基于OSC–WT–PLS近红外光谱法测定烟草中芸香苷

采用正交信号校正(OSC)结合小波变换(WT)对烟草光谱进行光谱预处理,将预处理后的烟草光谱结合偏最小二乘法(PLS)建立了烟草光谱对芸香苷的预测模型。利用OSC滤除光谱中与芸香苷含量无关的光谱信息,确定OSC提取的最佳主成分数为7,再选择WT中的最佳小波基函数bior1.1对OSC预处理后的光谱进行压缩及进一步滤噪,然后进行PLS建模,OSC–WT–PLS所建模型决定系数r~2=0.874,校正标准偏差RMSEC=0.85,预测均方根误差RMSEP=0.743,交互验证系数Q_(ext)~2=0.887。结果表明,用OSC–WT–PLS可滤除光谱信息中与待测样品含量无关的信息、减少光谱数据量,降低建立模型的复杂度、提高建模速度及模型的预测能力、准确度。     

不同比色皿对近红外光谱法检测水质酸度的影响及校正分析北大核心CSCD

为减小不同比色皿对近红外光谱测量结果的影响,提高水质酸度定量分析模型的预测精度,探讨了正交信号校正(OSC)用于不同比色皿的光谱背景干扰的去除效果。用两个同一批次的石英比色皿对32个不同pH的水样装样,采集近红外光谱数据,采用OSC对原始光谱进行预处理。比较OSC预处理前后两组光谱间的差异,并建立了水质酸度的偏最小二乘(PLS)定量分析模型,分析了光谱差异对模型预测精度的影响。结果表明:经OSC预处理后,两组光谱的平均差异值由0.0042降低至0.0013,光谱校正率达90%;与原始光谱建立的PLS模型相比,基于OSC预处理后的光谱建立的PLS模型的预测精度显著提高,预测均方根误差差值由0.912降低至0.205,相关系数差值由0.364降低至7.00×10^(-3),二者分别减小了78%和98%。     

独立分量分析预处理法提高苹果糖度模型预测精度研究

为了提高苹果近红外光谱糖度预测模型精度,利用独立分量分析方法(ICA)对苹果近红外光谱进行了预处理,并且建立了糖度的偏最小二乘(PLS)预测模型。结果表明,独立分量分析不但能分离出噪声信号,而且所分离出来的光谱信号也比原始光谱信号光滑。在预处理后的最佳PLS糖度模型校正时的相关系数rc和标准偏差SEC分别为0.9549和0.3361,用于预测时的相关系数rp和标准偏差SEP分别为0.9071和0.4355。与普通的平均处理法的PLS模型相比,其精度有所提高,且模型更加简洁。     

光谱预处理方法对混胺近红外定量模型影响的研究

本文探讨了一阶导数、Savitzky-Golay平滑、小波变换(WT)和正交信号校正(OSC)预处理方法对混胺组分近红外光谱的预处理效果。采用预测集标准偏差(SEP)对各种预处理方法的最佳参数进行选择。比较了各种预处理方法的去噪能力,对预处理方法组合后的效果进行了评价。研究表明,WT和OSC能有效去除噪声,提高分析模型的精度,WT和OSC结合后的预处理效果更好。     

化学计量学方法同时测定铁、铝和铍

采用正交信号校正(OSC)-小波包变换(WPT)-偏最小二乘法(PLS)(OSCW-PTPLS)相结合的化学计量学方法,用于不经化学分离解析光谱严重重叠的Fe(Ⅲ)、Al(Ⅲ)和Be(Ⅱ)混合物。该法结合OSC,WPT和PLS三种技术提高了获取特征信息的能力和回归质量。本文测定的三种金属离子可与铬天青S和溴化十六烷基吡啶(CPB)在pH=5.60的邻苯二甲酸氢钾-NaOH缓冲溶液中发生高灵敏度和低选择性的显色反应。设计了一个名为POSCWPTPLS的程序来执行相关计算。实验结果显示OSCWPTPLS方法优于PLS方法。     

