新鲜及干燥槲树叶挥发油的GC-MS分析及β-葡萄糖苷酶对其增香作用的研究

研究槲树叶中挥发油的化学成分及β-葡萄糖苷酶对其的增香作用,为进一步开发利用槲树资源提供理论支持.采用水蒸气蒸馏法提取新鲜及干燥槲树叶挥发油,结合气相色谱-质谱联用技术(GC-MS)对其进行分析鉴定,用面积归一化法获得各化合物的相对含量,并对加入β-葡萄糖苷酶前后槲树叶挥发油化学成分进行比较.结果从新鲜槲树叶挥发油中共分离鉴定出32个化合物,干燥槲树叶中72个化合物,表明槲树叶中所含化学成分丰富但新鲜槲树叶与干燥槲树叶中化学成分差别大;加入β-葡萄糖苷酶提高了槲树叶中某些香精成分的相对含量,说明β-葡萄糖苷酶对槲树叶具有增香作用.     

利用激光雷达数据估算韩国森林有效植被面积指数

雷达系统能够同时探测森林的水平结构和垂直结构, 结合地面控制点还可以高精度地描绘森林中的树干、树冠及林下植被. 基于此理念, 通过计算雷达激光束被拦截的比例估算红松(Pinus koraiensis)、日本落叶松(Larix leptolepis)和栎类(Quercus sp.)的有效植被面积指数(PAI_e). 从冠层表面或冠层内部反射的雷达数据中利用k-均值聚类方法提取林隙分数(G_LIDAR), 根据比尔-朗伯吸收定律和G_LIDAR计算PAI_e. 结果显示, 利用雷达数据推算的红松、日本落叶松和栎类的PAI_e与实际测量的PAI_e之间的相关系数分别为0.82, 0.64和0.59. 不同树种之间雷达测量值与实测值之间相关性的差异, 主要来自于叶片与枝条数量的不同. 如果没有树叶, 激光雷达的脉冲只能由枝条反射, 然而枝条的大小往往小于激光雷达的分辨率(1 m), 所以与长满树叶的枝条相比, 光秃的枝条反射雷达脉冲的几率非常小. 因此, 若在春季末期树叶出现后进行此类研究, 估算的准确度将有所提高.     

喜树叶、枝水溶性糖提取的研究

用正交实验结果作方差分析表明：溶剂用量对试验结果有较显著的影响（a=0.10)，提取温度对试验结果也有较大的影响，而提取时间对试验结果的影响不显著。喜树叶中水溶性糖的提取最优方案是A3C2B3，即溶剂用量为60ml，提取温度80℃，提取时间60min；喜树叶水溶性糖的提取最优方案是A2C2B1，即溶剂用量为40ml，提取温度80℃，提取时间20min。通过对喜树叶与枝的成对比较分析，叶与枝的水溶性糖含量无显著差异。     

山葵树叶提取物在力竭运动大鼠中的抗疲劳机制研究

山葵树叶中含有丰富的矿物质和维生素,体外研究证实山葵树叶提取物具有较好的体外抗氧化活性。然而,山葵树叶提取物在体内的抗氧化和抗疲劳作用尚不明确。本研究分别按照100 mg/kg·bw、200 mg/kg·bw和500 mg/kg·bw的剂量对SD大鼠灌胃山葵树叶提取液4周。研究显示,山葵树叶提取物可以剂量依赖性方式提高大鼠的力竭游泳时间(p<0.05)。山葵树叶提取物可显著降低力竭游泳大鼠血清Lac和BUN水平并升高NEFA水平。山葵树叶提取物可提高大鼠的肝糖原和肌糖原含量。山葵树叶提取物可提高大鼠血清和组织SOD、GSH-Px和CAT水平并降低MDA水平。山葵树叶提取物可上调大鼠肝组织中ORM1、CCR5的m RNA和蛋白水平。本研究表明山葵树叶提取物可有效提高力竭游泳大鼠的抗疲劳能力。山葵树叶提取物的抗疲劳作用与减少乳酸堆积、增加脂肪动员、减少糖原分解、提高抗氧化活性有关。此外,山葵树叶提取物的抗疲劳作用与上调ORM1和CCR5的表达有关。     

