基于高效液相色谱指纹图谱和化学模式识别法评价不同采收期水冬瓜树皮药材质量

建立不同采收期水冬瓜树皮药材的高效液相色谱(HPLC)指纹图谱,并结合化学模式识别法,对不同采收期水冬瓜树皮药材质量进行了评价。将新鲜的水冬瓜树皮烘干过筛后,用甲醇提取其中的有效成分,采用HPLC建立不同采收期的11个批次水冬瓜树皮的指纹图谱,通过《中药色谱指纹图谱相似度评价系统》[国家药典委员会(GPC)2004A版]、IBM SPSS Statistics 25统计学软件和SIMCA-P+12.0软件等化学计量学软件对指纹图谱进行相似度分析、系统聚类分析、主成分分析(PCA)和正交偏最小二乘法-判别分析(OPLS-DA)。结果显示:11个批次水冬瓜树皮的HPLC指纹图谱中有18个共有峰,这些共有峰与紫丁香苷的相对峰面积的相对标准偏差(RSD)为30%～124%,说明不同采收期的样品所含化学成分的含量差异较大。11个批次样品的指纹图谱与以S6色谱数据为参考生成的对照指纹图谱的相似度为0.932～0.982,表明不同采收期水冬瓜树皮药材总体质量较为稳定。系统聚类分析将11个批样品分为2组,这一结果得到了PCA和OPLS-DA的验证。OPLS-DA结果还显示:18个共有峰的变量投影重要性(VIP)值均大于0.8,说明不同批次水冬瓜树皮药材之间的质量存在微小差异,从中选择7个VIP值大于1.0的共有峰对应的物质作为质量差异性标志物,用来反映不同采收期水冬瓜树皮中主要化学成分变化。     

指纹图谱结合化学计量学方法研究新疆薰衣草精油成分

采用水蒸汽蒸馏法(SD)提取薰衣草挥发油,气相色谱-质谱联用(GC-MS)技术分析其化学成分及相对含量。通过气相色谱法(GC)建立其色谱指纹图谱,并结合化学计量学方法对其进行品种鉴别。3种薰衣草精油中共检测29种挥发性化学成分,其中共有成分有18种;31批薰衣草样本的GC指纹图谱相似度均大于0.9,符合指纹图谱相似度的要求,利用主成分分析法(PCA)和聚类分析法(HCA)对GC指纹图谱进行识别,可直观地区分薰衣草品种,该方法可应用于薰衣草质量控制及品种鉴别。     

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...     

基于化学识别模式的蒲公英指纹图谱的研究

建立蒲公英药材的指纹图谱,以中药色谱指纹图谱相似度评价软件(2012年版)确定共有峰及其归属,采用化学模式识别初步筛选其质量控制的4个指标性成分。结果表明,蒲公英药材的HPLC指纹图谱共标定出27个共有峰,并指认出其中14个色谱峰,15批蒲公英药材的相似度均0.93,且化学模式识别的结果具有相似性。本文建立的方法可应用于蒲公英药材的质量评价和其产地识别,为蒲公英药材质量控制与资源开发提供参考。     

基于挥发性组分的气相色谱指纹图谱评价沉香化气片质量

建立了沉香化气片的气相色谱指纹图谱,并结合化学模式识别评价20批沉香化气片的质量。乙醇超声提取20批沉香化气片的挥发性成分,以正十八烷为内标,分析了3个主要组分的含量,且以内标计算其他各组分的相对峰面积,建立了沉香化气片的气相色谱指纹图谱,确定了11个共有峰,得到了各批次样品的相似度,并通过气相色谱-质谱法和对照品比对对10个共有峰进行了指认。将获得的峰面积指纹图谱采用系统聚类分析和主成分分析进行化学模式识别研究,实现了不同批次沉香化气片的区分,发现了造成不同批次样品差异的主要标记物。该方法有效且综合性强,为科学评价与有效控制沉香化气片的质量提供了可靠的参考。     

邓老凉茶颗粒的超高效液相色谱质谱联用指纹图谱研究

建立了适用于邓老凉茶颗粒质量控制的超高效液相色谱质谱联用指纹图谱分析方法。样品采用甲醇索氏萃取60 min,萃取液采用超高效液相色谱质谱法进行指纹图谱分析。色谱柱采用Waters ACQUITY HSST3 C18(150 mm×3.0 mm,1.8μm),以0.5%甲酸-乙腈为流动相进行梯度洗脱,流速为0.8 mL/min,柱温35℃。质谱采用负离子ESI模式,选择基峰离子流质量色谱图进行指纹图谱研究。32个共有峰在15 min内得到良好分离,其中15个共有峰通过对照品进行了确证。通过《中药色谱指纹图谱相似度评价系统2004A版》对邓老凉茶颗粒样品进行相似度分析,15个批次样品的相似度均达到0.960以上,表明邓老凉茶颗粒的产品质量稳定性很好。以32个共有峰的相对峰面积进行主成分分析,邓老凉茶颗粒样品之间的细微质量差异得到明显区分。该方法快速、高效、可靠,可有效地用于邓老凉茶颗粒的质量控制。     