基于高光谱图像的生菜叶片氮素含量预测模型研究

为了便于更经济合理地为作物施肥,建立一种无损检测作物氮营养元素的高光谱图像模型。本实验以生菜为研究对象,无土栽培各氮素水平的生菜叶样本,在莲座期,采集生菜叶片样本的高光谱图像(390~1050 nm),同时采用凯氏定氮法测定对应生菜叶片样本的全氮含量。通过ENVI软件提取出生菜叶片中感兴趣区域的平均光谱作为该样本原始光谱信息,分别使用平滑处理(Smoothing)、多元散射矫正(MSC)、标准正态变量变换结合去趋势(SNV detrending)、一阶导数法(First derivative)、二阶导数法(Second derivative)、正交信号矫正(OSC)等预处理方法对样本原始光谱进行处理,然后利用偏最小二乘回归法(Partial least squares regression,PLSR)分别建立样本全波段光谱信息与氮含量的关系模型,研究各预处理方法对氮含量模型的影响,结果表明,使用OSC预处理的模型效果最好。为了简化模型,根据OSC预处理光谱后的模型的PLSR回归系数优选出敏感波长,利用训练集中样本的敏感波长光谱信息与氮含量数据重新构建PLSR回归模型,并利用测试集样本进行测试试验。结果表明,该模型得到校正集和预测集的决定系数(R2p)分别为0.89,0.81;均方根误差RMSEC,RMSEP分别为0.33,0.45。该回归模型大大降低了自变量个数,简化了模型,并且取得了较优的效果,这为生菜氮素含量预测提供了一种新的快速有效方法。     

正交信号校正用于傅里叶变换红外光谱的模型传递

利用正交信号校正（OSC）实现了4组分气体混合物的PLS模型,在两台傅里叶变换红外光谱（FTIR）仪上的传递,并与直接标准化（DS）、分段直接标准化（PDS）、多元分散校正（MSC）和有限脉冲响应（FIR）的传递效果进行了比较,确立了以源机的校正模型直接对目标机数据进行预测的传递方式。经过OSC校正,预测均方根误差（RMSEP）为10^-3左右。OSC可以有效地减小测量仪器间的差异,同时使PLS模型的潜变量个数降为4,使模型简单化。与DS和PDS相比,OSC不需要同一样品在两台仪器上测量,在支集大小为3时,得到一致的预测准确度,表现出稳健性。MSC和FIR处理的RMSEP为10^-1左右,效果远差于OSC。     

一种通过水光谱探究木犀草素浓度测定的新方法

采集了一定含水量、不同浓度的木犀草素溶液的近红外光谱,借助于多元分析方法研究了其谱峰变化,建立了一种基于不同浓度木犀草素对水光谱的扰动情况进行木犀草素检测的模型.通过比较不同光谱预处理方法,最终确定采用标准正态变换(SNV)法进行光谱预处理,并以偏最小二乘(PLS)法建立木犀草素的定量预测模型.结果显示,经Kennar...     

激光诱导击穿光谱结合CARS变量选择方法定量检测倍硫磷含量

利用双脉冲激光诱导击穿光谱(LIBS)技术对溶液中的倍硫磷含量进行定量检测。采用二通道高精度光谱仪采集不同浓度倍硫磷样品在206.28~481.77 nm波段的LIBS光谱,并对光谱进行多元散射校正(MSC)、标准正态变量变换(SNV)及3点平滑预处理,根据偏最小二乘(PLS)建模确定最优的预处理方法。在此基础上,利用竞争性自适应重加权算法(CARS)筛选与倍硫磷相关的重要变量,然后应用PLS回归建立溶液中倍硫磷含量的定量分析模型,并与单变量定量分析模型及未变量选择的PLS定量分析模型进行比较。结果表明,相比单变量定量分析模型及原始光谱PLS定量分析模型,CARS-PLS定量分析模型的性能更优,其模型的校正集和预测集的决定系数及平均相对误差分别为0.969 4、15.537%和0.995 9、5.016%。此外,与原始光谱PLS模型相比,CARS-PLS模型仅使用其中1.9%的波长变量,但预测集平均误差却由9.829%下降为5.016%。由此可见,LIBS技术检测溶液中的倍硫磷含量具有一定的可行性,且CARS方法能简化定量分析模型,提高模型的预测精度。     

傅立叶变换近红外光谱法快速评价涪陵榨菜品质

应用傅立叶变换近红外光谱技术,建立了评价涪陵榨菜品质的定量分析模型.测定了58份涪陵榨菜的近红外光谱数据,通过光谱预处理方法消除噪声,以偏最小二乘法(PLS)建立回归模型.最终得到评价其品质的水分、总酸(以乳酸计)和氨基酸含量近红外光谱分析模型的决定系数(R2)依次为0.957 8、0.975 4、0.950 4,交叉...     

