The distribution of Minuartia verna and Thlaspi alpestre in the British Isles in relation to 13 soil metals

The plant-communities from habitats of the metallophyte species Minuartia verna and Thlaspi alpestre (T. caerulescens) at sites disturbed and undisturbed by mining are described. Four communities were delineated by cluster and principal component analysis. Group 1 comprised species-poor communities on disturbed non-calcareous soils; group 2, relatively species-rich communities on disturbed calcareous soils; group 3, species-rich communities in the main on undisturbed calcareous soils. Group 4 consisted of species-rich communities with an alpine element, in damp habitats on base-rich soils derived from igneous rocks. Total and exchangeable elements As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb and Zn were determined for the soils of these sites. Levels of soil Ca, Cd, Pb and Zn accounted for most of the variation along the first axis of the PCA and soil nutrient levels were probably the main predictor along the second.Abbreviations PCA Principal Component Analysis     

空间独立成分分析实现fMRI信号的盲分离

独立成分分析（ICA）在功能核磁共振成像（fMRI)技术中的应用是近年来人们关注的一个热点。简要介绍了空间独立成分分析（SICA）的模型和方法,将fMRI信号分析看作是一种盲源分离问题,用快速算法实现fMRI信号的盲源分离。对fMRI信号的研究大多是在假定已知事件相关时间过程曲线的情况下,利用相关性分析得到脑的激活区域。在不清楚有哪几种因素对fMRI信号有贡献、也不清楚其时间过程曲线的情况下,用SICA可以对fMRI信号进行盲源分离,提取不同独立成分得到任务相关成分、头动成分、瞬时任务相关成分、噪声干扰、以及其它产生fMRI信号的多种源信号。     

Quality control of Pulsatilla koreana based on the simultaneous determination of triterpenoidal saponins by HPLC‐ELSD and principal component analysis

Introduction – Pulsatilla koreana Nakai, with triterpenoidal saponins as its main pharmacological effective compounds, is known to have several biological activities, including hypoglycaemic, antitumour, cognition‐enhancing, neuroprotective, cytotoxic and antiangiogenic activities. However, few analytical methods have been reported on the quality assessment of P. koreana roots. Obejective – To establish a high‐performance liquid chromatography coupled with evaporative light scattering detection for the simultaneous determination of five triterpenoidal saponins, including pulsatilloside E (1), pulsatilla saponin H (2), anemoside B₄ (3), hederacolchiside E (4) and cussosaponin C (5) in P. koreana. Methodology – The chromatographic separation was performed on a Shiseido CapCell PAK C₁₈ analytical column efficiently using gradient elution with acetonitrile and water. Results – All calibration curves showed excellent linear regressions (R² > 0.9996) within the range of tested concentrations. The intra‐ and inter‐day variations were below 4.78% in terms of RSD. The recoveries were 94.82–102.97% with RSD of 0.27–3.92% for spiked P. koreana samples. Conclusion – The validated method was successfully used for the analysis of five saponins in P. koreana from different locations. Moreover, the different samples were clustered in accordance with contents of triterpenoidal saponins based on aglycon type by a principal component analysis. Copyright © 2010 John Wiley & Sons, Ltd.     

黄山松土壤可溶性有机质对氮添加的响应及其与细菌群落的关联

为探究黄山松土壤可溶性有机质(DOM)数量和质量对短期氮(N)添加的响应及其与细菌群落的关联,在福建戴云山自然保护区设置不同N添加水平(0、40和80 kg N·hm^-2·a^-1)试验,采用三维荧光与平行因子联用法,并结合高通量测序手段分别对土壤DOM和细菌群落进行分析。结果表明: 与对照相比,N添加整体降低了0～10和10～20 cm土层可溶性有机碳(DOC)含量和DOM腐殖化指数(HIX),其中,高氮(80 kg N·hm^-2·a^-1)添加下均显著降低。平行因子分析法进一步表明N添加下DOM中类腐殖质组分(C1、C2)的相对含量降低。此外,N添加减少了富营养细菌(变形菌门、酸微菌纲)的相对丰度,而增加了贫营养细菌(斯巴达杆菌纲)的相对丰度。富营养细菌的相对丰度与HIX、C1、C2呈显著正相关,与相对易分解的类富里酸组分(C3)呈显著负相关;而贫营养细菌的情况则相反。说明N添加下不同生活策略的细菌类群对DOM中难分解和易分解组分存在明显的偏好性。我们推测N沉降加剧背景下土壤微生物生活策略的转变可能有助于DOM组分的塑造。     