树叶凋落物在受酸性矿山废水污染溪流中的分解

为了解华南地区酸性矿山废水对溪流中树叶分解的影响,在广东省大宝山矿区附近的1条受酸性矿山废水污染（pH值为2．7—3．4且富含多种重金属元素）的3级溪流中,利用2种孔径（5ram的网袋和0．1ram的布袋）的分解网袋对2种树叶（人面子和蒲桃）进行了为期101d的树叶分解研究。结果表明,人面子树叶网袋和布袋中的树叶干重剩余率分别为39％和48％,而蒲桃树叶网袋和布袋中的干重剩余率仍保持较高的水平,分别为61％和70％。根据指数衰减模型计算出树叶分解的半衰期,人面子树叶在网袋和布袋中的分解半衰期分别为57d和69d,而蒲桃树叶则分别为14-4d和217d。蒲桃树叶的分解速率明显比人面子树叶慢。在网袋中定殖的底栖动物主要是集食者,其中优势类群为摇蚊幼虫,占底栖动物个体总数的99％。摇蚊种群在网袋中的数量波动对2种树叶分解速率的影响并不明显。结果表明,受酸性矿山废水的影响,底栖动物群落的多样性大为减少。同时由于各种金属氧化物在树叶表面的不断沉淀,使树叶处于缺氧状态,抑制了微生物的活动,导致树叶分解速率大为降低。     

翅果油树叶总黄酮含量累计规律及最佳采收期研究

采集7-9月份三种品系的翅果油树叶,检测其水分及总黄酮含量的动态变化。结果8月份采集的三种品系的翅果油树叶中总黄酮含量相对较高,且水分含量相对较少。此外,8月份大宫灯品系朝南方向的翅果油树叶中总黄酮含量高;翅果油树叶含水量和总黄酮含量无直接相关性。研究结果对于翅果油树叶最佳采收时期的确立及对其进一步深入研究提供科学依据,具有一定的实际应用价值。     

一种测量细胞面积的显微光度方法

细胞生物学研究中广泛应用显微分光光度计测定单个细胞中特定物质的含量。通常在测含量的同时还要求获得单个细胞内此种物质分布的面积。对形状规则的被测物质,一般常用目镜测微尺测出长度,再算出面积。但这种方法不仅费时,费力,而且不适于测量形状不规则的单个细胞。我们在采用双区法,在测量物质含量的同时,可以很方便地测出不规则形状细胞內被测物质所占的面积。显微分光光度计测量物质含量的方法中常用的有两种——双区法和双波法。在公式推导中有一项被测物面积:B(1-F),其中(1-F)是测量光阑面积中含有被测物部份所占的百分数,B是测量光阑面积。在双区法中(1-F)=(1-T)/(1-T~*)(其中T~*是测量     

一种测量细胞面积的显微光度方法

细胞生物学研究中广泛应用显微分光光度计测定单个细胞中特定物质的含量。通常在测含量的同时还要求获得单个细胞内此种物质分布的面积。对形状规则的被测物质,一般常用目镜测微尺测出长度,再算出面积。但这种方法不仅费时,费力,而且不适于测量形状不规则的单个细胞。我们在采用双区法,在测量物质含量的同时,可以很方便地测出不规则形状细胞内被测物质所占的面积。显微分光光度计测量物质含量的方法中常用的有两种——双区法和双波法。在公式推导中有一项被测物面积:B(1—F),其中(1—F)是测量光阑面积中含有被测物部份所占的百分数,B是测量光阑面积。     

粤北地区溪流中的树叶分解及大型底栖动物功能摄食群

利用2种孔径(5mm的塑料网袋和0.1mm的布袋)的分解网袋对2种树叶在广东北部的横石水河的3级溪流中,进行了为期101d的树叶分解研究.结果表明:人面子树叶在网袋和布袋中的分解速率分别为0.0247d-1和0.0151d-1;而蒲桃树叶的分解速率则分别为0.0108d-1和0.0095d-1.说明2种树叶在布袋中的分解速率均比网袋慢,且人面子树叶的分解速率比蒲桃树叶快.定殖在2种树叶网袋中的功能摄食群以刮食者的比例最高(36%),其次是集食者(33%)和捕食者(25%),撕食者的比例最低(6%).在实验中后期,人面子树叶上的底栖动物个体总数、优势类群数和密度显著高于蒲桃树叶.说明在亚热带地区的中等级别的溪流中,由于撕食者种类减少,刮食者的类群数及密度对树叶分解速率具有显著影响.对微生物活动的抑制作用和对底栖动物取食的驱避作用使富含单宁成分的蒲桃树叶的分解速率下降.     