177 Saponins,Including 11 New Compounds in Wild Ginseng Tentatively Identified via HPLC-IT-TOF-MSn,and Differences among Wild Ginseng,Ginseng under Forest,and Cultivated Ginseng

Wild ginseng (W-GS), ginseng under forest (F-GS, planted in mountain forest and growing in natural environment), and cultivated ginseng (C-GS) were compared via HPLC-DAD and HPLC-IT-TOF-MSⁿ. A total of 199 saponins, including 16 potential new compounds, were tentatively identified from 100 mg W-GS (177 saponins in W-GS with 11 new compounds), F-GS (56 saponins with 1 new compound), and C-GS (60 saponins with 6 new compounds). There were 21 saponins detected from all the W-GS, F-GS, and C-GS. Fifty saponins were only detected from W-GS, including 23 saponins found in ginseng for the first time. Contents of ginsenosides Re (12.36–13.91 mg/g), Rh₁ (7.46–7.65 mg/g), Rd (12.94–12.98 mg/g), and the total contents (50.52–55.51 mg/g) of Rg₁, Re, Rf, Rb₁, Rg₂, Rh₁, and Rd in W-GS were remarkably higher than those in F-GS (Re 1.22–3.50 mg/g, Rh₁ 0.15–1.49 mg/g, Rd 0.19–1.49 mg/g, total 5.69–18.74 mg/g), and C-GS (Re 0.30–3.45 mg/g, Rh₁ 0.05–3.42 mg/g, Rd 0.17–1.68 mg/g, total 2.99–19.55 mg/g). Contents of Re and Rf were significantly higher in F-GS than those in C-GS (p < 0.05). Using the contents of Re, Rf, or Rb₁, approximately a half number of cultivated ginseng samples could be identified from ginseng under forest. Contents of Rg₁, Re, Rg₂, Rh₁, as well as the total contents of the seven ginsenosides were highest in ginseng older than 15 years, middle–high in ginseng between 10 to 15 years old, and lowest in ginseng younger than 10 years. Contents of Rg₁, Re, Rf, Rb₁, Rg₂, and the total of seven ginsenosides were significantly related to the growing ages of ginseng (p < 0.10). Similarities of chromatographic fingerprints to W-GS were significantly higher (p < 0.05) for F-GS (median: 0.824) than C-GS (median: 0.745). A characteristic peak pattern in fingerprint was also discovered for distinguishing three types of ginseng. Conclusively, wild ginseng was remarkably superior to ginseng under forest and cultivated ginseng, with ginseng under forest slightly closer to wild ginseng than cultivated ginseng. The differences among wild ginseng, ginseng under forest, and cultivated ginseng in saponin compositions and contents of ginsenosides were mainly attributed to their growing ages.     

气相色谱-三重四极杆质谱分析人参炮制品中的挥发性成分

人参炮制的化学成分变化研究主要集中在皂苷和糖类,本文首次从挥发性成分角度阐释了人参不同炮制品的物质基础。利用气相色谱-质谱联用(GC-MS/MS)方法,对鲜参、生晒参和红参中挥发性成分及其衍生规律进行研究。采用TG-5SILMS非极性气相色谱柱,以He为载气,通过NIST MS Spectral Database对挥发性成分进行检测并鉴定。鲜参、生晒参、红参中分别检出30、33和34种挥发性成分,其中生晒参中(-)-斯巴醇含量为鲜参含量的31.98倍,辛醛等8种挥发性成分为鲜参中含量的3倍以上,红参中有环癸等10种挥发性成分为鲜参中含量的3倍以上。生晒参和红参中各有4种挥发性成分在鲜参中未检出。     

