一种快速定量分析药用植物淫羊藿生物碱的方法

建立了基于近红外漫反射光谱的药用植物淫羊藿(Epimedium)生物碱的定量分析方法,测定了9种淫羊藿生物碱的含量。当聚类分析采用主成分分析、数学处理采用2,4,4,1模式、光谱散射校正采用标准正则变换+散射处理及回归分析采用改进最小二乘法时,淫羊藿生物碱近红外定标模型的定量效果最好;定标方程的定标决定系数、交互验证相关系数、定标标准差和交互验证标准差分别为0.899 7、0.845 7、0.168 6和0.085 3。近红外定标模型预测值与常规化学分析值差异很小。应用近红外漫反射光谱法测得9种淫羊藿生物碱的含量介于6.537–20.586 mg·g–1(干重)之间,淫羊藿生物碱的种间差异较大。近红外漫反射光谱法具有快速、简便和无损(不损耗受检材料)的优点,可用于淫羊藿生物碱的研究与开发。     

近红外漫反射光谱法快速测定药用植物淫羊藿总黄酮含量

利用一种基于近红外漫反射光谱技术的淫羊藿总黄酮快速定量分析方法, 测定了淫羊藿属(Epimedium)7个种中总黄酮的含量。研究结果表明, 近红外光谱经二阶导数处理、主成分分析聚类及加权多元离散校正处理后, 采用改进最小二乘法回归得到的定标模型的预测效果最佳; 定标样品集预测方程的定标决定系数、交互验证标准差及交互验证相关系数分别为0.985 5、0.023 0和0.044 3; 检验样品集方程的定标决定系数、检验标准差及偏差分别为0.965 1、0.018和0.006, 达到了快速测定淫羊藿总黄酮含量的要求。该方法为淫羊藿总黄酮的快速定量分析提供了新的依据。     

盐胁迫对两种淫羊藿属植物生长及各器官总黄酮含量的影响

采用不同浓度NaCl(0、100、200、300和500 mmol/L)的Hoagland's培养液处理两种淫羊藿属植物--淫羊藿、箭叶淫羊藿幼苗,处理30 d后分别测定其株高、叶表面积、干物质生物量以及根、茎、叶的总黄酮含量,以明确淫羊藿属两种药用植物的抗盐特性.结果显示:(1)盐胁迫对淫羊藿和箭叶淫羊藿的生长均有影响,随着NaCl处理浓度的增加,淫羊藿、箭叶淫羊藿的株高和叶表面积均逐渐显著减小;各器官干物质生物量逐渐降低,但淫羊藿的干物质下降量较小(不显著),且同一处理下淫羊藿的生物量明显小于箭叶淫羊藿.(2)随着NaCl胁迫浓度的增加,除淫羊藿茎的总黄酮含量一直呈下降趋势外,淫羊藿根、叶和箭叶淫羊藿根、茎、叶均呈现在低浓度范围内总黄酮含量增加,且箭叶淫羊藿的含量高于淫羊藿;而在高浓度盐胁迫下,其总黄酮含量均呈下降的趋势,且淫羊藿的含量高于箭叶淫羊藿.研究表明,淫羊藿的抗盐性明显高于箭叶淫羊藿,适于高盐土壤环境种植,但在低盐环境条件下,种植箭叶淫羊藿可显著提高总黄酮产量并提高经济效益.     

食用调和油中花生油含量的近红外光谱分析

采用偏最小二乘法(PLS)等方法建立了食用调和油中花生油含量定量分析的近红外光谱定标模型。采集食用调和油样品在4 000 cm-1~10 000 cm-1范围内的近红外漫反射光谱,光谱经一阶导数处理后,采用偏最小二乘法建立样品中花生油含量的定标模型,并用Leave-one-out内部交叉验证法对模型进行验证。模型相关系数为0.99961,校正均方根RMSEC为0.830%。比较不同光谱预处理方法对定标模型的影响,结果表明一阶导数Corr.coeff最好。采用不同的化学计量学方法建立的定标模型中以偏最小二乘回归法最理想。     

淫羊藿大花类群花序性状与黄酮成分含量相关性研究

采用三重四级杆串联质谱法(UPLC-MS/MS)分析淫羊藿大花类群总状花序品种与圆锥状花序品种间主要黄酮成分含量差异。质谱采用电喷雾离子源正离子模式(ESI~+)采集,通过多反应监测(MRM)同时对淫羊藿药材中的14种有效成分进行定量分析。含测结果显示圆锥状花序品种黄酮成分含量要明显高于总状花序,而朝鲜淫羊藿成分含量及变化趋势则异于其它花序品种;聚类结果显示,总状花序品种与圆锥状花序品种区分明显,朝鲜淫羊藿在PCA及PLS-DA的得分图中被单独归为一类,与含量分析结果一致,这与朝鲜淫羊藿归于淫羊藿属sect.Macroceras组,而其它中国种类属于sect.Diphyllon组有关。该检测方法灵敏、准确、快速,适用于淫羊藿的定量分析,该实验结果为淫羊藿质量控制、品种选育等提供科学支撑。     

