜组织切片的近红外光谱, 选取适宜的波段和光谱预处理方法进行主成分分析, 很好地区分了癌变、增生和正常子宫内膜组织切片, 并且分辨出处于不同分化期的组织切片, 为子宫内膜癌的早期诊断提供了可靠依据. 该法快速、简便, 有望发展成为一种新型的肿瘤无创诊断方法.     

基于近红外光谱分析技术的食品包装塑料的定性分析

该文基于近红外漫反射光谱分析技术对食品包装材料聚乙烯、聚丙烯进行定性判别试验研究,选取不同波段范围、采用不同光谱预处理方法,使用主成分分析法(Principal component analysis,PCA)结合SIMCA、贝叶斯判别、K-近邻3种模式识别方法建立定性预测模型,并根据正确识别率比较了各模型预测性能。结果表明:使用SIMCA方法、贝叶斯判别、K-近邻3种方法建立的定性校正模型均在1 050～1 550 nm波长范围内效果较好;采用矢量归一化、标准正态变量变换、中心化、滑动均值滤波、多项式平滑滤波、一阶微分6种光谱预处理方法和上述3种模式识别方法对塑料样品近红外光谱进行了数据处理,其中在1 050～1 550 nm范围内,主成分因子数为3,采用原始光谱建立的K-近邻定性校正模型较优,对样品校正集和预测集的正确识别率均为100%。可为食品包装材料聚乙烯、聚丙烯的快速鉴别研究提供参考。     

基于近红外光谱技术与化学计量学的绿茶无损鉴别方法研究

该文利用近红外光谱技术结合化学计量学方法开发了不同品种绿茶的无损鉴别方法。通过近红外光谱技术得到了8个品种绿茶样品的近红外光谱,比较了单一以及优化组合光谱预处理方法对光谱的影响,利用无监督的主成分分析(PCA)与有监督的线性判别分析方法(LDA)分别构建了茶叶品种鉴别模型。结果表明:对比单一预处理方法,优化组合预处理具有更优的鉴别准确性。标准正态变量变换预处理消除了茶叶样品大小不均造成的光谱散射影响,一阶导数预处理实现了变动背景的消除,减少了基线漂移的影响,突出了图谱中的有效信息,采用二者相结合的预处理方式并结合无监督的主成分分析法可实现较为准确的绿茶样品种类鉴别分析,准确率达75.0%。此外,采用有监督的线性判别分析方法处理原始光谱数据,可达到100%的鉴别准确率,但该方法需提供类别的先验知识。因此,采用近红外光谱技术和化学计量学相结合的手段可实现不同品种绿茶的快速无损鉴别。     

温控近红外光谱用于胺类化合物氢键相互作用研究

氢键对于蛋白质等生物分子的结构与功能具有重要影响.基于近红外光谱对含氢基团的高灵敏响应及其温度效应,研究了脂肪胺中氮氢基团的结构及相互作用.采用独立成分分析对不同温度、不同浓度样品的光谱进行分析,得到光谱中的三种独立成分,分别对应于氮氢基团的非氢键键合、线型氢键键合和环状氢键键合三种结构形式.随着温度的升高,两种键合形式的氮氢基团逐步转化为非氢键键合形式.环状键合的氮氢基团先解离为线型键合形式,再解离为非氢键键合形式.随着脂肪伯胺侧链的增长,NH基团的光谱吸收受温度影响减弱,且线型键合形式受温度的影响较环状键合形式小.     

近红外光谱和气相色谱-质谱联用分析烟用爆珠的研究

分别采用近红外光谱(NIRS)和气相色谱-质谱联用(GC-MS)法分析了3种不同类型烟用爆珠。收集了清甜型、蜜甜型和薄荷型3种类型烟用爆珠的不同批次共27个样品,采集其NIRS谱图,通过光谱数据分析结合簇类独立软模式法(Soft independent modeling of class analogy,SIMCA)对3种烟用爆珠样品建立了分类模型,采用线性判别分析法(Linear discriminant analysis,LDA)对同一类型不同批次的烟用爆珠进行质量一致性评价,同时采用GC-MS法对3种类型烟用爆珠内含物中挥发性及半挥发性成分进行了分析。结果表明,烟用爆珠香型不同,其内含物挥发性及半挥发性成分差别较大;NIRS技术可以有效判别不同颜色壁材的爆珠;建立的SIMCA模型可区分3种类型烟用爆珠,且清甜型、蜜甜型和薄荷型烟用爆珠不同批次样品的区分准确度均在90%以上,建立的LDA模型可很好地区分3种类型不同批次的烟用爆珠。     

