传统藏药五脉绿绒蒿不同居群红外光谱分析

利用正交试验对光谱采集条件进行了优化,优化所得中红外光谱采集条件为:样品KBr比例1:100 (m/m),粒径75μm,扫描次数32次,分辨率4 cm~(-1),压力1. 9×10~3kg。对17个不同居群五脉绿绒蒿的中红外及衰减全反射(ATR)数据进行分析,均得到了7个共有峰。吸光度聚类分析结果表明,中红外及ATR分析数据均可将17个居群分为3大类群,各居群的聚类情况均符合野外样点实际分布(S4除外)。除趋势对应分析(DCA)分析结果揭示了五脉绿绒蒿类群与生态环境之间的关系,纬度和海拔是影响五脉绿绒蒿不同类群红外光谱特征的主要环境因素。     

显微分光光度法与显微红外光谱综合方法在黑色中性笔字迹鉴定中的应用

以黑色中性笔字迹为研究对象,共收集10个不同厂家不同型号的样本56份,结合化学计量学的方法对黑色字迹样本的显微红外谱图和显微分光谱图进行处理.对显微红外谱图进行聚类分析和相似度比较,以区分不同成分的字迹;利用聚类分析,可将56份样本中的47份按成分不同分为6大类;利用相似度的概念,可对谱图的差异性进行量化;显微分光谱图主要进行色差计算,以区分不同色度的字迹;利用色差计算公式,计算两样品间的色差,共得1 596份色差数据,色差小于1的数据为31份,占全部比对样品的1.9%;将显微红外和显微分光分析结果进一步结合比对,可发现红外谱图聚为一类的样本之间有较大的色差,而色差很小的样本其红外谱图有较大差异,从而可将56份黑色字迹区分,为字迹的鉴定提供了新思路和新方法.     

红外光谱法对PC/ABS材料共混比例进行半定量

采集不同PC/ABS(聚碳酸酯/丙烯腈-丁二烯-苯乙烯共聚物)共混比例样品的红外谱图形成学习集。将学习集相同共混比样品的红外谱图平均后,得到该共混比样品红外谱图的特征。将待测样品与平均后的特征进行匹配,进行分类从而达到半定量的目的。通过测试未知样品,对模型的准确性进行了验证,实际分析结果表明,该方法可以准确对不同共混比例的PC/ABS样品进行分类。     

分析测试新成果(238~242)电线塑料护套的傅立叶变换红外光谱分析

采用傅立叶变换红外光谱法对21个5种不同颜色的电线塑料护套样品进行了分析.从红外光谱图中可观察到样品特征峰的峰数、峰位、相对峰面积比均有差异,但可以归纳为两大类.其中同种颜色的不同样品在红外谱图中又反映出了不同的信息,这表明在外观颜色十分相近的情况下,采用此方法能够有效的为刑事案件现场遗留的各种塑料制品提供鉴别与比对.     

红外光谱法直接鉴别苦丁茶的研究

本文利用傅立叶变换红外光谱(FTIR)法快速、直接地测定了11种苦丁茶,并对所获得的指纹图谱进行特征峰指认和对比分析。结果表明:各种苦丁茶化学成分相同,而由于各成分间的相对含量的不同,使每种样品都有自己独特的红外谱图,不同产地、不同级别苦丁茶的红外吸收频率、吸收峰的相对强度都存在比较大的差异。同时还运用傅立叶变换红外光谱技术对不同产地、不同级别苦丁茶的混合化学体系进行了全组分快速分析,为苦丁茶的鉴别及质量控制提供了可靠的依据。     

