直接鉴别延胡索及其伪品的FTIR-主成分分析法研究

采用傅里叶变换红外光谱直接测定法测定了延胡索及其伪品齿瓣元胡、东北延胡索、土元胡、新疆延胡索及夏天无的傅里叶变换红外光谱,采用主成分析法比较了正伪品之间的差异程度.结果表明基于傅里叶变换红外光谱的主成分分析在反映同属不同种植物化学组成差异程度上具有应用价值.     

PCA-LVQ法及其在RS-FTIR大气环境监测数据处理中的应用

将主成分分析(PCA)用于遥感傅里叶变换红外光谱(Remote Sensing Fourier Transform Infrared:RS-FTIR)的特征提取,结合学习矢量量化(LVQ)神经网络,实现了PCA-LVQ对大气中的8组分混合体系进行快速定性分析的建模方法。并与单纯的LVQ神经网络、反向传播人工神经网络(BP-ANN)得到的结果进行了比较。PCA-LVQ显示出较好的处理数据的能力,它不仅提高了运算速度,而且提高了模型的预测准确度,分类精度达到91.7%。PCA-LVQ的这一预测精度及运算速度,足以满足遥感傅里叶变换红外光谱对大气中有毒气体的实时、在线监测的需要。     

健康和病变关节软骨的傅里叶变换红外光谱显微成像及Fisher判别

傅里叶变换红外光谱显微成像(FTIRI)可同时获得样品的红外光谱和形貌信息,其与化学计量学方法结合,可实现生物组织中主成分含量及分布的定量研究.本研究采用FTIRI技术结合主成分分析(PCA)以及Fisher判别算法对正常和病变的关节软骨进行鉴别分析.对关节软骨切片进行实现FTIR扫描及光谱分析,再利用SPSS软件对软骨的光谱(矩阵)进行主成分分析,根据主成分得分矩阵构造分类函数,结合Fisher判别算法对样本进行分类识别.正常和病变的关节软骨样品识别准确率高达95.7％(初始案例)和94.3％(交互验证案例).本方法可准确有效地辨别关节软骨是否发生病变,为监测骨关节炎的发生和修复提供参考.     

不同产地鲍鱼的FTIR谱图分析

为了寻找能够鉴别不同产地鲍鱼成分差异的新方法,利用傅里叶变换红外光谱(FTIR)测定不同产地的鲍鱼样品,对所获得的指纹图谱进行对比分析,初步探讨鲍鱼区域性之间的差别.结果表明:这3个产地鲍鱼红外吸收峰的峰数、峰位、峰形、峰强都存在一定程度的差异,为鉴别鲍鱼产地提供了一种有效的手段.     

快速傅里叶变换电化学弛豫测定法简介

由于傅里叶变换谱学有许多突出优点,它引起了现代化学家的很大注意。现代谱学中的傅里叶变换核磁共振(FT-NMR),傅里叶变换红外光谱(FT-IR),傅里叶变换质谱(FT-MS)等技术国内外已有许多文献介绍。最近电化学也出现了快速傅里叶变换电化学弛豫测定法(FFT-ERM),它对于研究电化学动     

正常与癌症肺组织的傅里叶变换红外光谱差异的研究

傅里叶变换红外(FTIR)光谱可以在分子水平上研究细胞和组织等复杂的生命体系,提供分子结构和组成的信息.我们发展了一种用于直接测定肿瘤及正常组织红外光谱的方法,对16例肺癌及其癌旁正常组织进行了测定.结果表明,对于正常和癌变的肺组织,FTIR光谱中存在显著差异,相关谱带的相对峰高比可以表征这些差异.因此,傅里叶变换红外光谱可以用来诊断癌症与正常的肺组织,有望成为肿瘤快速诊断的新方法.     

红外光谱结合贝叶斯判别对洗发用品的分类研究

建立一种基于红外光谱的快速无损地检验洗发用品的分析方法。利用傅里叶红外光谱对60个常见的洗发用品样品进行检验,分别采用Savitzky-Golay(S-G)平滑、快速傅里叶变换(FFT)、降噪等方法对光谱数据进行预处理,并结合主成分分析法对光谱数据进行降维处理。同时建立多层感知器神经网络和贝叶斯判别分析两种分类模型,对光谱数据进行分析验证。多层感知器神经网络对原始数据、经过S-G平滑、FFT、降噪后的分类准确率分别为86.67%、88.33%、80%、90%,贝叶斯判别的分类准确率为83.33%、85%、83.33%、95%。结果显示,降噪处理效果较佳,贝叶斯判别具有更高的准确率。该方法重现性好、样品用量少、无损样品,可为洗发用品类物证鉴定提供科学依据。     

