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1.
红外指纹图谱和聚类分析法在赤芍产域分类鉴别中的应用   总被引:27,自引:0,他引:27  
以赤芍的红外指纹图谱为依据,采用主成分分析法对来自18个产地的赤芍进行了聚类分析。可将18个产地大致分为6类,这一分类与地理位置有较明显的对应关系,同一区域内赤芍的性能较为相似,可作为传统中医界对赤芍药材质量评价的依据。用径向基函数人工神经网络法预测了45个赤芍样本的产区,结果表明,径向基函数人工神经网络法具有较强的预测能力,用它可鉴别赤芍的产区。可为药材的质量控制提供一个快捷、准确、可行的鉴别方法。  相似文献
2.
稳定性氢同位素分析在牛肉产地溯源中的应用   总被引:3,自引:0,他引:3  
探讨了利用高温热解炉和同位素比率质谱仪(IRMS)联用测定肉品中稳定性氢同位素比率的方法,并利用此方法测定了我国不同地域来源脱脂牛肉、牛尾毛中氢同位素比率.分析了牛组织中氢同位素组成与地域经度、纬度及海拔高度变化的关系,以及稳定性氢同位素用于牛肉产地溯源的可行性.结果表明,不同地域来源牛组织中δ2H值的差异显著,其与当地饮水中氢同位素组成密切相关,而且有随着地理纬度增加而减小的趋势; 牛尾毛与牛肉中δ2H值的相关性显著.稳定性氢同位素是用于牛肉产地溯源的一项很有潜力的指标,且牛肉和牛尾毛中的氢同位素组成均可反映牛来源地的信息.  相似文献
3.
应用电喷雾串联质谱法( ESI-MS/MS)对云南和秘鲁产玛咖样品中低极性化学成分进行检测,获得各样品的一级质谱指纹谱图和各离子峰的二级质谱数据,并测定各样品促进大鼠睾丸间质细胞增殖活性,采用化学计量学方法主成分分析( PCA)、偏最小二乘法( PLS)和灰色关联度分析( GRA)对所获得的一级质谱数据进行处理后,可有效区分玛咖的不同产地,且筛选出其中具有促大鼠睾丸间质细胞增殖活性的可能成分,进而通过二级质谱数据分析得到可能活性成分的结构。实验结果表明,玛咖低极性成分具有很好的促大鼠睾丸间质细胞增殖活性,其中活性较强的主要为N-benzylhexadecanamide和N-benzy-(9Z,12Z,15Z)-octadecatrien-amide。本方法为简单、快速分析中药中促睾丸间质细胞增殖活性成分筛选方法提供了借鉴。  相似文献
4.
Chromatographic profiles obtained by headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography (GC) were processed as continuous and non-specific signals through multivariate analysis techniques in order to select and identify the most discriminate volatile marker compounds related to the geographical origin of extra virgin olive oils. The blind analysis of the chromatographic profiles was carried out on several steps including preliminary mathematical treatments, explorative analysis, feature selection and classification. The results obtained through the application of stepwise linear discriminant analysis (SLDA) method revealed a perfect discrimination between the different Spanish geographical regions considered (La Rioja, Andalusia and Catalonia). The assignment success rate was 100% in both classification and prediction by using cross validation procedure. In addition, it must be noted that the proposed strategy was able to verify the geographical origin of the samples involving only a reduced number of discriminate retention times selected by the stepwise procedure. This fact emphasizes the quality of the accurate results obtained and encourages the feasibility of similar procedures in olive oil quality and traceability studies. Finally, volatile compounds corresponding to the predictors retained were identified by gas chromatography-mass spectrometry (GC-MS) for a chemical interpretation of their importance in quality virgin olive oils.  相似文献
5.
The aim of the present study was to characterize and classify olive oils from Western Greece according to cultivar and geographical origin, based on volatile compound composition, by means of Linear Discriminant Analysis. A total of 51 olive oil samples were collected during the harvesting period 2007-2008 from six regions of Western Greece and from six local cultivars. Forty-five of the samples were characterized as extra virgin olive oils. The analysis of volatile compounds was performed by Headspace Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC/MS). Fifty-three (53) different volatile compounds were tentatively identified and semi-quantified. Using selected volatile compound composition data (selection was based on the application of ANOVA to total volatiles to determine those variables showing substantial differences among samples of different geographical origin/cultivar), the olive oil samples were satisfactorily classified according to geographical origin (87.2%) and cultivar (74%).  相似文献
6.
Multi-element (H,C,N,S) stable isotope ratio analysis was tested for its suitability as a means for geographical provenance assignment of lamb meat from several European regions. The defatted dry matter (crude protein fraction) from lamb meat was found to be a suitable probe for "light" element stable isotope ratio analysis. Significant differences were observed between the multi-element isotope ratios of lamb samples from different regions. The mean hydrogen isotopic ratios of the defatted dry matter from lamb were found to be significantly correlated with the mean hydrogen isotopic ratios of precipitation and groundwater in the production regions. Carbon and nitrogen isotopic ratios were influenced by feeding practices and climate. Sulfur isotopic ratios were influenced by geographical location and surface geology of the production region. The results permitted differentiation of lamb meat, from most production regions, by inspection. However, more sophisticated evaluation of the data using multivariate methods, such as linear discriminant analysis, achieved 78% correct classification.  相似文献
7.
