红外指纹图谱与双指标模型结合用于白芷品质分析

利用共有峰率和变异峰率两个指标,鉴别了不同品质的白芷的红外指纹图谱,白芷样品按厂家各自聚为一类。并应用化学计量学中模式识别方法,即主成分分析和系统聚类分析法,对白芷样品共有特征高效液相色谱峰数据进行处理。主成分分析和系统聚类分析结果与双指标模型一致,川白芷与祁白芷共有峰率最高,达到83. 3%。运用红外指纹图谱与双指标模型结合的方法,可以对白芷进行简单快速准确鉴别,为白芷品质的评价提供了另一种思路。     

基于质子转移反应-飞行时间质谱快速鉴别不同产地闽北水仙茶

采用质子转移反应-飞行时间质谱仪(PTR-TOF-MS), 构建了3个产地(武夷山、建阳、建瓯)113个闽北水仙茶样品香气的化学指纹图谱, 对所得的闽北水仙茶香气指纹图谱进行主成分分析(PCA), 获得了不同产地闽北水仙茶样品的质谱信息特征, 然后采用软独立建模分类法(SIMCA)、K最邻近结点算法(KNN)、偏最小二乘判别分析法(PLS-DA)对闽北水仙茶的质谱信息进行了模式识别.结果表明, PTR-TOF-MS结合分类识别模式能有效区分不同产地的闽北水仙茶.PCA 提取了3个主成分, 累计贡献率为84.66%;3个识别模型的校正集判别正确率分别为89.38%、100.00%和100.00%, 预测集的判别正确率分别为83.18%、 96.46%和95.57%.基于此成功建立了不同产地的闽北水仙茶识别模型.本方法无需样品预处理、分析速度快、灵敏度高、对茶叶无损伤, 为茶叶产地溯源提供了新方法.     

基于高效液相色谱指纹图谱的不同产地不同采摘期昆仑雪菊的化学模式识别及抗氧化谱效关系探究

干燥、粉碎10批不同产地、不同采摘期的昆仑雪菊样品,分取0.2 g,用60%(体积分数)甲醇溶液50 mL超声提取30 min,过0.45μm滤膜,所得溶液(质量浓度为4 000 mg·L^-1)进入高效液相色谱仪,其中各组分在Agilent HC-C₁₈色谱柱上用不同体积比的0.4%(体积分数)乙酸溶液和乙腈的混合溶液进行梯度洗脱分离,在285 nm波长下检测。以中药色谱指纹图谱相似度评价系统建立指纹图谱,筛选共有组分并进行相似度评价。对绿原酸进行方法学考察,并以绿原酸为参照计算各共有组分的含量。以聚类分析和主成分分析等化学模式识别法对不同产地、不同采摘期的样品进行分类。分别采用1,1-二苯基-2-三硝基苯肼(DPPH)、2,2-联氮-二(3-乙基-苯并噻唑-6-磺酸)二铵盐(ABTS)自由基清除法测定10批样品的抗氧化活性,以灰色关联分析法建立共有组分峰面积数据和抗氧化活性的谱效关系。结果显示：10批样品指纹图谱以及它们与对照指纹图谱之间的相似度均大于0.900,共有组分有24个;两种化学模式识别法均将样品分为4类,推测分类结果和产地、采摘...     

莪术药材的闪蒸气相色谱测定及其模式识别分析研究

建立了莪术药材的闪蒸-气相色谱法(FE-GC),采用FE-GC测定了3个产地的9个莪术样品.0.4mg的粉末样品, 在200℃下闪蒸,经色谱分离,基于闪蒸色谱图上分离鉴定到的35个共有峰的相对强度,结合化学模式识别即主成分分析和系统聚类分析法对莪术样品进行了鉴别分析.3个产地的莪术样品可以很好地得到区别.本法快速、简便、准确, 不失为药材质量控制的良好方法.     