傅里叶变换中红外光谱法检测脑胶质瘤

采用傅里叶变换衰减全反射中红外光谱法检测了19例液氮冻存的脑胶质瘤离体组织样品(星形细胞瘤10例, 少枝-星形细胞瘤9例), 对得到的红外光谱进行分析发现, 恶性程度不同的星形细胞瘤组织的红外光谱存在差异, 并且不同类型的脑胶质瘤组织的红外光谱也表现出较为明显的区别, 因此可以根据各个特征吸收峰的峰位、 峰形及谱峰强度等信息来区分脑胶质瘤, 并初步鉴别脑胶质瘤的性质. 研究结果表明, 通过某些特征吸收峰峰位的变化来鉴别星形细胞瘤和少枝-星形细胞瘤与病理诊断结果的符合率约为80%, 说明傅里叶变换衰减全反射中红外光谱法有望发展成为一种对样品无损伤、 快速的脑肿瘤诊断新方法.     

二维相关红外光谱法与阿胶的真伪鉴别

采用傅里叶变换红外光谱法(FT-IR)和二维相关红外光谱技术(2D-IR)对几种阿胶进行了真伪鉴别。实验结果表明,伪品阿胶和黄明胶与标本东阿阿胶的谱图较为相似,尤其是黄明胶与阿胶极其相似,仅仅在1648cm^-1的酰胺I带的吸收峰和东阿阿胶有9个波数的区别;不同批次和厂家的正品阿胶的红外光谱图更为相似,难以区分开,借助于二维相关红外光谱法,获取了物质的微观结构信息,提高了谱图的分辨率,几种真品阿胶得到了直观有效的鉴别。     

基于化学模式识别的大蒜傅里叶变换红外光谱指纹图谱多样性

以不同地理居群的大蒜为研究对象,采用傅里叶变换红外光谱法获取各样品的红外谱图及不同波数下各样品的透过率数据,运用主成分分析及聚类分析等统计学方法对谱图数据进行了比较分析。结果发现,不同地理居群大蒜的红外指纹图谱存在差异,统计学分析结果显示25个品种大致可分为4大类(其中2个样品,4号及25号与这4类间有较大差异),此现象一定程度上反映了大蒜种植地居群环境对大蒜理化性质的影响。     

Classification of the biological material with use of FTIR spectroscopy and statistical analysis

Rapid detection and discrimination of dangerous biological materials such as bacteria and their spores has become a security aim of considerable importance. Various analytical methods, including FTIR spectroscopy combined with statistical analysis have been used to identify vegetative bacteria, bacterial spores and background interferants. The present work discusses the application of FTIR technique performed in reflectance mode using Horizontal Attenuated Total Reflectance accessory (HATR) to the discrimination of biological materials. In comparison with transmission technique the HATR is more rapid and do not require the sample destruction, simultaneously giving similar absorbance bands. HATR-FTIR results combined with statistical analysis PCA and HCA demonstrate that this combination provides novel and accurate microbial identification technique.     

Simple and Sensitive Voltammetric Determination of Esculetin Using Electrochemically Reduced Graphene Oxide Modified Electrode

A simple and sensitive voltammetric sensor for esculetin, based on electrochemically reduced graphene oxide film modified glassy carbon electrode, was reported for the quantitative determination of esculetin in the Chinese traditional herbal drug Viola yedoensis Makino. Electrochemical impedance spectroscopy and scanning electron microscopy were employed to study the characteristic of the graphene oxide film. The electrochemical behavior of esculetin on this sensor was investigated in pH 3.0 phosphate buffer solution by cyclic voltammetry. Significant advantages were achieved by the excellent conductivity and the high surface‐to‐volume ratio of electrochemically reduced graphene oxide. A calibration plot of oxidation peak currents versus esculetin concentrations was linear in the range of 4.0 ξ 10^‐8 mol L^‐1 to 5.0 ξ 10^‐6 mol L^‐1 with a detection limit of 2.0 ξ 10^‐8 mol L^‐1. The practical application of the present sensor was demonstrated by determining the concentration of esculetin in real sample with no interference.     