CdS／聚电解质核-壳式复合微球的光谱特性研究

合成了CdS/聚电解质核-壳式复合微球并研究了其红外光谱、拉曼光谱和真空紫外光谱.在复合微球的红外光谱中出现的619.1 cm-1 Cd-S伸缩振动峰,与固态CdS相比出现了明显的蓝移现象.拉曼光谱中,与CdS特征纵光学声子模(1LO)相对应的299.4 cm-1也发生了蓝移现象.常温(290 K)和低温(20 K)下的真空紫外光谱存在差异.对于激发光谱,常温下主峰在269 nm,并有一些副峰,而低温下仅在253 nm处有1个明显的激发峰;常温下的发光峰在382 nm,并且有322、542和585 nm的副峰,而低温下则在394 nm处有明显的发光峰.这些结果说明CdS和聚电解质之间形成了包裹关系,并且具有很好的光学性能,可以作为荧光量子点标记材料.     

一种基于近红外光谱技术的不同品种及掺假三七的无损鉴别分析研究

基于近红外光谱技术与化学计量学方法,提出了一种不同品种及掺假三七的快速无损鉴别方法.分别采集景天三七、菊三七、血三七、田三七完整、粉末及掺假样品的近红外光谱,采用单一和组合预处理方法消除光谱中的干扰,筛选出最佳的预处理方法;结合主成分分析法建立不同品种以及掺假三七样品的鉴别模型.结果表明:结合主成分分析,采用原始光谱即...     

基于近红外光谱的维生素C片无损鉴别分析

基于近红外光谱技术与化学计量学方法,建立了一种国内外不同品牌维生素C片的无损鉴别方法。采集了国内外8个品牌的维生素C片共计40个样本的近红外光谱数据,比较了完整样品以及粉末样品的近红外光谱,采用连续小波变换技术消除背景干扰和基线漂移,基于标准偏差与相对标准偏差的变量筛选方法筛选出具有代表性的波数点,结合主成分分析方法对国内外不同品牌维生素C片进行鉴别分析。结果表明:原始光谱存在着明显的背景干扰和基线漂移现象,且粉末样品的重现性要优于完整样品;单纯使用原始光谱无法辨别来自不同品牌的维生素C片;连续小波变换可以有效消除背景干扰,提高模型鉴别能力;完整样品的鉴别准确率优于粉末样品,说明国内外不同品牌维生素C片主要成分基本一致,可能是辅剂和工艺上存在细微差异。通过结合近红外光谱分析技术与化学计量学方法,可实现对国产以及进口不同品牌维生素C片的鉴别分析。     

Crude Oil Model Emulsion Characterised by means of Near Infrared Spectroscopy and Multivariate Techniques

Water-in-oil emulsions are investigated by means of multivariate analysis of near infrared (NIR) spectroscopic profiles in the range 1100 — 2250 nm. The oil phase is a paraffin-diluted crude oil from the Norwegian Continental Shelf. The influence of water absorption and light scattering of the water droplets are shown to be strong. Despite the strong influence of the water phase, the NIR technique is still capable of predicting the composition of the investigated oil phase.     

In Line Monitoring of VAc-BuA Emulsion Polymerization Reaction in a Continuous Pulsed Sieve Plate Reactor using NIR Spectroscopy

Summary: This work deals with the in line and in situ monitoring of the changes in residual monomer concentrations and polymer particle size in the process of emulsion copolymerization of vinyl acetate (VAc) and butyl acrylate (BuA) over the sections of a novel tubular reactor (pulsed sieve plate continuous reactor, PSPC) using NIR spectroscopy. Off-line measurements (gas chromatographic, gravimetric and dynamic light scattering) were used as reference for the development of the multivariate PLS calibration model. All NIR spectra were on-line collected with an IFS 28/N Bruker spectrometer using a probe (transflectance mode) immersed into the reaction medium. The calibration model and validation data were analyzed using the OPUS/QUANT software. The results indicated that there exists a good agreement between values from the NIR calibration models and the off-line reference measured experimental data. Moreover, the on-line NIR can detect efficiently the occurrence of disturbances during the polymerization reaction, a useful tool for the improving the process safety.     