基于模糊模式识别技术的红外光谱法分析淫羊藿及人参

提出了应用模糊模式识别技术对来自不同产地的42个淫羊藿样品和40个人参样品的红外光谱数据进行处理,从而作出对此两类天然中药材的产地鉴别。用主成分分析法对上述两类药材的光谱变量作降维处理,然后用选取的主成分得分矩阵代替原始的光谱变量输入于模糊模式识别的模型中,从而求得上述药材每一个试样的贴近度和所属类别。模拟试验的结果表明:此两类天然中药材的产地鉴别的正确率可达92%以上。     

12种道地中药中无机元素的含量测定

报道了用Ｘ射线荧光分析法测定的１２种道地中药，９８个不同产地样品中的Ｆｅ、Ｃｕ、Ｚｎ、Ｍｎ、Ｓｒ、Ｃａ、Ｋ含量。结果表明，不同种属，不同产地，不同品种中药元素量存在差异，不同加工方法影响中药中元素含量，同种中药中元素分布模式也不同。     

高效液相色谱法结合化学计量学分析不同产地姜黄的指纹图谱

本文采用高效液相色谱法(HPLC)对来自于四川、广东和广西的68个姜黄样品进行质量控制方面的研究。通过高效液相色谱-质谱(HPLC-MS)联用技术对姜黄样品中的部分姜黄素类化合物和倍半萜烯类化合物进行了鉴定。进而对所采集到的姜黄样品的HPLC指纹图谱进行主成分分析(PCA)。结果表明,姜黄样品按产地被很好的分成了三类,其所含化合物的含量与产地有关。通过建立偏最小二乘判别分析(PLSDA)、反传人工神经网络(BP-ANN)及最小二乘支持向量机(LS-SVM)这三种有监督模式识别模型对未知样品进行产地预报,结果表明,非线性模型BP-ANN和LS-SVM的预报结果优于线性模型PLS-DA的结果。本文提出的方法可用于姜黄或其他一些中药或食品的质量控制,且一般不需要对它们的组分做定量分析。     

铁皮石斛的裂解气相色谱指纹图谱及其系统聚类分析

采用裂解气相色谱/质谱法(Py-GC/MS)测定了10种不同产地的铁皮石斛并结合系统聚类分析法比较了这些铁皮石斛的指纹图谱,采用释放气体分析法考察了裂解温度对指纹图谱的影响。结果表明,0.4 mg样品在450 ℃下可瞬间裂解,10种样品的指纹图谱具有相似性,且重现性好;采用系统聚类分析能区别不同产地的样品。本法快速、简便、准确,不失为药材质量控制的良好方法。     

超高效液相色谱法测定不同产地白芷中6种香豆素类成分

白芷样品粉末(约2.5g)用25mL甲醇浸泡过夜后超声提取30min,加入适量甲醇补足所失质量,提取液经0.22μm有机膜过滤,采用超高效液相色谱法测定滤液中6种香豆素类成分的含量。以Waters ACQUITY UPLC BEH-C_(18)色谱柱为分离柱,用乙腈和水以不同比例混合的溶液为流动相进行梯度洗脱,用紫外检测器测定。6种香豆素类成分的质量浓度在一定范围内与其对应的峰面积呈线性关系,检出限(3S/N)为0.034～0.091mg·L~(-1)。方法用于白芷样品的分析,加标回收率为93.2%～107%,测定值的相对标准偏差(n=6)为0.64%～1.7%。对9个不同产地的白芷样品中6种香豆素类成分的含量进行聚类分析和主成分分析,结果表明:聚类分析和主成分分析的结果一致,样品被分为3类。     

无机元素与计量学模型结合的半夏产地溯源研究

目的:建立不同产地半夏无机元素的分析方法和溯源体系,为半夏药材的质量控制和道地性评价提供技术支持。方法:采用电感耦合等离子体质谱法(ICP-MS)和电感耦合等离子体原子发射光谱法(ICP-AES)对我国6个主产区72份半夏样品中K、Ca、Na、Mg、Al等37种无机元素的含量进行测定,并采用方差分析、主成分分析、因子分析等计量学方法进行统计与评价。通过对比BP-神经网络算法、K-最近邻算法、最小二乘支持向量机等多种模式识别方法,探索适合半夏产地溯源的最佳模型。结果:不同产地半夏中无机元素的构成各具特征,各无机元素含量在产地间差异显著(P＜0.05),其中La、Pb、As、Na、Bi、Hg、Sn、Cd、Ag 9种元素在不同产区间的差异最为明显;3D-plots图显示不同产地半夏样品分布相对集中,具备产地分类的可行性;KNN分类模型(曼哈顿距离)是半夏产地溯源的最佳方法,测试集的正确率达到100%。结论:无机元素分析技术结合适当的计量学模型可以实现半夏的产地溯源。     

Comprehensive quality evaluation of the lateral root of Aconitum carmichaelii Debx. (Fuzi): Simultaneous determination of nine alkaloids and chemical fingerprinting coupled with chemometric analysis