不同品种淫羊藿黄酮类有效成分的主成分分析及对肾阳虚大鼠保护作用的研究

采用HPLC测定不同品种淫羊藿黄酮类即淫羊藿苷、朝藿定A、朝藿定B、朝藿定C4种有效成分含量,结合主成分分析对不同品种淫羊藿进行质量分析与评价,并考察淫羊藿对大鼠肾阳虚保护作用.将实验动物随机分为阳虚模型对照组(模型组)、金匮肾气丸干预组(阳性组)、淫羊藿低(125 mg/kg)、中(250 mg/kg)、高(500 ...     

不同群落类型柔毛淫羊藿总黄酮和淫羊藿苷含量及其与土壤因子的关系

2009年8月,采用高效液相色谱法和紫外分光光度法测定了唐家河自然保护区次生落叶阔叶林红桦群落(群落Ⅰ)、常绿落叶阔叶混交林细叶青冈群落(群落Ⅱ)和常绿阔叶林油樟群落(群落Ⅲ)下生长的柔毛淫羊藿各器官的总黄酮和淫羊藿苷含量,分析其与土壤因子的关系结果表明：柔毛淫羊藿叶片中总黄酮和淫羊藿苷含量最高、茎中最低;群落Ⅰ的柔毛淫羊藿总黄酮和淫羊藿苷含量［(5.32±0.23)%和(0.47±0.05)%］均显著高于群落Ⅱ［(4.06±0.03)%和(0.32±0.01)%］和群落Ⅲ［(4.15±0.07)%和(0.28±0.09)%］;土壤氮含量和pH值对柔毛淫羊藿的总黄酮和淫羊藿苷含量影响较大,柔毛淫羊藿总黄酮和淫羊藿苷含量与土壤全氮和碱解氮呈显著负相关(P<0.05),与土壤pH值呈极显著正相关(P<0.01).土壤较低的氮供应水平和较高的土壤酸度可能使群落Ⅰ柔毛淫羊藿的总黄酮和淫羊藿苷含量增加.     

梯度洗脱法同时快速分离测定不同品种不同部位淫羊藿中7种异戊烯基黄酮类成分的研究

建立一种同时快速分离测定不同品种、不同部位淫羊藿中双藿苷A、淫羊藿属苷A、朝藿定C、淫羊藿苷、淫羊藿属苷C、意卡瑞苷A和去多甲基羟基淫羊藿素7种异戊烯基黄酮类成分的梯度洗脱方法,其中双藿苷A、意卡瑞苷A和去多甲基羟基淫羊藿素为首次报道其含量测定。实验比较了三种不同的梯度洗脱条件和三种不同的提取分离条件,选出了实验的最佳条件:采用RP-HPLC法,以美国WATERS SUNFIRETM-C18为色谱柱,乙腈-水为流动相,梯度洗脱(乙腈:0 min,20%;10 min,40%;15 min,45%;20 min,60%),流速为1 mL/min,检测波长270 nm,在此条件下,30 m in内所有组分均得到了良好的分离。实验同时考察比较了巫山淫羊藿植株不同药材部位和其它十种不同品种淫羊藿中7种异戊烯基黄酮类成分的分布。结果表明:不同品种淫羊藿中黄酮类成分的含量差异很大,但大部分品种以朝藿定C为主;同一品种巫山淫羊藿不同部位中则双藿苷A和朝藿定C的含量较大(在巫山淫羊藿根中,两者的含量分别为现行质量控制指标淫羊藿苷的20倍和30倍),可见巫山淫羊藿显著不同于其它品种的淫羊藿,朝藿定C在其药用效果中可能比淫羊藿苷扮演着更重要的角色尤其是在根部作为药用时,这也为民间将巫山淫羊藿根作为小黄连使用提供了一定的实验支持。结论:对于品种较多,分布资源较广的淫羊藿药材,作为药用时,应注意品种和药用部位,考察药材的内在质量,不能一概而论。实验所得到的方法能被用做淫羊藿植株中二次代谢产物分布的快速考察、筛选符合要求的淫羊藿原药材和淫羊藿制备药物中的质量考察。     

