声光可调-近红外光谱技术分析烟草主要化学成分

建立了声光可调-近红外光谱方法(AOTF-NIR)检测烟草主要化学成分的方法。应用AOTF-NIR光谱仪测定了不同地区、不同等级烟草样品的近红外光谱,用Unscrambler(定量分析软件将光谱与对应的化学成分值相关联,建立了烟草中总糖、还原糖、总烟碱和钾的回归模型。用这些模型对未知样品进行了预测。总糖、还原糖、总烟碱和钾模型预测的平均相对标准偏差分别为2.71%、3.13%、4.04%和6.42%。     

烟草组分的近红外光谱和支持向量机分析

测定了120个产自福建、安徽和云南烟草样品的近红外光谱. 在利用支持向量机(SVM)技术建立其定量、定性分析模型之前, 用小波变换技术对光谱变量进行了有效的压缩, 然后采用径向基核函数建立了75个烟草样品的分类模型, 同时建立了总糖、还原糖、烟碱和总氮4个组分的定量分析模型, 并利用45个烟草样品对模型进行了检验. 仿真实验表明, 建立的SVM分类模型分类准确率达到100%, 而4个组分的定量分析模型的预测决定系数(R2)、预测均方差(RMSEP)和平均相对误差(RME)3个指标值显示其模型泛化能力非常强, 预测效果良好, 可见这是一种有效的近红外光谱的建模分析方法.     

近红外光谱技术在快速检验制丝过程中烟丝质量均一性上的应用北大核心CSCD

采用近红外光谱技术结合主成分分析-马氏距离法研究了卷烟制丝工艺过程中掺配、加香、贮丝及喂丝等4个工序段中烟丝样品的质量均一性。用主成分分析法提取近红外光谱所包含的特征信息,较全面地反映制丝过程4个不同取样点样本的离散程度,马氏距离可反映制丝过程中烟丝质量的波动情况。此外,采用成品烟丝的模型预测了取样点D处烟丝样品中6种化学成分(总植物碱、总糖、还原糖、总氮、钾和氯)的含量,使不同批次的烟丝样品中化学成分的差异控制在合理范围,降低批次间卷烟产品化学成分含量的波动,能有效稳定品牌香烟的特征风格。     

近红外光谱技术用于花生油中棕榈油含量的测定

本文采用近红外光谱技术采集样品的近红外光谱数据,光谱经一阶求导后,采用偏最小二乘法(PLS)建立花生油中棕榈油含量的定标模型,并用交互验证法对模型进行了验证。模型相关系数为0.9963,校正均方根(RMSEC)为0.937。该模型应用于实际样品的检测,结果令人满意。     

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。     

近红外光谱分析模型传递简易方法研究

本文在不同时间安装的多台同型号近红外光谱仪上建立推进剂校正模型时,由于推进剂样品数量少且难于保存,新到仪器在建模时常遇到代表性样品数量严重不足.为此,提出将2台波长一致性好的近红外光谱仪器上采集的光谱组成一个混合校正样品光谱集,使用偏最小二乘法(PLS)建立模型的方法.结果表明,在用户缺少专业模型传递软件情况下,该方法...     

近红外光谱技术对烟草pH值的快速测定

提出了一种基于近红外漫反射光谱技术快速测定烟草pH值的方法.采集不同烟草粉末样品的近红外漫反射光谱,并对其原始光谱数据进行一阶微分、二阶微分及平滑等预处理,用偏最小二乘法(PLS)方法建立pH值预测模型(建模样品572个).从光谱主成分分布和pH值分布方面考察了81个验证集样品,结果表明验证集样品分布范围较大,分布较合理.利用主仪器模型对验证集样品进行预测,结果表明主仪器一阶微分模型和二阶微分模型对验证集样品的pH值预测与实际测量值的平均绝对偏差分别为0.057、0.065,t检验表明预测值和实测值之间没有显著性差异,达到了较好的结果.考察了主仪器pH值一阶微分、二阶微分模型在同一型号不同仪器间的直接转移效果,一阶微分模型转移给了子仪器A ～F,二阶微分模型转移给了子仪器G,7台子仪器pH值预测的平均绝对偏差为0.049 ～0.070,且都通过了F检验.实验表明,该主仪器模型能够快速预测烟叶中的pH值,并成功转移到同类仪器上进行检测.     