Amino alcohol alkaloids are the active components in the lateral root of Aconitum carmichaelii Debx. (Fuzi), and they have a variety of pharmacological activities. However, the chemical fingerprints of the ester alkaloids reported to date were mainly obtained from high‐performance liquid chromatography coupled with ultraviolet detection, and it is difficult to obtain information about amino alcohol alkaloids in Fuzi from such chromatograms. In this paper, a comprehensive fingerprinting method was established using high‐performance liquid chromatography coupled with an evaporative light‐scattering detector for the simultaneous quantitative analysis of both the amino alcohol alkaloids and ester alkaloids. A total of 42 samples of Fuzi from four production areas were analyzed by constructing high‐performance liquid chromatography fingerprints. Then, the quantitative results of the chemical fingerprints combined with chemometrics methods were employed to reveal the factors affecting the geo‐authentic Fuzi and to determine characteristic components that can be used to identify these samples. The results indicated distinct differences in the alkaloid contents among samples from the four regions; the geographical origin may be the primary factor affecting the geo‐authentic Fuzi, and 15 major components (including songorine, neoline, and hypaconitine, which were quantitatively determined) were found to be characteristic components for the discrimination of Fuzi samples from various regions. Neoline might be a critical component for identifying geo‐authentic Fuzi. This approach is convenient, reproducible and provides a promising method for the quality evaluation of Fuzi.     

Methods for the exploratory analysis of two-dimensional chromatographic signals

In this article several approaches for the exploratory analysis of two-dimensional chromatographic signals (fingerprints) are presented. Their usefulness is illustrated on experimental chromatographic data obtained from high performance liquid chromatography using the photodiode-array detector (HPLC-DAD). Among the methods discussed are principal component analysis (PCA), hierarchical clustering methods and several N-way techniques such as PARAFAC, PARAFAC2 and Tucker3. In addition to the N-way methods, other approaches that allow for comparing samples represented by two-dimensional fingerprints are also presented (the Rv coefficient, the STATIS approach and ‘fuzzy’ variants of the similarity matrix). Exploratory analysis of the HPLC-DAD data with peak shifts is also discussed.     

Quality assessment of crude and processed Arecae semen based on colorimeter and HPLC combined with chemometrics methods

Raw Arecae Semen, the seed of Areca catechu L., as well as Arecae Semen Tostum and Arecae semen carbonisata are traditionally processed by stir‐baking for subsequent use in a variety of clinical applications. These three Arecae semen types, important Chinese herbal drugs, have been used in China and other Asian countries for thousands of years. In this study, the sensory technologies of a colorimeter and sensitive validated high‐performance liquid chromatography with diode array detection were employed to discriminate raw Arecae semen and its processed drugs. The color parameters of the samples were determined by a colorimeter instrument CR‐410. Moreover, the fingerprints of the four alkaloids of arecaidine, guvacine, arecoline and guvacoline were surveyed by high‐performance liquid chromatography. Subsequently, Student's t test, the analysis of variance, fingerprint similarity analysis, hierarchical cluster analysis, principal component analysis, factor analysis and Pearson's correlation test were performed for final data analysis. The results obtained demonstrated a significant color change characteristic for components in raw Arecae semen and its processed drugs. Crude and processed Arecae semen could be determined based on colorimetry and high‐performance liquid chromatography with a diode array detector coupled with chemometrics methods for a comprehensive quality evaluation.     

基于三波长融合谱的系统指纹定量法鉴定龙胆泻肝丸的真实质量

建立了龙胆泻肝丸(Longdanxiegan pill,LDXGP)三波长融合高效液相色谱(HPLC)指纹图谱,以系统指纹定量法全面鉴定LDXGP的质量。采用反相高效液相色谱法(RP-HPLC),运用多波长融合指纹图谱技术对色谱图进行处理,以黄芩苷为参照物峰,确立了63个共有指纹峰,以宏定性相似度为参量对12个厂家的12批LDXGP进行聚类分析,确定用其中10批生成对照指纹图谱(RFP),以此RFP为标准用系统指纹定量法评价12批LDXGP的质量。结果鉴别出9批质量完全合格,1批含量明显偏高,2批化学成分数量和分布比例不合格。基于多波长融合技术的系统指纹定量法是评价中药真实质量的可靠方法。     

Fingerprint chromatogram analysis of Pseudostellaria heterophylla (Miq.) Pax root by high performance liquid chromatography