色谱指纹图谱在香精香料质量控制中的应用

烟用香精香料化学成分复杂,现无合适的化学质量控制方法,通过实例,对10个批次正常生产的香料标样进行同时蒸馏萃取,取其萃取液进行气相色谱氢焰检测.进行同组分色谱峰的匹配,根据相对峰面积求出标准指纹图谱,然后10批标样各自与标准指纹图谱进行相似度计算,据此设立待测样品的合格性允差范围.待测样品与标准指纹图谱进行谱峰匹配,计算与标准指纹图谱的相似度,依据合格性允差范围,判定其质量状况.     

连花清瘟颗粒有效成分提取及高效液相色谱指纹图谱分析北大核心CSCD

建立连花清瘟颗粒的高效液相色谱(HPLC)指纹图谱,确认其化学成分并结合化学模式识别技术对其进行系统、科学的质量评价。使用化学对照品比对分析和超高效液相色谱-飞行时间质谱(UPLC-Q-TOF-MS)进行定性鉴定;Swell Chromplus TM-C18色谱柱(150 mm×4.6 mm,5μm);以0.1%磷酸-乙腈流动相,梯度洗脱;检测波长278 nm,进行高效液相色谱(HPLC)。采用中药色谱指纹图谱相似度评价系统及聚类分析、主成分分析分析软件进行化学模式识别方法分析。结果表明,通过指纹图谱相似度计算发现,10批样品的HPLC指纹图谱中发现16个共有峰,相似度达到0.967。确认了9个化学成分,包括新绿原酸、绿原酸、隐绿原酸、异绿原酸A、苦杏仁苷、连翘苷、连翘酯苷A、大黄素、大黄酚、大黄酸。该方法简单、稳定、重复性好,可用于该药物的质量评价。     

北五味子的液相色谱指纹图谱的建立

利用反相高效液相色谱法建立中药材北五味子的指纹图谱,为科学评价及有效控制北五味子质量提供了新方法。实验分析了10个不同产地的北五味子样品,采用国家食品药品监督管理局推荐的“中药色谱指纹图谱相似度评价系统(2004 A版)”计算处理,建立了由26个指纹峰和19个共有峰组成的北五味子指纹图谱,确定了5个主要的指纹峰。通过夹角余弦法和相关系数法计算了北五味子10个样本与指纹图谱间的相似度,得到了满意的结果。所建立的指纹图谱可以用来区别不同产地北五味子药材的优劣,为进一步控制北五味子的质量提供依据。     

不同产地半枝莲药材及其混淆品的气相色谱-质谱指纹图谱研究

采用气相色谱-质谱(GC-MS)联用技术,结合化学计量学直观推导式演进特征投影法(HELP)和相似度分析(SA),对不同产地半枝莲及其混淆品白花蛇舌草和半边莲挥发性成分的指纹图谱进行了研究.分别从半枝莲、白花蛇舌草以及半边莲中定性定量出52、38、38种化合物.其中半枝莲和白花蛇舌草的共有峰48个,半枝莲与半边莲的共有...     

Quality control and original discrimination of Ganoderma lucidum based on high-performance liquid chromatographic fingerprints and combined chemometrics methods

In this paper, the feasibility and advantages of employing high-performance liquid chromatographic (HPLC) fingerprints combined with chemometrics methods for quality control of the cultured fruiting bodies of Ganoderma lucidum were investigated and demonstrated for the first time. In order to compare the HPLC fingerprints chromatograms between G. lucidum from different origins, the similarities of all the 60 samples and relative peak areas of 19 characteristic compounds were firstly calculated respectively. Then different pattern recognition procedures, including hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least squares-discrimination analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) were applied to classify the G. lucidum samples according to their cultivated origins. Consistent results were obtained to show that G. lucidum samples could be successfully grouped in accordance with the province of origin. Furthermore, four marker constituents were screened out to be the most discriminant variables, which could be applied to accurate discrimination and quality control of G. lucidum by quantitative analysis. Finally, the chemical properties of those samples were also investigated to find out the differences of quality between them. Ranked in decreasing order, the quality of the G. lucidum can be arranged as Jinzhai/Huangshan, Shandong followed by Zhejiang samples. Our results revealed that the developed method has potential perspective for the original discrimination and quality control of G. lucidum.     