Multivariate pattern recognition of petroleum-based accelerants by solid-phase microextraction gas chromatography with flame ionization detection

A novel method has been developed for the extraction, analysis and identification of petroleum-based fuels using solid-phase microextraction with analysis by GC-FID. Multivariate data analysis is employed to simplify these data allowing for more accurate classification. Principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) are explored for their effectiveness in establishing accelerant groupings based on the current and previous ASTM International guidelines. The SIMCA models developed for the previous and current ASTM system were 98.5% and 97.2% accurate in unknown sample class prediction. SPME in conjunction with multivariate data analysis is a new approach in accelerant sampling and classification.     

Analyzing the Interaction between Anthocyanins and Native or Heat-Treated Whey Proteins Using Infrared Spectroscopy

The color stability of anthocyanins (ACN) has been shown to be improved by interaction with whey proteins (WP). In this study, we explore the ACN–WP interaction using Fourier transform infrared spectroscopy (IR). ACN from purple corn, grape, and black carrot (50 μM) were evaluated. IR spectra (4000–700 cm⁻¹) were collected for native and preheated (40–80 °C) WP (5 mg/mL) and ACN–WP mixtures at pH 7.4. Soft independent modeling of class analogy was used to analyze the IR data. The WP secondary structure changed after heat treatments and after interaction with ACN. As expected, the WP α-helices decreased, and β-sheet increased after heat treatment. The intensities of the WP amide I and II bands decreased after ACN addition, revealing a decrease in the WP α-helix content. Higher preheating temperatures (70–80 °C) resulted in a more disordered WP structure that favored stronger WP–ACN interactions related to amide III changes. Addition of ACN stabilized WP structure due to heat denaturation, but different ACN structures had different binding affinities with WP. WP structure had less change after interaction with ACN with simpler structures. These results increase our understanding of ACN–WP interactions, providing a potential strategy to extend anthocyanin color stability by WP addition.     

共聚物酸掺杂接枝聚苯胺的研究

采用核壳乳液聚合方法合成了以甲基丙酸甲酯、甲基丙烯酸和丙烯酸丁酯三元共聚物酸为核,聚苯胺为壳的导电高分子复合物。复合物的电导率随着聚苯胺含量的增加而升高。用粒径分析仪、ＴＥＭ、ＦＴ－ＩＲ和ＤＳＣ对复合材料进行了表征。结果表明形成了核壳结构,由于共聚物酸起到了掺杂剂的作用,使制得的复合物能在环己酮、四氢呋喃等普通有机溶剂中有好的溶解性。     

Enhanced Characterization of Naproxen Formulation by Near Infrared Spectroscopy

Near infrared spectroscopy in combination with appropriate chemometric methods is an effective technique for quantitative analysis of parameters of interest for the pharmaceutical industry. In this study, the artificial neural network (ANN) was applied to monitor critical parameters (compression force, tablet hardness, mean particle size, and active pharmaceutical ingredient concentration of tablets) in the process of naproxen pharmaceutical preparation. The performance of ANN was compared to linear methods (partial least squares regression (PLS) and synergy interval partial squares (siPLS)). The ANN models for compression force, tablet hardness, mean particle size, and active pharmaceutical ingredient concentration of tablets yielded the low root mean square error of prediction (RMSEP) values of 0.936 KN, 0.302 kg, 4.49 mg, and 2.14 µm, respectively. The predictive ability of the PLS model was improved by siPLS with selection of spectral regions and the best performance among all calibration methods was showed by the nonlinear method (ANN). Effective models were built by using these approaches using near infrared spectroscopy.     

近红外光谱在品质分析和定量分析中的应用

主要介绍近红外光谱在品质分析和定量分析中的一些应用，作为一种简单、快速、无损的检测手段，近红外光谱在鉴定原料的真伪、原料中有效成分的含量、有毒组分的识别等方面具有独特的效果。因此它在食品、药品、化工产品等领域得到了广泛应用。