A simple and reliable high performance liquid chromatographic (HPLC) method has been developed and validated for the fingerprinting of extracts from the root of Pseudostellaria heterophylla (Miq.) Pax. HPLC with gradient elution was performed on an authentic reference standard of powdered P. heterophylla (Miq.) Pax root and 11 plant samples of the root were collected from different geographic locations. The HPLC chromatograms have been standardized through the selection and identification of reference peaks and the normalization of retention times and peak intensities of all the common peaks. The standardized HPLC fingerprints show high stability and reproducibility, and thus can be used effectively for the screening analysis or quality assessment of the root or its derived products. Similarity index calculations based on cosine angle values or correlation methods have been performed on the HPLC fingerprints. As a group, the fingerprints of the P. heterophylla (Miq.) Pax samples studied are highly correlated with closely similar fingerprints. Within the group, the samples can be further divided into subgroups based on hierarchical clustering analysis (HCA). Sample grouping based on HCA coincides nicely with those based on the geographical origins of the samples. The HPLC fingerprinting techniques thus have high potential in authentication or source-tracing types of applications.     

高效液相色谱技术在代谢组学研究中的应用

高效液相色谱技术逐渐广泛应用于代谢组学的研究中。迄今为止,该技术已经在不同生理状态的生物体液的代谢指纹谱分析中得到了应用。本文评述了传统高效液相色谱技术、毛细管技术和超高效液相色谱等技术在代谢组学的应用。     

Discrimination of Polygoni Multiflori radix and Cynanchi Auriculati radix using ultra‐high performance liquid chromatography fingerprints and chemical pattern recognition

In this work, a strategy was proposed to discriminate Polygoni Multiflori Radix (PMR) and its adulterant (Cynanchi Auriculati Radix, CAR). Ultra‐high performance liquid chromatography (UHPLC) fingerprints were established to analyze samples containing PMR, CAR and mixtures simultaneously. Multivariate classification methods were applied to analyze the obtained UHPLC fingerprints, including principal component analysis (PCA), partial least square discriminant analysis (PLS‐DA), soft independent modeling of class analogy (SIMCA), support vector machine discriminant analysis (SVMDA) and counter‐propagation artificial neural network (CP‐ANN). A plot of PCA score showed that PMR and CAR samples belonged to separate clusters (PMR class and CAR class), and samples of mixtures were located near PMR or CAR classes. Analysis by PLS‐DA, SVMDA and CP‐ANN performed well for recognition and prediction in terms of PMR and CAR samples. Moreover, the PLS‐DA method performed best in the detection of adulterated samples, even if the adulterant was about 25%.     

运用色谱指纹图谱与化学计量学方法对灵芝进行分类

采用95%乙醇为提取溶剂,运用高效液相色谱(HPLC)指纹图谱技术与化学计量学方法,对11个不同灵芝菌株子实体进行分类。通过相似度分析分别获得提取样品指纹图谱的13个共有峰及每个样品之间的相似度;以相对共有峰面积为分析参数,运用化学计量学方法包括聚类分析(HCA)、主成分分析(PCA)及判别分析(DA)对其进行分类,结果分为紫芝、赤芝和美国大灵芝3类。实验结果表明,用化学计量学的方法对灵芝样品的指纹图谱数据进行分析,是一种可用于其分类的科学方法。     

Fingerprint Studies of Radix Scutellariae by Capillary Electrophoresis and High Performance Liquid Chromatography

Two methods based on capillary electrophoresis (CE) and high performance liquid chromatography (HPLC) are described to establish fingerprints of Radix Scutellariae simultaneously. In order to choose an appropriate extraction method, Radix Scutellariae samples extracted by different methods were determined by HPLC. The contents of baicalin, the quality marker of Radix Scutellariae, as well as the number of peaks in the chromatograms were determined to evaluate the extraction methods. 10 batches of Radix Scutellariae collected from different regions in China were applied to establish the fingerprints. Eleven common peaks were isolated within 12 min by CE. The fingerprints obtained with HPLC consisted of 14 common peaks within 40 min. The two proposed methods demonstrated good stability and reproducibility with RSD less than 4% for relative migration time in CE and retention time in HPLC. Finally, the data from the 10 batches of Radix Scutellariae by CE and HPLC were all processed with two kinds of mathematical methods including correlation coefficient and the included angle cosine. The fingerprints of Radix Scutellariae established with CE and HPLC are suitable to identify and differentiate samples by geographical origin and can used for quality control.