柔毛淫羊藿愈伤组织诱导及其总黄酮和淫羊藿苷含量测定

本研究旨在探讨柔毛淫羊藿愈伤组织的最佳诱导条件和愈伤组织中总黄酮、淫羊藿苷含量。采用正交试验设计方法研究不同外植体、培养基、培养温度和光照条件对柔毛淫羊藿愈伤组织诱导的影响,分光光度法测定愈伤组织中总黄酮含量,高效液相色谱法测定其中淫羊藿苷含量。结果显示,以幼叶为外植体,培养基为N6+2, 4-D 3 mg/L+6-BA 1 mg/L+NAA 0.5 mg/L,在黑暗或弱光(1 000 Lx)和(21±1)℃条件下愈伤组织诱导效果最好;愈伤组织中总黄酮和淫羊藿苷含量分别达5.24%和0.564%,与叶中含量无显著差异。初步建立了柔毛淫羊藿愈伤组织诱导的适宜培养条件,为高产淫羊藿总黄酮和淫羊藿苷的组培苗生产和细胞悬浮培养体系的建立提供了依据。     

偏斜淫羊藿化学成分研究

采用70%乙醇超声波辅助提取偏斜淫羊藿（Epimedium truncatum H.R.Liang）叶片中的类黄酮化学成分,利用LC-MS联用技术鉴定其化合物组成,利用HPLC方法测定其主要活性成分的含量并与药典规定药材箭叶淫羊藿（Epimedium sagittatum）主要活性成分的含量进行比较。结果从偏斜淫羊藿叶片中鉴定出6个化合物：朝藿定B、朝藿定C、淫羊藿苷、3,5,7-三羟基4’-甲氧基-8-异戊烯基黄酮-3-O-α-L-吡喃鼠李糖基（1→2）-α-L-吡喃鼠李糖苷、槲皮素-3-O-鼠李糖甙、山奈苷。该6个化合物均为首次在该植物中发现。偏斜淫羊藿富含朝藿定C,其含量显著高于箭叶淫羊藿主要活性成分的总含量。结果表明LC-MS可以简单、快速地对淫羊藿化学成分进行定性和定量分析,偏斜淫羊藿富含朝藿定C,具有潜在的药用价值。     

Feasibility of Estimating Cu Contamination in Floodplain Soils using VNIR Spectroscopy—A Case Study in the Le’an River Floodplain,China

Heavy metal accumulation can influence the physical, chemical, and ecological processes in the soil ecosystem, and the accumulation of heavy metals has become a serious environmental issue in China, especially in the floodplains downstream from mining and smelting sites. A novel method of estimating the heavy metal contamination of soil is proposed using visible and near-infrared (VNIR) spectroscopy and partial least squares regression (PLSR). Our study focuses on the Le’an river floodplain, Jiangxi Province, China, which houses the largest copper mining operation in China and has suffered a series of environmental setbacks from the extraction of copper. Our study employs PLSR to summarize the relationship between VNIR reflectance spectra and the copper content of collected soil samples, and then estimates copper contamination of the soil using VNIR spectroscopy and the calibrated model. More specifically, with 71 soil samples collected from the Le’an River floodplain, our study aims at (1) exploring the correlation between VNIR and soil constituents, including soil organic matter, total copper, and iron content; (2) assessing the relationship between VNIR determination of copper and the pre-processing of soil samples; and (3) evaluating the performance of data transformation methods in PLSR. The correlation analysis revealed that the mechanism of estimating Cu content lay in its correlation with Fe content. The PLSR model with logarithmic scale transformed copper content and the standard normal variate spectra was chosen for estimating copper contamination from untreated soil samples; the model with logarithmic scale transformed copper content and reflectance spectra was selected for pretreated soil samples. The correlation analyses and regression results in the PLSR models both suggest that the main mechanism for estimating Cu content in this case study lies in its correlation with Fe content. Therefore, the coupling of VNIR spectroscopy and PLSR could serve as an alternative method of monitoring heavy metal contamination of soil.     

Rapid estimation of single cell oil content of solid-state fermented mass using near-infrared spectroscopy

Calibration model using near-infrared reflectance spectroscopy (NIRS) for estimation of SCO content in solid-state fermented mass was established. The NIRS calibration model was derived by partial least-squares (PLS) regression and prediction of SCO contents of independent solid-state fermented mass samples fermented by different oleaginous fungi showed the model to be rapid and accurate, giving R(2)-value higher than 0.9552 and root mean standard error of prediction (RMSEP) value lower than 0.5772%. The established NIRS calibration model could be used to estimate the SCO contents of the solid-state fermented masses and will provide much convenience to the research of SCO production in solid-state fermentation.     