液相色谱-大气压化学电离质谱法分析人参中的人参皂甙

研究了用反相高效液相色谱-大气压化学电离质谱(HPLC/APCI-MS)分析人参皂甙的方法。液相色谱采用乙腈-水流动相进行梯度洗脱,质谱采用正负离子同时扫描并结合二级质谱进行定性,用选择反应离子模式(SRM)测定检测限。实验发现虽然人参皂甙是热不稳定物质,但在大气压化学电离质谱的高温汽化过程中仍能检测到很强的负离子分子离子峰,而且随着汽化温度的升高,人参皂甙的负离子分子离子峰的强度增加。该方法对人参皂甙Rb1和Rg1的检测限分别为1.2×10-13 g和3.0×10-14 g,并检测出白参中包括丙二酰人参皂甙在内的29种人参皂甙。该法灵敏度高,重复性好,结果准确,能有效地对药材提取物中的多种人参皂甙进行检测和结构分析。     

Improved Extraction Method and Chromatographic Separation of Ginsenosides from Ginseng Roots,Leaves and Ginseng Drug Preparations

A new extraction method for ginsenosides from ginseng roots, ginseng leaves and ginseng drug preparations by Sep-Pak C₁₈ cartridges has been studied. Ginsenoside extraction by Sep-Pak cartridges is a rapid, efficient, reproducible method. In addition, the extracts were analyzed by high performance thin layer chromatography (HPTLC) and reverse phase high performance liquid chromatography (HPLC). The major components of ginseng saponins were effectively separated using an ODS-120T column.     

气相色谱法测定太白洋参中的甘露醇含量

介绍了应用气相色谱法－氢火焰离子化检测器检测太白洋参中甘露醇的方法,采用OV－225填充柱分离该法平均回收率为90．66％,检出限为0．1mg/kg。     

矿物元素指纹图谱的建立及在西洋参产地鉴别中的应用研究

采用电感耦合等离子体质谱法测定了山东、吉林、美国和加拿大4个产地西洋参中50种矿物元素的含量,研究了不同产地西洋参矿物元素的差别和转换系数,构建了西洋参的矿物元素指纹图谱。以各产地矿物元素含量的平均值构建了山东、吉林、美国和加拿大产西洋参的矿物元素标准指纹图谱。采用SPSS 20.0计算了各西洋参矿物元素指纹图谱与其矿物元素标准指纹图谱的相似度,确定了山东、吉林、美国和加拿大产西洋参矿物元素指纹图谱的相似度阈值分别为0.93、0.91、0.98和0.93。通过比较未知产地西洋参矿物元素指纹图谱与矿物元素标准指纹图谱的相似度,进行西洋参的产地判别。采用20批未知产地西洋参样品验证模型的准确性,正确率为85%。此外,研究表明,不同生长年限和不同部位西洋参样品对所建立的西洋参产地鉴别方法无影响。     

中国雪参挥发油成分的色谱-质谱分析

本文测定了中国雪参根中人参挥发油的含量,并用色谱-质谱联用仪分析了化学成分及百分含量。从中分离出132种化合物,初步鉴定出49种,占挥发油总量的87.73％,有28种化合物尚未见报道。     

The Effects of New Zealand Grown Ginseng Fractions on Cytokine Production from Human Monocytic THP-1 Cells