不同产地黄芪的红外光谱鉴别研究

采用红外光谱、二阶导数红外光谱和二维相关红外光谱,对四种不同产地的黄芪原药材进行了鉴别研究。结果表明:不同产地黄芪的红外光谱和二阶导数红外谱具有一定的相似度,与淀粉的红外谱图比对,4个不同产地的黄芪均含有淀粉,其中陕西绥德产黄芪的淀粉含量比其它3个产地黄芪的都要高。山西浑源和山西天镇产黄芪谱图的1 510、1 425cm-1木质素特征峰比内蒙古固阳和陕西绥德产黄芪的更为明显,说明前二者产黄芪中木质素含量高于后二者产黄芪。在二维相关红外谱图上,根据4个产地黄芪的相对峰强度的差异,可进行产地的鉴别。研究结果表明对于不同产地黄芪的鉴别,红外三级鉴定法是一种快速有效的新方法。     

衰减全反射红外光谱法测定电工胶带粘合剂

采用衰减全反射傅里叶变换红外光谱法(ATR-FTIR)对31个品牌电工胶带的粘合剂进行分析,通过红外特征吸收峰确定粘合剂的主要成分均为天然橡胶和丁苯橡胶混合物,不同品牌的样品通过红外光谱定性分析无法区分。通过OPUS软件分别选择天然橡胶和丁苯橡胶的红外特征吸收峰进行峰面积积分,计算两种物质特征峰面积的相对比例,采用单因素方差分析确定不同样品天然橡胶和丁苯橡胶特征峰面积的相对比例是否存在统计学差异,然后采用最小显著性差异法进行验后多重比较,分析特征峰面积相对比例存在统计学差异的品牌。31个品牌电工胶带组成的465组样品对中有422组可以区分,区分率达到90.8%。结果表明,通过红外光谱定量分析可实现不同品牌电工胶带粘合剂的区分。     

独立成分分析结合在线红外技术研究3,4-双(4'-氨基呋咱基-3')氧化呋咱的合成反应机理

利用在线红外技术监测3,4-双(4'-氨基呋咱基-3')氧化呋咱(DATF)的合成过程,并结合核独立成分分析算法对反应过程中获得的实时红外光谱数据进行解析,得到了反应物、中间体及产物各组分纯物质的红外光谱图.采用密度泛函理论B3LYP法,在6-31+G(d,p)基组水平上求得中间体的红外振动光谱,验证了所分离红外光谱图的正确性,从而推导出合理的合成反应机理.结果表明,核独立成分分析算法能合理地解析红外光谱在线数据,并有效捕捉合成反应的中间体,对合成反应机理的研究具有重要的指导意义.     

PBT/PEG型聚醚酯的鉴定

采用红外光谱、核磁共振和DSC热分析手段对一种未知聚合物样品进行表征。通过对样品红外谱图的吸收峰位和强度及对其核磁共振氢谱中各质子化学位移归属的分析,判明该样品为PBT/PEG型聚醚酯弹性体,且不含游离的聚乙二醇组分。样品的DSC测试表明其与PBT/PEG型聚醚酯的热行为较相符。该分析为此类聚合物提供了一种简单、快速且结果可靠的鉴定方法。     

常见黑色玉石的红外反射光谱测试及鉴定

红外光谱检测技术具有准确、快速、简便、无损等优点,广泛应用于不同领域.在宝石学领域,对于宝玉石的鉴定具有重要意义.本文以市场上常见的六种黑色玉石为实验测试样品,除常规检测外,采用红外反射光谱方法,得出对应的红外反射光谱图,分析比较它们的差异不同,达到有针对性的快速区分鉴定宝玉石种属的目的.     

Application of HPTLC Multiwavelength Imaging and Color Scale Fingerprinting Approach Combined with Multivariate Chemometric Methods for Medicinal Plant Clustering According to Their Species