Analysis of Fungal Pellets by UV-Visible Spectrum Diffuse Reflectance Spectroscopy

The application of the UV-visible spectrum diffuse reflectance spectroscopy for the determination of intracellular pH in vivo, for determination of cytochrome content, and for the noninvasive in vivo detection of the redox state of fungal mitochondrial cytochromes in filamentous fungi is introduced. The time course of the intracellular pH values, mitochondrial cytochromes, and CO-binding pigments content and the correlations between the actual redox state of cytochrome aa(3) and saturation of growth medium with oxygen in pellets of the basidiomycete Phanerochaete chrysosporium were determined. As the test microorganism, the yeast Saccharomyces cerevisiae was used. UV-visible spectrum diffuse reflectance spectroscopy proved to be a promising method for the quick and simple analysis of light-impermeable biological structures for which the classical transmittance spectrophotometric methods are difficult to implement.     

Noninvasive determination of hemoglobin and hematocrit using a temperature-controlled localized reflectance tissue photometer

We performed visible/near-infrared optical measurements on the forearm of human subjects. We conducted four studies: one study using a commercial diffuse reflectance spectrometer, and three studies using a breadboard temperature-controlled localized reflectance tissue photometer. Calibration relationships were established between skin reflectance signal and either the reference blood hemoglobin (Hb) concentration or the hematocrit values (Hct). Prediction results were expressed as the prediction correlation coefficient (r(p)) and the standard error for cross-validation prediction (CV-SEP). Using diffuse reflectance measurement, r(p) = 0. 8, CV-SEP = 0.9 g/dL for Hb and r(p) = 0.7, CV-SEP = 3.3% for Hct (n = 40). In a localized reflectance study involving calculating the absorption and scattering coefficients and including effect of change of skin temperature in the calibration model, the best prediction results were r(p) = 0.9, CV-SEP = 0.8 g/dL for Hb and r(p) = 0.8, CV-SEP = 3% for Hct (n = 26). In a second localized reflectance study on a population having diverse skin colors at 34 degrees C, the optimal model led to r(p) = 0.8, CV-SEP = 0.9 g/dL for Hb and r(p) = 0.9, CV-SEP = 2.1% for Hct (n = 28) using the localized reflectance values without deducing the absorption and scattering coefficients. Improvement in the correlation was more noticeable for Hct than for the case of Hb. The photometer was used to screen prospective blood donors with low Hb concentration. It was possible to predict anemic subjects in the limited prospective blood donor population.     

Early pregnancy diagnosis in sheep using near-infrared spectroscopy on blood plasma

The objective of this study was to evaluate the ability of near-infrared reflectance spectroscopy (NIRS) to discriminate between pregnant and nonpregnant ewes in early stages of pregnancy after artificial insemination (AI) from blood plasma. Samples were collected using jugular puncture at 18 and 25 days after AI from 188 Rasa Aragonesa and Ansotana ewes. Plasma samples were analyzed for pregnancy-associated glycoprotein (PAG) and progesterone (P4) using ELISA commercial kits. The spectra of plasma samples were recorded in the visible and near-infrared ranges. The performance of these tests were compared, using as criterion standard the pregnancy status determined using transabdominal ultrasonography at 45 days after AI. Pregnancy rate was 47.9% (90/188). At Day 18, sensitivity was similar in NIRS and P4 tests (98.9% vs. 100%; not significant) and greater than PAG (32.2%; both P < 0.001). Specificity was similar in NIRS and PAG tests (both 100%) and greater than that of P4 (84.7%; P < 0.001). At Day 25, sensitivity and specificity of NIRS and PAG were both 100%. It can be concluded that NIRS was an accurate method of diagnosis of pregnancy at Days 18 and 25 after AI in ewes.     