皱叶留兰香迁地栽培后的营养成分及抗性指标测定

皱叶留兰香 (ＭｅｎｔｈａｃｒｉｓｐａｔｅＳｃｈｒａｄ .ｅｘＷｉｌｌｄ .)为唇形科薄荷属 (ＭｅｎｔｈａＬ .)多年生宿根草本植物 ,原分布于地中海沿岸 ,我国云南及贵州等地也有分布。皱叶留兰香及薄荷属某些种类 ,在民间被广泛药用和食用。具有疏风散热、辟秽解毒之功效 ,常用于外感风热、头痛、目赤、食滞气胀、口疮、牙痛等症[1 ] ,现代研究表明薄荷属植物还具有抗病毒、杀菌、抗刺激、利胆[2 ] 及放疗区域皮肤保护[3] 等作用。食用则具有清凉芳香的口味特点 ,在我国西南地区已经成为普通蔬菜 ,广泛用于调料、生食和火锅等。作者对皱…     

60Co-r射线辐照对几种植物提取物有效成份的影响

以贯叶连翘,银杏,枳实,红车轴草,当归,灵芝,茶提取物为研究对象,采用^60Co-r辐照新技术,研究了10kGy辐照剂量对它们有效成份的影响。结果表明：辐照对贯叶连翘,银杏,枳实,红车轴草,当归,灵芝几种提取物的有效成份无明显影响;辐照后绿茶提取物中儿茶素含量较对照下降5．29％,普洱茶提取物中茶多酚含量较对照增加9．45％。     

西洋参有效成分与气候生态因子的关系

通过回归分析、灰色关联分析等方法系统地分析了气候生态因子对西洋参有效成分含量的影响,结果表明：温度和日照是影响西洋参总皂甙含量的主要气候因子;其总皂甙的含量与总氨基酸的含量呈显著负相关,故气候因子对二者的作用方向相反;影响西洋参醚浸出物、醇浸出物以及水溶性浸出物含量的主要气候因子均为气温日较差和日照时。     

Chemodiversity of Volatile Oils in Thapsia garganica L. (Apiaceae)

The chemical composition of the volatile oils obtained from the roots, leaves, flowers, and stems of Thapsia garganica of Tunisian origin was investigated by GC‐FID and GC/MS analyses. Sesquiterpene hydrocarbons and oxygenated monoterpenes were predominant in the oils of all plant parts. Bicyclogermacrene (21.59–35.09%) was the main component in the former compound class, whereas geranial (3.31–14.84%) and linalool (0.81–10.9%) were the most prominent ones in the latter compound class. Principal‐component (PCA) and hierarchical‐cluster (HCA) analyses revealed some common constituents, but also significant variability amongst the oils of the different plant parts. This organ‐specific oil composition was discussed in relation to their biological and ecological functions. For the evaluation of the intraspecific chemical variability in T. garganica, the composition of the flower volatile oils from four wild populations was investigated. Bicyclogermacrene, linalool, and geranial were predominant in the oils of three populations, whereas epicubenol, β‐sesquiphellandrene, and cadina‐1,4‐diene were the most prominent components of the oil of one population. PCA and HCA allowed the separation of the flower oils into three distinct groups, however, no relationship was found between the volatile‐oil composition and the geographical distribution and pedoclimatic conditions of the studied populations.     

基于神经网络的马尾松叶绿素含量高光谱估算模型

分析不同生长期的马尾松冠层反射光谱特征与相应叶绿素含量的相关关系.利用36个红边参数逐一筛选,最终确定7个与叶绿素含量相关性较高的红边参数作为光谱特征参数,分别应用逐步分析法与BP神经网络构建叶绿素含量的高光谱估算模型;同样,筛选出4个植被指数作为光谱特征参数,同时,将对原始光谱进行主成分分析降维后的前4个主成分作为BP神经网络的输入变量,分别应用逐步分析法与BP神经网络构建叶绿素含量的高光谱估算模型.结果表明: 将红边参数作为输入变量建立的逐步回归模型和BP神经网络模型的决定系数(R²)分别为0.5205、0.7253,均方根误差(RMSE)分别为0.1004、0.0848,相对误差分别为6.3%、5.7%.将植被指数作为输入变量建立的逐步回归模型和BP神经网络模型的R²分别为0.5392、0.7064,RMSE分别为0.0978、0.0871,相对误差分别为6.2%、6.0%.基于主成分分析的BP神经网络模型的预测效果最好,R²为0.7475,RMSE为0.0540,相对误差为4.8%.