高效液相色谱全轮廓指纹图谱结合化学计量学区分不同地区的紫苏叶

利用高效液相色谱全轮廓指纹图谱结合化学计量学方法对不同栽培地区的紫苏叶样品(共84个)进行区分。全轮廓色谱数据经自适应迭代加权最小二乘法(airPLS)和相关优化翘曲法(COW)校正后,基线和保留时间漂移现象均得到明显改善。经预处理后的色谱数据采用主成分分析(PCA)进行解析,结果表明不同来源的样品能按其特性各自聚为一类;而分段间隔压缩变量后的色谱数据经主成分分析处理可得到与全轮廓色谱数据为输入变量时相一致的结果。此外,偏最小二乘判别分析(PLS-DA)对于紫苏叶样品分类的识别能力和预报能力分别为92.8%和89.6%。     

High-performance liquid chromatographic analysis for the characterization of triterpenoids from Ganoderma

A high-performance liquid chromatographic (HPLC) analysis of triterpenoids from Ganoderma is developed and validated in an attempt to explore a way to differentiate a number of species of the genus Ganoderma. Results show that 64 samples examined in this study could be divided into 18 groups based on characteristics of the HPLC pattern of triterpenoids. This result also conforms with those of the morphological examination and the interfertility test by di-monokaryotic mating. The HPLC analysis of triterpenoids further reveals that differentiation among samples from three different regions each of the two species G. lucidum and G. tsugae is workable. Even then, an incorrect designation is found for two of the groups of samples that were originally classified as G. resinaceum but showed different morphological characteristics and mating incompatibility. In conclusion, an HPLC analysis of triterpenoids is a simple and easy way to differentiate among different species of the genus Ganoderma.     

Discrimination of Ganoderma lucidum according to geographical origin with near infrared diffuse reflectance spectroscopy and pattern recognition techniques

A rapid and nondestructive near infrared (NIR) method combined with chemometrics was used to discriminate Ganoderma lucidum according to cultivation area. Raw, first, and second derivative NIR spectra were compared to develop a robust classification rule. The chemical properties of G. lucidum samples were also investigated to find out the difference between samples from six varied origins. It could be found that the amount of polysaccharides and triterpenoid saponins in G. lucidum samples was considerably different based on cultivation area. These differences make NIR spectroscopic method viable. Principal component analysis (PCA), discriminant partial least-squares (DPLS) and discriminant analysis (DA) were applied to classify the geographical origins of those samples. The results showed that excellent classification could be obtained after optimizing spectral pre-treatment. For the discriminating of samples from three different provinces, DPLS provided 100% correct classifications. Moreover, for samples from six different locations, the correct classifications of the calibration as well as the validation data set were 96.6% using the DA method after the SNV first derivative spectral pre-treatment. Overall, NIR diffuse reflectance spectroscopy using pattern recognition was shown to have significant potential as a rapid and accurate method for the identification of herbal medicines.     

Screening of adulteration in packaging biocomposites by infrared spectroscopy and chemometrics

Fourier transform infrared spectroscopy coupled with chemometrics was employed to detect packaging polylactic acid-based biocomposite samples adulterated with polypropylene (PP) 30–45% and linear low-density polyethylene 2–10%. Principal component analysis, soft independent modeling of class analogy (SIMCA) and partial least square discriminate analysis (PLS-DA) chemometric techniques were utilized to classify samples in different classes. Totally, 362 samples were modeled in three different classes (two adulterated and one non-adulterated). The obtained results revealed that PLS-DA is the most suitable chemometric approach for prediction of probable adulteration in biocomposite samples with reliable specificity and selectivity. It could provide 99% correct class prediction rate between non-adulterated biocomposite samples and adulterated ones, while SIMCA methods provided 73.33% prediction accuracy in classification.     

Classification of Liquor Using Near-Infrared Spectroscopy and Chemometrics

The authenticity of Chinese liquor concerns consumer health and economic issues. The traditional characterization methods are time-consuming and require experienced analysts. The use of near-infrared (NIR) spectroscopy and chemometrics to classify Chinese liquor samples was investigated using 128 liquors. The spectral region between 5340 cm^?1 and 7400 cm^?1 was found to be most informative. Principal component analysis was employed to characterize liquor and principal components were extracted as inputs of training classifiers. Several supervised pattern recognition methods including K-nearest neighbor, perceptron, and multiclass support vector machine were used as algorithms of constructing classifiers. The initial principal components and all spectral variables were used as the input of training models. In terms of the misclassification ratio, the support vector machine approach was the most accurate. The results indicated that near-infrared spectroscopy and chemometrics are an alternative to conventional methods for the characterization of liquor.     