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.  相似文献
8.
Inductively coupled plasma mass spectrometry (ICP–MS) and isotope-ratio mass spectrometry (IR-MS) have been used to examine the multi-elemental composition and 15N/14N and 13C/12C isotope ratios of three spring barley (Hordeum vulgare) genotypes (Orthega, Barke, and Bartok) grown in three typical Danish agricultural soils (North Jutland, West Jutland, and East Zealand) differing in soil fertility. The aim of the study was to examine whether it was possible to generate a unique elemental fingerprint of individual barley genotypes irrespective of the elemental imprint plants had received from soils differing in fertility and agricultural practice. Multivariate statistics were used to analyze the elemental fingerprints of the barley genotypes at different times during a full growing season from early tillering to full maturity of the barley grains. Initially, 36 elements were analyzed in the plant samples but this number was subsequently reduced to 15 elements: B, Ba, C, Ca, Cu, Fe, K, Mg, Mn, N, Na, P, S, Sr, and Zn. These elements exceeded the limit of detection (LOD) for all genotypes, soil types, and plant growth stages and for these elements the accuracy was better than 90% compared with apple leaf certified reference material (CRM). Principal component analysis (PCA) separated multi-elemental data in accordance with soil type when plants of similar physiological age were compared, whereas this separation disappeared if plants of all ages were compared simultaneously. Isotope ratios (15N) of plants also proved to be a highly accurate property for classification of samples according to soil type. In contrast, the differences in 13C were too small to enable such classification. The differences in 15N among soils were so pronounced that separation of samples according to the physiological age of plants became redundant. However, 15N and the multi-elemental analysis revealed no differences between the three barley genotypes, indicating that the influence of soil chemistry and possibly also climate and agricultural practice was too large to allow an unique elemental fingerprint for the genotypes. This finding was substantiated by analyzing the multi-elemental composition of grain from two additional genotypes (Otira and Barthos) grown at the north and east locations, respectively. PCA showed not only that the elemental fingerprints of these two genotypes were similar to those of the others, but also that the soil in which the plant had been growing could be accurately predicted on the basis of the PCA scores from the genotypes Orthega, Barke, and Bartok. Similar conclusions could be drawn using 15N data.  相似文献
9.
A rapid near infrared spectroscopy analysis method was developed for the geographical origin discrimination and content determination of Radix scutellariae, a kind of Traditional Chinese Medicine (TCM). 81 R. scutellariae samples from six different origins were analyzed with HPLC-UV as reference method. The NIR spectra were collected in integrating-sphere diffused reflection mode and processed with different spectra pretreated methods. Discriminant analysis (DA) and discriminant partial least squares (DPLS) were applied to classify the geographical origins of those samples, and the latter had a better predictive ability with 100% accuracy after two exceptional samples eliminated from the calibration set. For the quantitative calibration, the samples were divided into calibration set and validation set by Kennard-Stone algorithm. The models of baicalin, wogonoside, baicalein, wogonin were established with partial least squares (PLS) algorithm and the optimal principal component (PC) numbers were selected with Leave-One-Out (LOO) cross-validation. The established models were evaluated with the root mean square error of prediction (RMSEP) and corresponding correlation coefficients. The correlation coefficients of all the four calibration models are above 0.920, and the RMSEPs of baicalin, wogonoside, baicalein and wogonin are 0.752%, 0.094%, 0.418% and 0.139%, respectively. This research indicated that the NIR diffuse reflection spectroscopy could be used for the rapid analysis of R. scutellariae, which is beneficial to the quality control of this raw material in TCM pharmaceutical factory, and will also help to solve analogous problems.  相似文献
10.
Principal component analysis (PCA) is widely used as an exploratory data analysis tool in the field of vibrational spectroscopy, particularly near-infrared (NIR) spectroscopy. PCA represents original spectral data containing large variables into a few feature-containing variables, or scores. Although multiple spectral ranges can be simultaneously used for PCA, only one series of scores generated by merging the selected spectral ranges is generally used for qualitative analysis. Alternatively, the combined use of an independent series of scores generated from separate spectral ranges has not been exploited.The aim of this study is to evaluate the use of PCA to discriminate between two geographical origins of sesame samples, when scores independently generated from separate spectral ranges are optimally combined. An accurate and rapid analytical method to determine the origin is essentially required for the correct value estimation and proper production distribution. Sesame is chosen in this study because it is difficult to visually discriminate the geographical origins and its composition is highly complex. For this purpose, we collected diffuse reflectance near-infrared (NIR) spectroscopic data from geographically diverse sesame samples over a period of eight years. The discrimination error obtained by applying linear discriminant analysis (LDA) was improved when separate scores from two spectral ranges were optimally combined, compared to the discrimination errors obtained when scores from singly merged two spectral ranges were used.  相似文献
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