近红外光谱主成分-所有可能回归法定量分析烤烟、小麦样品中的组分含量

利用主成分-所有可能回归法,建立了烤烟、小麦样品不同组份的近红外光谱定量分析模型。结果表明,烤烟样品的总糖、还原糖以及小麦样品的蛋白质含量的预测模型均有好的定量分析结果,且其预测结果与PLS法预测结果相当。     

近红外光谱主成分—所有可能回归法定量分析烤烟,小麦样品中的组 …

利用主成分－所有可能回归法,建立了烤烟、小麦样品不同组份的近红外光谱定量分析模型。结果表明,烤烟样品的总糖、还原糖以及小麦蛋白质含量预测模型均有好的定量分析结果,县其预测结果与ＰＬＳ法预测结果相当。     

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。     

Improved calibration transfer between near-Infrared (NIR) spectrometers using canonical correlation analysis

The application of mobile near-infrared (NIR) spectrometers in field measurements is growing. Calibration transfer techniques offer simple solutions for enabling models constructed on benchtop instruments for use on mobile spectrometers. Since different types of spectrometers with different components, scanning ranges and resolutions cause great differences in the spectral response, calibration transfer is difficult to apply. In this paper, we focus on calibration transfer among benchtop, portable and handheld spectrometers by a method of calibration transfer based on canonical correlation analysis (CTCCA). Its capability was illustrated by the example of a group of NIR spectra dataset for predicting reducing sugars, total sugar, and nicotine contents in tobacco leaves. The experimental results showed that the transferability of CTCCA was superior to other conventional calibration transfer methods, including piecewise direct standardization, spectral space transformation, calibration transfer based on independent component analysis, and calibration transfer based on the weight matrix. Moreover, the best transfer results were obtained in the three cases by canonical correlation analysis method executing transfer while the spectra were not interpolated, which shows that this approach has the advantage of easy implementation for calibration transfer. Therefore, CTCCA without interpolation calculation offers a new and simple solution for transferring the spectra acquired by mobile spectrometers to the optimized spectral models built on benchtop devices to improve the accuracy of the results. Additionally, the results show that the benchtop spectrometer is more suitable as the master instrument for calibration transfer with more accurate prediction than using a portable device as the master.     

卷烟主流烟气粒相物中中性化学成分的全二维气相色谱飞行时间质谱(GC×GC-TOF MS)谱图特征识别

建立了全二维气相色谱-飞行时间质谱(GC×GC-TOF MS)分析卷烟主流烟气中中性化学成分的方法。以较长的弱极性柱HP-5MS(50 m×0.2 mm i.d.×0.33μm)作为第一维柱,较短的薄液膜中等极性柱DB-17MS(1.7 m×0.1 mm i.d.×0.1μm)作为第二维柱,对优质烟叶单料卷烟烟气的中性成分进行定性分析,经过人工纠错等分析初步鉴定出匹配度大于700的1 464种成分,重点讨论了中性香味羰基化合物全二维点阵的谱图特征,为烟气和复杂体系的深入研究提供了方法学基础。     

Quantitative analysis of routine chemical constituents in tobacco by near-infrared spectroscopy and support vector machine