In the current study, multiwavelength detection combined with color scales HPTLC fingerprinting procedure and chemometric approach were applied for direct clustering of a set of medicinal plants with different geographical growing areas. The fingerprints profiles of the hydroalcoholic extracts obtained after single and double development and detection under 254 nm and 365 nm, before and after selective spraying with specific derivatization reagents were evaluated by chemometric approaches. Principal component analysis (PCA) with factor analysis (FA) methods were used to reveal the contribution of red (R), green (G), blue (B) and, respectively, gray (K) color scale fingerprints to HPTLC classification of the analyzed samples. Hierarchical cluster analysis (HCA) was used to classify the medicinal plants based on measure of similarity of color scale fingerprint patterns. The 1-Pearson distance measurement with Ward’s amalgamation procedure proved to be the most convenient approach for the correct clustering of samples. Data from color scale fingerprints obtained for double development procedure and multiple visualization modes combined with appropriate chemometric methods proved to detect the similar medicinal plant extracts even though they are from different geographical regions, have different storage conditions and no specific markers are individually extracted. This approach could be proposed as a promising tool for authentication and identification studies of plant materials based on HPTLC fingerprinting analysis.     

Geographical classification of Epimedium based on HPLC fingerprint analysis combined with multi‐ingredients quantitative analysis

A reliable and comprehensive method for identifying the origin and assessing the quality of Epimedium has been developed. The method is based on analysis of HPLC fingerprints, combined with similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) and multi‐ingredient quantitative analysis. Nineteen batches of Epimedium , collected from different areas in the western regions of China, were used to establish the fingerprints and 18 peaks were selected for the analysis. Similarity analysis, HCA and PCA all classified the 19 areas into three groups. Simultaneous quantification of the five major bioactive ingredients in the Epimedium samples was also carried out to confirm the consistency of the quality tests. These methods were successfully used to identify the geographical origin of the Epimedium samples and to evaluate their quality.     

Comprehensive Metabolite Profiling in Genetic Resources of Garlic (Allium sativum L.) Collected from Different Geographical Regions

Garlic (Allium sativum) is the second most important Allium crop that has been used as a vegetable and condiment from ancient times due to its characteristic flavor and taste. Although garlic is a sterile plant that reproduces vegetatively through cloves, garlic shows high biodiversity, as well as phenotypic plasticity and environmental adaptation capacity. To determine the possible mechanism underlying this phenomenon and to provide new genetic materials for the development of a novel garlic cultivar with useful agronomic traits, the metabolic profiles in the leaf tissue of 30 garlic accessions collected from different geographical regions, with a special focus on the Asian region, were investigated using LC/MS. In addition, the total saponin and fructan contents in the roots and cloves of the investigated garlic accessions were also evaluated. Total saponin and fructan contents did not separate the garlic accessions based on their geographical origin, implying that saponin and fructan contents were clone-specific and agroclimatic changes have affected the quantitative and qualitative levels of saponins in garlic over a long history of cultivation. Principal component analysis (PCA) and dendrogram clustering of the LC/MS-based metabolite profiling showed two major clusters. Specifically, many Japanese and Central Asia accessions were grouped in cluster I and showed high accumulations of flavonol glucosides, alliin, and methiin. On the other hand, garlic accessions grouped in cluster II exhibited a high accumulation of anthocyanin glucosides and amino acids. Although most of the accessions were not separated based on country of origin, the Central Asia accessions were clustered in one group, implying that these accessions exhibited distinct metabolic profiles. The present study provides useful information that can be used for germplasm selection and the development of new garlic varieties with beneficial biotic and abiotic stress-adaptive traits.     

Fingerprint Analysis of Eucommia Bark by LC-DAD and LC-MS with the Aid of Chemometrics