Discrimination of Rhizoma Corydalis from two sources by near-infrared spectroscopy supported by the wavelet transform and least-squares support vector machine methods

Near-infrared spectroscopy (NIRS) was applied for direct and rapid collection of characteristic spectra from Rhizoma Corydalis, a common traditional Chinese medicine (TCM), with the aim of developing a method for the classification of such substances according to their geographical origin. The powdered form of the TCM was collected from two such different sources, and their NIR spectra were pretreated by the wavelet transform (WT) method. A training set of such Rhizoma Corydalis spectral objects was modeled with the use of the least-squares support vector machines (LS-SVM), radial basis function artificial neural networks (RBF-ANN), partial least-squares discriminant analysis (PLS-DA) and K-nearest neighbors (KNN) methods. All the four chemometrics models performed reasonably on the basis of spectral recognition and prediction criteria, and the LS-SVM method performed best with over 95% success on both criteria. Generally, there are no statistically significant differences in all these four methods. Thus, the NIR spectroscopic method supported by all the four chemometrics models, especially the LS-SVM, are recommended for application to classify TCM, Rhizoma Corydalis, samples according to their geographical origin.     

Quality evaluation of Ganoderma through simultaneous determination of nine triterpenes and sterols using pressurized liquid extraction and high performance liquid chromatography

A method combining HPLC and pressurized liquid extraction was developed for simultaneous quantification of nine components, including eight triterpenes (ganoderic acid A, ganoderic acid Y, ganoderic acid DM, ganoderol A, ganoderol B, ganoderal A, methyl ganoderate D and ganoderate G) and a sterol (ergosterol), in Ganoderma. The determination was achieved by using a Zorbax ODS C18 analytical column (4.6 x 250 mm id, 5 microm) and gradient elution with diode-array detection. All calibration curves showed good linearity (r2 > 0.9997) within the test ranges. The developed method showed good repeatability for the quantification of the nine investigated components in Ganoderma with intra- and inter-day variations of less than 2.4% and 4.1%, respectively. The validated method was successfully applied to quantify the nine components in two species of Ganoderma, i.e. G. lucidum and G. sinense, used as Lingzhi in China. Furthermore, hierarchical clustering analysis based on the nine components in HPLC profiles from the tested 11 samples showed that chemical characteristics were significantly different between G. lucidum and G. sinense, which suggested that clinical investigation should be performed so as to ensure the safety and efficacy of medication.     

Improved chromatographic fingerprints for facile differentiation of two Ganoderma spp

This paper addresses a comprehensive and comparative study of six phytochemical extraction methods for triterpenes from the fruiting body of Ganoderma spp. Quantitative analysis of extracts was performed by HPLC with photodiode array detection. In general, pressurized liquid extraction and microwave-assisted extraction under optimized conditions produce better yields, and the former also significantly reduces the total time of extraction and manipulation of a sample, as well as the amount of solvent used in comparison with conventional soxhlet, reflux, ultrasonic, and methanol-CO(2) supercritical fluid extractions. Based on the improved extraction protocol, the fingerprinting profiles for two species of Lingzhi were established using the consistent chromatographic features of 12 authentic samples. Eleven common peaks of ganoderic/ganoderenic acids were identified using LC-ESI-MS-MS. These specific triterpene groups were adopted as chemical markers for Lingzhi. Using chemometric analysis, the developed fingerprinting was successfully applied to differentiate between the two species under the Ganoderma genus and is applicable as a method for quality evaluation of this valuable medicinal fungus and its related proprietary products.     

杭州老虎洞窑古陶瓷成分的化学计量学研究

用支持向量机算法研究了与杭州老虎洞古陶瓷有关的两个断源、断代问题。作为化学计量学的～种新型分类算法,支持向量机在小样本问题上表现出良好的泛化能力,与特征选择方法结合,可以有效处理样本少,特征多的问题。本研究综合利用支持向量机、特征选择算法和其它化学计量学算法研究了杭州凤凰山麓万松岭附近的古窑遗址和“传世哥窑”的断源、断代问题,证明老虎洞窑与郊坛下窑产品截然不同,万松岭附近地面收集瓷片样本是老虎洞窑宋代地层的瓷片滑落所致,而“传世哥窑”样品可能是老虎洞窑元代时的产品。实验表明：支持向量机算法与化学分析相结合可以成为研究古陶瓷断源和断代问题的一种新方法。