It is important to monitor quality of tobacco during the production of cigarette. Therefore, in order to scientifically control the tobacco raw material and guarantee the cigarette quality, fast and accurate determination routine chemical of constituents of tobacco, including the total sugar, reducing sugar, Nicotine, the total nitrogen and so on, is needed. In this study, 50 samples of tobacco from different cultivation areas were surveyed by near-infrared (NIR) spectroscopy, and the spectral differences provided enough quantitative analysis information for the tobacco. Partial least squares regression (PLSR), artificial neural network (ANN), and support vector machine (SVM), were applied. The quantitative analysis models of 50 tobacco samples were studied comparatively in this experiment using PLSR, ANN, radial basis function (RBF) SVM regression, and the parameters of the models were also discussed. The spectrum variables of 50 samples had been compressed through the wavelet transformation technology before the models were established. The best experimental results were obtained using the (RBF) SVM regression with gamma=1.5, 1.3, 0.9, and 0.1, separately corresponds to total sugar, reducing sugar, Nicotine, and total nitrogen, respectively. Finally, compared with the back propagation (BP-ANN) and PLSR approach, SVM algorithm showed its excellent generalization for quantitative analysis results, while the number of samples for establishing the model is smaller. The overall results show that NIR spectroscopy combined with SVM can be efficiently utilized for rapid and accurate analysis of routine chemical compositions in tobacco. Simultaneously, the research can serve as the technical support and the foundation of quantitative analysis of other NIR applications.     

粒子群算法结合支持向量机回归法用于近红外光谱建模

研究了最小二乘法支持向量机(LSSVM)应用于烟丝样品和小麦样品的近红外光谱建模,采用粒子群优化算法(PSO)优化LSSVM的参数。通过对烟草样品和小麦样品的近红外光谱建模和预测,并与常规的偏最小二乘法(PLS)比较发现,PSO-LSSVM法具有更好的预测效果和稳健性。     

Towards a nondestructive chemical characterization of biofilm matrix by Raman microscopy

In this study, the applicability of Raman microscopy (RM) for nondestructive chemical analysis of biofilm matrix, including microbial constituents and extracellular polymeric substances (EPS), has been assessed. The examination of a wide range of reference samples such as biofilm-specific polysaccharides, proteins, microorganisms, and encapsulated bacteria revealed characteristic frequency regions and specific marker bands for different biofilm constituents. Based on received data, the assignment of Raman bands in spectra of multispecies biofilms was performed. The study of different multispecies biofilms showed that RM can correlate various structural appearances within the biofilm to variations in their chemical composition and provide chemical information about a complex biofilm matrix. The results of RM analysis of biofilms are in good agreement with data obtained by confocal laser scanning microscopy (CLSM). Thus, RM is a promising tool for a label-free chemical characterization of different biofilm constituents. Moreover, the combination of RM with CLSM analysis for the study of biofilms grown under different environmental conditions can provide new insights into the complex structure/function correlations in biofilms.     

NanoESI Mass Spectrometry of Rubisco and Rubisco Activase Structures and Their Interactions with Nucleotides and Sugar Phosphates

Ribulose bisphosphate carboxylase/oxygenase (Rubisco) is the protein that is responsible for the fixation of carbon dioxide in photosynthesis. Inhibitory sugar phosphate molecules, which can include its substrate ribulose-1,5-bisphosphate (RuBP), can bind to Rubisco catalytic sites and inhibit catalysis. These are removed by interaction with Rubisco activase (RA) via an ATP hydrolytic reaction. Here we show the first nanoESI mass spectra of the hexadecameric Rubisco and of RA from a higher plant (tobacco). The spectra of recombinant, purified RA revealed polydispersity in its oligomeric forms (up to hexamer) and that ADP was bound. ADP was removed by dialysis against a high ionic strength solution and nucleotide binding experiments showed that ADP bound more tightly to RA than AMP-PNP (a non-hydrolysable ATP analog). There was evidence that there may be two nucleotide binding sites per RA monomer. The oligomerization capacity of mutant and wild-type tobacco RA up to hexamers is analogous to the subunit stoichiometry for other AAA+ enzymes. This suggests assembly of RA into hexamers is likely the most active conformation for removing inhibitory sugar phosphate molecules from Rubisco to enable its catalytic competency. Stoichiometric binding of RuBP or carboxyarabinitol bisphosphate (CABP) to each of the eight catalytic sites of Rubisco was observed.     