Chromatographic fingerprints of 46 Eucommia Bark samples were obtained by liquid chromatography-diode array detector (LC-DAD). These samples were collected from eight provinces in China, with different geographical locations, and climates. Seven common LC peaks that could be used for fingerprinting this common popular traditional Chinese medicine were found, and six were identified as substituted resinols (4 compounds), geniposidic acid and chlorogenic acid by LC-MS. Principal components analysis (PCA) indicated that samples from the Sichuan, Hubei, Shanxi and Anhui—the SHSA provinces, clustered together. The other objects from the four provinces, Guizhou, Jiangxi, Gansu and Henan, were discriminated and widely scattered on the biplot in four province clusters. The SHSA provinces are geographically close together while the others are spread out. Thus, such results suggested that the composition of the Eucommia Bark samples was dependent on their geographic location and environment. In general, the basis for discrimination on the PCA biplot from the original 46 objects× 7 variables data matrix was the same as that for the SHSA subset (36 × 7 matrix). The seven marker compound loading vectors grouped into three sets: (1) three closely correlating substituted resinol compounds and chlorogenic acid; (2) the fourth resinol compound identified by the OCH₃ substituent in the R4 position, and an unknown compound; and (3) the geniposidic acid, which was independent of the set 1 variables, and which negatively correlated with the set 2 ones above. These observations from the PCA biplot were supported by hierarchical cluster analysis, and indicated that Eucommia Bark preparations may be successfully compared with the use of the HPLC responses from the seven marker compounds and chemometric methods such as PCA and the complementary hierarchical cluster analysis (HCA).     

Comprehensive classification of USA cannabis samples based on chemical profiles of major cannabinoids and terpenoids

Abstract

Different USA-origin cannabis samples were analyzed by GC-FID to quantify all possible cannabinoids and terpenoids prior to their clustering. Chromatographic analysis confirmed the presence of seven cannabinoids and sixteen terpenoids with variable levels. Among tested cannabinoids, Δ⁹-Tetrahydrocannabinol Δ⁹-THC and cannabinol CBN were available in excess amounts (1.2–8.0?wt%) and (0.22–1.1?wt%), respectively. Fenchol was the most abundant terpenoid with a range of (0.03–1.0?wt%). The measured chemical profile was used to cluster 23 USA states and to group plant samples using different unsupervised multivariate statistical tools. Clustering of plant samples and states was sensitive to the selected cannabinoids/terpenoids. Principal component analysis (PCA) indicated the importance of Δ⁹-THC, CBN, CBG, CBC, THCV, Δ⁸-THC, CBL, and fenchol for samples clustering. Δ⁹-THC was significant to separate California-origin samples while CBN and fenchol were dominant to separate Oregon-origin samples away from the rest of cannabis samples. A special PCA analysis was performed on cannabinoids after excluding Δ⁹-THC (due to its high variability in the same plant) and CBN (as a degradation byproduct for THC). Results indicated that CBL and Δ⁸-THC were necessary to separate Nevada and Washington samples, while, CBC was necessary to isolate Oregon and Illinois plant samples. PCA based on terpenoids content confirmed the significance of caryophyllene, guaiol, limonene, linalool, and fenchol for clustering target. Fenchol played a major role for clustering plant samples that originated from Washington and Nevada. k-means method was more flexible than PCA and generated three different classes; samples obtained from Oregon and California in comparison to the rest of other samples were obviously separated alone, which attributed to their unique chemical profile. Finally, both PCA and k-means were useful and quick guides for cannabis clustering based on their chemical profile. Thus, less effort, time, and materials will be consumed in addition to decreasing operational conditions for cannabis clustering.     

基于三维荧光特性的汽油聚类分析

应用三维荧光光谱法研究了90#、93#及97#3种汽油纯样品以及它们的相互掺杂样品的荧光特性。选取激发波长(λex)为330nm,发射波长(λem)在340～500nm间的荧光强度数据,用主成分聚类分析法作了研究。结果表明:所得的荧光数据分为三类,属90#汽油样品的数据为一类,处于第Ⅰ象限中;属97#汽油样品为第二类,处于第Ⅲ象限;属93#汽油样品为第三类,处于第Ⅳ象限。在第Ⅰ及第Ⅳ象限中的荧光数据又分为二类,一类为纯品油样,另一类为混杂油样。因此,根据聚类分析结果可方便地对不同标号的汽油加以区别。而且根据纯品汽油样品与混杂油样品的试验点之间的距离可推测油样中混杂组分量的多少。     