Pro-inflammatory cytokines and anti-inflammatory cytokines are important mediators that regulate the inflammatory response in inflammation-related diseases. The aim of this study is to evaluate different New Zealand (NZ)-grown ginseng fractions on the productions of pro-inflammatory and anti-inflammatory cytokines in human monocytic THP-1 cells. Four NZ-grown ginseng fractions, including total ginseng extract (TGE), non-ginsenoside fraction extract (NGE), high-polar ginsenoside fraction extract (HPG), and less-polar ginsenoside fraction extract (LPG), were prepared and the ginsenoside compositions of extracts were analyzed by HPLC using 19 ginsenoside reference standards. The THP-1 cells were pre-treated with different concentrations of TGE, NGE, HPG, and LPG, and were then stimulated with lipopolysaccharide (LPS). The levels of pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-8 (IL-8), and anti-inflammatory cytokines, such as interleukin-10 (IL-10), and transforming growth factor beta-1 (TGF-β1), were determined by enzyme-linked immunosorbent assay (ELISA). TGE at 400 µg/mL significantly inhibited LPS-induced TNF-α and IL-6 productions. NGE did not show any effects on inflammatory secretion except inhibited IL-6 production at a high dose. Furthermore, LPG displayed a stronger effect than HPG on inhibiting pro-inflammatory cytokine (TNF-α, IL-1β, and IL-6) productions. Particularly, 100 µg/mL LPG not only significantly inhibited the production of pro-inflammatory cytokines TNF-α, IL-1β, and IL-6, but also remarkably enhanced the production of anti-inflammatory cytokine IL-10. NZ-grown ginseng exhibited anti-inflammatory effects in vitro, which is mainly attributed to ginsenoside fractions (particularly less-polar ginsenosides) rather than non-saponin fractions.     

非靶向代谢组学用于藜芦妨害人参治疗脾气虚的机制研究

采用超高效液相色谱串联四级杆飞行时间质谱( UPLC/Q-TOF-MS)联用技术,通过非靶向代谢组学方法分析大鼠尿液内源性代谢物的变化,研究藜芦妨害人参发挥药效作用的机制。建立脾气虚大鼠模型,连续给药15天,测定力竭游泳时间及血液中白细胞、红细胞、血红蛋白的含量。结果表明,人参可显著提高脾气虚模型大鼠的力竭游泳时间(p﹤0.01),升高白细胞、红细胞及血红蛋白含量(p﹤0.05,p﹤0.01),藜芦对脾气虚模型大鼠各项指标无明显影响(p>0.05),人参与藜芦配伍后对脾气虚模型大鼠各项指标均无显著影响(p>0.05),表明藜芦妨害了人参发挥药效作用。采用UPLC/Q-TOF-MS技术及非靶向代谢组学的方法分析了空白组、模型组、人参组、藜芦组、参藜组对脾气虚模型大鼠的尿液代谢组差异,其中主成分分析( PCA)得分图显示各组代谢轮廓有显著差别,并通过正交偏最小二乘法-判别分析( OPLS-DA)及数据库检索,鉴定出15种人参干预调节脾气虚模型大鼠的潜在生物标志物,从中找出了7种人参藜芦配伍后减弱人参上述干预作用的潜在生物标志物,并对其涉及的代谢通路进行了系统分析。上述研究结果表明,人参藜芦配伍后妨害了人参对脾气虚模型大鼠的治疗作用,其机理可能是影响人参对体内能量代谢、免疫平衡及氧化还原反应等相关代谢的调节。     

Identification and Evaluation of a Panel of Ginsenosides from Different Red Ginseng Extracts with Nootropic Effect

Red ginseng has been gradually discovered to have pharmacological and physiological effects. It is well known that the most important bioactive components of ginseng are ginsenosides. The nootropic effect of ginsenosides from nine different red ginseng extracts was evaluated here. Nine groups of mice were perfused with different concentrations of nine red ginseng extracts, respectively, and two groups of mice with distilled water. The nootropic effect of ginsenosides on mice was evaluated with behavior tests and a biochemical indicator study. The extracts were identified by rapid resolution liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry(RRLC-Q-TOF-MS). Furthermore, principal component analysis(PCA) was used to analyze the contribution of chemical components from different ginseng groups. The extracts with the most and the weakest effective nootropic were found. It is notable that extract processing is a very important factor to decide pharmacological functions of ginseng extracts. As a conclusion, the most effective extract method for ginsenosides has been found. A panel of 13 ginsenosides has been screened out as chemical markers with nootropic effect, which include high level ginsenosides Ra0, Rb1, Rc, Rb2, Rb3, Re, Rd, and Rg1 and low level ginsenosides mRb1, mRc, mRb2, mRd, and F2. Low level ginsenosides were first time to be discovered as possible nootropic compounds. This method may shed light on fast discovery of bioactive compounds of medicinal plants with low level compounds.