中药紫花地丁黄酮碳苷类化学成分的超高效液相色谱-电喷雾离子源-四极杆飞行时间串联质谱研究

采用超高效液相色谱-电喷雾离子源-四极杆飞行时间串联质谱(UPLC-ESI-QTOF-MS/MS)方法,以中药紫花地丁中分离得到的5个黄酮碳苷化合物为对照品,研究了黄酮二糖碳苷类化合物在ESI-QTOF-MS/MS质谱中的裂解规律。研究进一步证实了文献报道的黄酮二糖碳苷C-6位取代糖基较C-8位糖更易优先发生裂解;但同时发现结构中如果含有不稳定构象的糖基取代时,该规律不再适用。通过对照品的质谱裂解规律,并结合文献和高分辨质谱数据,成功表征和鉴定了紫花地丁中21个黄酮二糖碳苷类以及4个黄酮氧苷类成分。该方法能快速、灵敏、准确地对中药中微量黄酮碳苷类成分的结构进行表征和鉴定。     

Flavone C-glycosides from Viola yedoensis MAKINO

A new flavone C-glycoside, apigenin 6-C-alpha-L-arabinopyranosyl-8-C-beta-L-arabinopyranoside, has been isolated from Viola yedoensis together with the known compounds, apigenin 6,8-di-C-alpha-L-arabinopyranoside, apigenin 6-C-alpha-L-arabinopyranosyl-8-C-beta-D-glucopyranoside (isoschaftoside), apigenin 6-C-beta-D-glucopyranosyl-8-C-alpha-L-arabinopyranoside (schaftoside), apigenin 6-C-beta-D-glucopyranosyl-8-C-beta-L-arabinopyranoside (neoschaftoside), apigenin 6,8-di-C-beta-D-glucopyranoside (vicenin-2), apigenin 6-C-alpha-L-arabinopyranosyl-8-C-beta-D-xylopyranoside, apigenin 6-C-beta-D-xylopyranosyl-8-C-alpha-L-arabinopyranoside, luteolin 6-C-beta-D-glucopyranoside (isoorientin) and luteolin 6-C-alpha-L-arabinopyranosyl-8-C-beta-D-glucopyranoside (isocarlinoside). The structures were determined by spectroscopic methods and new or revised (1)H- and (13)C-NMR spectral assignments are proposed for some compounds.     

偏最小二乘法在红外光谱识别茶叶中的应用

采用漫反射傅立叶变换红外光谱(FTIR)法结合主成分分析(PCA)、偏最小二乘法(PLS)、簇类的独立软模式(SIMCA)识别法对十三种茶叶进行了分类判别研究。研究结果表明,通过多元散射校正(MSC)对原始光谱进行预处理,可以提高模式识别技术的分类判别效果。在此基础上,选取1 900~900 cm-1波长范围内的茶叶红外光谱建立识别模型,三种方法都得到了满意的分类判别效果。在对检验集中全部130个样本的判别中,PCA仅有两类样本无法判别,SIMCA的识别率和拒绝率都在90%以上,而PLS的识别效果最佳,全部样本都得到了正确的归类。这一研究结果表明傅立叶变换红外光谱法与化学计量学方法相结合可以实现茶叶品种的快速鉴别,这为茶叶的客观评审提供了一种新思路。     

一种新颖的基于FTIR-CWT及ANN分类法的同科属中药材菟丝子与金灯藤的识别研究

采用水平衰减全反射傅里叶变换红外光谱法（HATR-FTIR）测定了同属种子植物中药材菟丝子及金灯藤的FTIR,运用基于连续小波多分辨率分析法对吸收较为相似的菟丝子及金灯藤的FTIR进行特征提取。选择第7、10、13分解层数的特征向量,进行人工神经网络（ANN）训练,再用训练出来的网络对不同产地的植物种子菟丝子和金灯藤所得FTIR小波提取的特征向量进行分类。通过对32个不同样本的验证,说明能够采用基于FTIR-连续小波特征提取及人工神经网络分类法对同科属中药材菟丝子与金灯藤进行识别。     

Classification of Rat FTIR Colon Cancer Data Using Waveletsand BPNN

本文提出了一种新的基于水平衰减全反射-傅里叶变换红外光谱（HATR-FTIR）的小波特征提取与反向传播人工神经网络模式分类方法以提高FTIR对早期大鼠结肠癌的诊断准确率．对60只DMH诱导的SD大鼠,44只诱导鼠的第二代鼠,36只正常SD大鼠的结肠正常组织、异常增生、早癌及进展期癌组织所获得的的HATR-FTIR,利用连续小波多尺度分析法提取12个特征量,采用反向传播人工神经网络进行分类,识别准确率分别为100%、94%、97.5%及100%．实验结果表明此方法对早期结肠癌具有较高的诊断率．     