施用生物炭后土壤有机碳的近红外光谱模型研究与应用

土壤有机碳是影响土壤肥力的最重要因素之一。生物炭由于具有高度芳香化碳结构和发达孔隙结构等特性,可以作为一种土壤改良剂,提高土壤有机碳含量,改善土壤物理结构,近些年成为农业环境领域研究的热点。分别采用传统方法和可见光近红外光谱（VIS-NIRS,400-2500 nm）技术对施加不同用量生物炭的土壤有机碳含量进行检测和对比分析,以期为含生物炭土壤的有机碳分析建立有效预测模型。通过比较不同样本选择方法（Kennard-Stone（KS）,Random selection（RS）和Sample set partitioning based on joint x-y distances（SPXY））和光谱预处理方法（Savitzky-Golay平滑（SG）、倒数的对数log（1/R）、标准正态变量变换（SNV）、一阶导数（Der1）、二阶导数（Der2）和多元散射校正（MSC））,以3种模型（组合间隔偏最小二乘模型（Synergy Interval Partial Least Squares,siPLS）,遗传算法-支持向量机模型（Genetic Algorithm-Support vector machine,GA-SVM）和随机森林模型（Random Forest,RF））来建立生物炭土壤有机碳预测模型。结果表明：（1）施加生物炭增加了土壤有机碳含量,增加幅度随生物炭添加量的提高呈增加趋势;（2）土壤反射率随土壤有机碳含量的增加而降低,在1410、1920和2200 nm光谱附近存在明显的吸收谷;（3）对比3种样本选择方法,KS方法所划分的样本集相对于RS方法和SPXY方法更适用于生物炭土壤有机碳模型的建立;（4）以SG+MSC预处理结合GA-SVM方法建立的模型精度最高,校正集的R_cal²和RMSECV值分别为0.9526和0.4839,验证集的R²_val和RMSEP值分别为0.8598和0.9987,RPD值为2.6017。该模型因具有精度高且模拟效果较好等优点,可用于含生物炭土壤的有机碳含量的科学预测。     

Apple flavonols during fruit adaptation to solar radiation: spectral features and technique for non-destructive assessment

Spectral properties of flavonols of three varieties (Golden Delicious, Antonovka, and Renet Simirenko) of anthocyanin-free apple fruit were investigated with reflectance spectroscopy. The results of spectral and biochemical analyses suggested that fruit reflectance in a broad spectral range 365-430 nm is strongly dependent on and, in sunlit fruit surfaces, governed by flavonols. The build up of peel flavonols (mainly rutin and other quercetin glycosides) resulted in a dramatic decrease of fruit reflectance in this range, flattening of the spectrum, and extending the region with low reflectance (4-5%) to ca. 410 nm. The spectral features observed suggest that flavonols contribute significantly to screening of excessive radiation, not only UV-A, but in the short-wave bands of chlorophyll and carotenoid absorption in the visible part of the spectrum as well. To retrieve quantitatively flavonol content from reflectance spectra, we tested the applicability of an inversion technique developed for non-destructive leaf pigment assessment. The model for flavonol content assessment was suggested in the form (R(-1)410 - R(-1)460)R800, where Rlambda is reflectance at wavelength lambda. The model was linearly related to flavonol content between 8 and 220nmol/cm2 with the coefficient of determination r2=0.92 and root mean square error of flavonol estimation of 20 nmol/ cm2 regardless of cultivar, chlorophyll, and carotenoid content.     

Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis–NIR Spectroscopy

Assessment and monitoring of soil organic matter (SOM) quality are important for understanding SOM dynamics and developing management practices that will enhance and maintain the productivity of agricultural soils. Visible and near-infrared (Vis–NIR) diffuse reflectance spectroscopy (350–2500 nm) has received increasing attention over the recent decades as a promising technique for SOM analysis. While heterogeneity of sample sets is one critical factor that complicates the prediction of soil properties from Vis–NIR spectra, a spectral library representing the local soil diversity needs to be constructed. The study area, covering a surface of 927 km² and located in Yujiang County of Jiangsu Province, is characterized by a hilly area with different soil parent materials (e.g., red sandstone, shale, Quaternary red clay, and river alluvium). In total, 232 topsoil (0–20 cm) samples were collected for SOM analysis and scanned with a Vis–NIR spectrometer in the laboratory. Reflectance data were related to surface SOM content by means of a partial least square regression (PLSR) method and several data pre-processing techniques, such as first and second derivatives with a smoothing filter. The performance of the PLSR model was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to parent materials). The results showed that the models based on the global calibrations can only make approximate predictions for SOM content (RMSE (root mean squared error) = 4.23–4.69 g kg⁻¹; R² (coefficient of determination) = 0.80–0.84; RPD (ratio of standard deviation to RMSE) = 2.19–2.44; RPIQ (ratio of performance to inter-quartile distance) = 2.88–3.08). Under the local calibrations, the individual PLSR models for each parent material improved SOM predictions (RMSE = 2.55–3.49 g kg⁻¹; R² = 0.87–0.93; RPD = 2.67–3.12; RPIQ = 3.15–4.02). Among the four different parent materials, the largest R² and the smallest RMSE were observed for the shale soils, which had the lowest coefficient of variation (CV) values for clay (18.95%), free iron oxides (15.93%), and pH (1.04%). This demonstrates the importance of a practical subsetting strategy for the continued improvement of SOM prediction with Vis–NIR spectroscopy.