Quality assessment of cortex cinnamomi by HPLC chemical fingerprint, principle component analysis and cluster analysis

HPLC fingerprint analysis, principle component analysis (PCA), and cluster analysis were introduced for quality assessment of Cortex cinnamomi (CC). The fingerprint of CC was developed and validated by analyzing 30 samples of CC from different species and geographic locations. Seventeen chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression of the HPLC fingerprints. The correlation coefficients of similarity in chromatograms were higher than 0.95 for the same species while much lower than 0.6 for different species. Besides, two principal components (PCs) have been extracted by PCA. PC1 separated Cinnamomum cassia from other species, capturing 56.75% of variance while PC2 contributed for their further separation, capturing 19.08% variance. The scores of the samples showed that the samples could be clustered reasonably into different groups corresponding to different species and different regions. The scores and loading plots together revealed different chemical properties of each group clearly. The cluster analysis confirmed the results of PCA analysis. Therefore, HPLC fingerprint in combination with chemometric techniques provide a very flexible and reliable method for quality assessment of traditional Chinese medicines.     

Synergistic effect of the simultaneous chemometric analysis of H NMR spectroscopic and stable isotope (SNIF-NMR,O, C) data: Application to wine analysis

It is known that ¹H NMR spectroscopy represents a good tool for predicting the grape variety, the geographical origin, and the year of vintage of wine. In the present study we have shown that classification models can be improved when ¹H NMR profiles are fused with stable isotope (SNIF-NMR, ¹⁸O, ¹³C) data. Variable selection based on clustering of latent variables was performed on ¹H NMR data. Afterwards, the combined data of 718 wine samples from Germany were analyzed using linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), factorial discriminant analysis (FDA) and independent components analysis (ICA). Moreover, several specialized multiblock methods (common components and specific weights analysis (ComDim), consensus PCA and consensus PLS-DA) were applied to the data.     

Nonlinear mapping technique for data visualization and clustering assessment of LIBS data: application to ChemCam data

ChemCam is a remote laser-induced breakdown spectroscopy (LIBS) instrument that will arrive on Mars in 2012, on-board the Mars Science Laboratory Rover. The LIBS technique is crucial to accurately identify samples and quantify elemental abundances at various distances from the rover. In this study, we compare different linear and nonlinear multivariate techniques to visualize and discriminate clusters in two dimensions (2D) from the data obtained with ChemCam. We have used principal components analysis (PCA) and independent components analysis (ICA) for the linear tools and compared them with the nonlinear Sammon’s map projection technique. We demonstrate that the Sammon’s map gives the best 2D representation of the data set, with optimization values from 2.8% to 4.3% (0% is a perfect representation), together with an entropy value of 0.81 for the purity of the clustering analysis. The linear 2D projections result in three (ICA) and five times (PCA) more stress, and their clustering purity is more than twice higher with entropy values about 1.8. We show that the Sammon’s map algorithm is faster and gives a slightly better representation of the data set if the initial conditions are taken from the ICA projection rather than the PCA projection. We conclude that the nonlinear Sammon’s map projection is the best technique for combining data visualization and clustering assessment of the ChemCam LIBS data in 2D. PCA and ICA projections on more dimensions would improve on these numbers at the cost of the intuitive interpretation of the 2D projection by a human operator.     

FTIR聚类分析结合差热分析法应用于中药材延胡索表征的研究

采用傅里叶变换红外光谱法（FTIR）对不同品种的大叶、小叶延胡索及非正品延胡索进行了直接测定,并用FTIR聚类分析并结合差热分析法（DTA）对延胡索正品的不同品种及与非正品的亲缘关系进行了研究。FTIR聚类分析结果显示5个样品分为4组,大叶、小叶延胡索为一组,齿瓣元胡、东北元胡和土元胡各为一组;差热分析结果显示正品延胡索品种与非正品延胡索的DTA曲线有很明显的区别。所提出方法可有效地鉴别亲缘关系相近的中药材植物。