Lignans,flavonoids and coumarins from Viola philippica and their α-glucosidase and HCV protease inhibitory activities

Two lignans including a new one, five flavonoids and five coumarins were isolated from the whole plant of Viola philippica (synonymised as Viola yedoensis Makino). The new compound was structurally determined as (7R,8S,8′S) -3,3′-dimethoxy- 4,4′,9-trihydroxy- 7,9′-epoxy-8,8′-lignan 9-O-rutinoside by analysis of its NMR, MS and CD spectroscopic data. The known compounds were characterised by comparing their NMR and MS data with those reported. Among the known compounds, 5-hydroxy-4′-methoxyflavone-7-O- rutinoside, 6,7-di-O-β-D- glucopyranosylesculetin, and 7R,8S-dihydrodehydrodiconiferyl alcohol 4-O-β-D- glucopyranoside were isolated and identified from this genus for the first time. Of these compounds, 5-hydroxy-4′-methoxyflavone-7-O-rutinoside and (7R,8S,8′S) -3,3′-dimethoxy- 4,4′,9-trihydroxy- 7,9′-epoxy-8,8′-lignan 9-O-rutinoside were potently active against α-glucosidase, while the two dimeric coumarins, 5, 5′-bi (6, 7-dihydroxycoumarin) and 6,6′,7,7′-tetrahydroxy-5,8′-bicoumarin potently inhibited HCV protease.     

Comprehensive Evaluation of Amino Acids and Polyphenols in 69 Varieties of Green Cabbage (Brassica oleracea L. var. capitata L.) Based on Multivariate Statistical Analysis

The biological activities of the primary metabolites and secondary metabolites of 69 green cabbage varieties were tested. The LC-MS detection method was used to determine the content of 19 free amino acids (lysine, tryptophan, phenylalanine, methionine, threonine, isoleucine, leucine, valine, arginine, asparagine, glycine, proline, tyrosine, glutamine, alanine, aspartic acid, serine, and glutamate). The content of 10 polyphenols (chlorogenic acid, gallic acid, 4-coumaric acid, ferulic acid, gentisic acid, cymarin, erucic acid, benzoic acid, rutin, and kaempferol) was determined by the HPLC detection method. Considering the complexity of the data obtained, variance analysis, diversity analysis, correlation analysis, hierarchical cluster analysis (HCA), and principal component analysis (PCA) were used to process and correlate amino acid or polyphenol data, respectively. The results showed that there were significant differences between the different amino acids and polyphenols of the 69 cabbage varieties. The most abundant amino acids and polyphenols were Glu and rutin, respectively. Both amino acids and polyphenols had a high genetic diversity, and multiple groups of significant or extremely significant correlations. The 69 cabbage varieties were divided into two groups, according to 19 amino acid indexes, by PCA. Among them, seven varieties with high amino acid content all fell into the fourth quadrant. The HCA of amino acids also supports this view. Based on 10 polyphenols, the 69 cabbage varieties were divided into two groups by HCA. Based on 29 indexes of amino acids and polyphenols, 69 cabbage varieties were evaluated and ranked by PCA. Therefore, in this study, cabbage varieties were classified in accordance with the level of amino acids and polyphenols, which provided a theoretical basis for the genetic improvement of nutritional quality in cabbage.     

Characterization of Basil Volatile Fraction and Study of Its Agronomic Variation by ASCA

Basil is a plant known worldwide for its culinary and health attributes. It counts more than a hundred and fifty species and many more chemo-types due to its easy cross-breeds. Each species and each chemo-type have a typical aroma pattern and selecting the proper one is crucial for the food industry. Twelve basil varieties have been studied over three years (2018–2020), as have four different cuts. To characterize the aroma profile, nine typical basil flavour molecules have been selected using a gas chromatography–mass spectrometry coupled with an olfactometer (GC–MS/O). The concentrations of the nine selected molecules were measured by an ultra-fast CG e-nose and Principal Component Analysis (PCA) was applied to detect possible differences among the samples. The PCA results highlighted differences between harvesting years, mainly for 2018, whereas no observable clusters were found concerning varieties and cuts, probably due to the combined effects of the investigated factors. For this reason, the ANOVA Simultaneous Component Analysis (ASCA) methodology was applied on a balanced a posteriori designed dataset. All the considered factors and interactions were statistically significant (p < 0.05) in explaining differences between the basil aroma profiles, with more relevant effects of variety and year.