GC-MS与正交投影法或渐进窗口正交投影法用于羌活挥发油成分的测定

中药化学组成的定性定量测定是药物活性理论的基础,联用色谱及其相关的化学计量学方法为中药复杂体系的分离和分辨提供了强有力的工具.采用GC-MS法对传统中药羌活中的挥发油成分进行了分离测定,并对其中重叠色谱峰根据其重叠程度,采用迭代的正交投影法(OPA)和非迭代的渐进窗口正交投影法(EWOP)进行了分辨,得到每个组分的纯色谱和光谱曲线,共分辨出98个色谱峰,通过质谱库检索得到其中65个组分的定性定量结果,占总含量的92.13%.     

Fingerprint developing of coffee flavor by gas chromatography-mass spectrometry and combined chemometrics methods

In this paper, chromatographic fingerprint was firstly used for quality control of tobacco flavors. Based on gas chromatography-mass spectrometry (GC-MS) and combined chemometrics methods, a simple, reliable and reproducible method for developing chromatographic fingerprint of coffee flavor, one of tobacco flavors, was described. Six coffee flavor samples obtained from different locations were used to establish the fingerprint. The qualitative and quantitative analysis of coffee flavor sample from Shenzhen was completed with the help of subwindow factor analysis (SFA). Fifty-two components of 68 separated constituents in coffee flavor sample from Shenzhen, accounting for 88.42% of the total content, were identified and quantified. Then, spectral correlative chromatography (SCC) was used to extract the common peaks from other five studied coffee flavor samples. Thirty-eight components were found to exist in all six samples. Finally, the method validation of fingerprint analysis was performed based on the relative retention time and the relative peak area of common peaks, sample stability and similarity analysis. The similarities of six coffee flavor samples were more than 0.9104 and showed that samples from different locations were consistent to some extent. The developed chromatographic fingerprint was successfully used to differentiate coffee flavor from coco flavor and some little difference sample prepared with coffee flavor and coco flavor by both similarity comparison and principal component projection analysis. The developed method can be used for quality control of coffee flavor.     

烤烟烟叶和烟梗的热裂解产物的研究

为了加深理解梗丝在卷烟叶组配方中的作用,对比研究了烤烟叶片和烟梗的化学组成以及它们在不同温度下的热裂解产物。一个改进后的热裂解装置被用来模拟卷烟的燃烧行为。采用热裂解仪研究了烤烟叶片和烟梗在大气环境中于300 ℃、600 ℃和900 ℃下的热裂解行为,并采用气相色谱-质谱联用仪对它们的热裂解产物进行分析。结果表明,烤烟烟叶和烟梗的热裂解产物种类随着热裂解温度的增加而增多;在相同热裂解温度条件下,烟叶的热裂解产物种类明显多于烟梗的热裂解产物。     

Application of Grey-correlated Spectral Region Selection in Analysis of Near-infrared Spectra

The optimal selection method of spectral region based on the grey correlation analysis was applied in the analysis of near-infrared(NIR) spectra. In order to compute “characteristic” spectral region, 160 samples of tobacco were surveyed by NIR. Next, the whole spectral region was randomly divided into six regions, and the values of association coefficients and correlation orders of different regions were computed for total sugar, reducing sugar and nicotine. Moreover, two regions that owned the largest value of association coefficient were regarded as “characteristic” spectral region of a model. Finally, the quantitative analysis models of different components were established via the partial least squares method, and the common selection methods of spectral region were compared. The simulation results indicate that the models to choose the spectral region based on grey correlation analysis are more effective than the common selection methods of spectral region, the optimized time of algorithm is shorter, the prediction precision of the models is higher and generalization ability for quantitative analysis results is stronger. This research can provide the support for the quantitative analysis models of NIR spectra and new idea for commercial analysis software of NIR. So, it has a high application value in the analysis of NIR spectra.