酸性培养基对喜树叶片细胞壁降解的影响

在组织培养过程中对喜树叶片外植体进行解剖学观察。发现在组织培养条件下,喜树叶片在培养基的酸性环境中细胞壁呈现模糊微弱降解、明显降解和完全降解直至消失的解剖学特征。在同样的组培条件和相同的时间内,同一喜树叶片不同部位出现细胞壁程度不同的降解和消失现象,可能是喜树叶片因上表皮凸凹不平进而导致其不同部位与酸性培养基接触的程度不同,因而使培养基中的酸性物质对喜树叶片上表皮的不同部位影响出现异质化。本文对培养基中的酸性成分对喜树叶片细胞壁降解的影响有了进一步的认识和理解。     

Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software

A digital image analysis method previously used to evaluate leaf color changes due to nutritional changes was modified to measure the severity of several foliar fungal diseases. Images captured with a flatbed scanner or digital camera were analyzed with a freely available software package, Scion Image, to measure changes in leaf color caused by fungal sporulation or tissue damage. High correlations were observed between the percent diseased leaf area estimated by Scion Image analysis and the percent diseased leaf area from leaf drawings. These drawings of various foliar diseases came from a disease key previously developed to aid in visual estimation of disease severity. For leaves of Nicotiana benthamiana inoculated with different spore concentrations of the anthracnose fungus Colletotrichum destructivum, a high correlation was found between the percent diseased tissue measured by Scion Image analysis and the number of leaf spots. The method was adapted to quantify percent diseased leaf area ranging from 0 to 90% for anthracnose of lily-of-the-valley, apple scab, powdery mildew of phlox and rust of golden rod. In some cases, the brightness and contrast of the images were adjusted and other modifications were made, but these were standardized for each disease. Detached leaves were used with the flatbed scanner, but a method using attached leaves with a digital camera was also developed to make serial measurements of individual leaves to quantify symptom progression. This was successfully applied to monitor anthracnose on N. benthamiana leaves. Digital image analysis using Scion Image software is a useful tool for quantifying a wide variety of fungal interactions with plant leaves.     

大批量测定植物(互花米草)叶面积的一种新方法

叶面积的准确测定是评价生态系统能流、碳流和水分利用的重要基础.目前常用的叶面积测定方法都有其局限性,有些方法快捷、准确,但仅适用于小批量测定;大多数方法很难在较短时间内准确进行大批量测定.本文以互花米草叶面积测定为例,探讨了以扫描仪和叶片干重为基础,结合PHOTOSHOP图像处理技术,大批量、快捷、准确测定植物叶面积的方法--扫描-干重法.结果表明:虚拟正方形叶片边长与叶子像素成幂函数曲线关系,公式为419.85x^1.9693,R≈1.00;用此公式验证扫描-干重法,相对误差仅为3.651%.用扫描-干重法测得的结果与方格法相比无显著差异(P=0.473),表明该方法是可行的.     

用扫描仪及Image J软件精确测量叶片形态数量特征的方法

传统的纸样称重法用来测量离体叶片的面积,烦琐、耗时、精度不高。为寻求一种适合的方法,我们对离体叶片采用扫描仪获取叶片的数字图像,利用Image J软件测量叶片的长、宽、周长、面积及叶柄的长,并与传统的纸样称重测定叶面积法进行比较。结果表明,此方法具有低成本、快速、精确等特点,适用于植物形态学、植物生理生态学、林学及农业等对叶片形态特征的测量研究工作。     

Characterization of leaf boron injury in salt-stressed Eucalyptus by image analysis

Symptoms of boron toxicity (i.e., necrosis of leaf tips and margins) have been observed on eucalyptus trees in the San Joaquin Valley of California where the trees are being tested for their effectiveness at reducing the volume of agricultural drainage effluents. In a controlled, outdoor sand-tank study, Eucalyptus camaldulensis Dehn., Clone 4544 trees were grown and irrigated with combinations of salinity and B to determine their influence on tree growth and water use. Irrigation water quality treatments were prepared to simulate the Na-sulfate salinity, high B nature of these drainage effluents. Electrical conductivities (EC_iw) of the waters ranged from 2 to 28 dS m-1 and B concentrations ranging from 1 to 30 mg L-1. As an integral component of this study , we developed a method to quantify and correlate foliar damage with leaf B concentrations. By scanning both injured and uninjured leaves into computer files and processing with image analysis, we were able to simultaneously correlate salinity stress with its overall effect on leaf area as well as to quantify the relative fraction of leaf area affected by specific-ion (i.e., B) injury. Leaf area was unaffected by B stress but was reduced by salinity only in the younger leaves. Boron injury was correlated with increasing irrigation water B only in older leaves. The relative injured area (RIA) of the older leaves was related to the B concentrations of leaves from trees grown at various salinities . A regression equation was developed from injury data obtained from trees grown under boron and salinity stress for 223 days (r2=0.90). From this relationship, we were able to estimate leaf boron concentrations from injury symptoms in leaves selected at random from main trunk branches of trees grown for 333 days under the same stress conditions. The results suggest that this method may have potential as an effective tool for monitoring the response to toxic levels of boron in eucalyptus, once B toxicity has been established by analytical means. The RIA appears to be mitigated by increased salinity of the irrigation water and is consistent with the general reduction in leaf B by salinity. The interactive effects of boron and salinity on foliar injury depends on the physiological age of the leaf.     

钾元素不同供应水平下玉米叶片的生长与发育

采用沙培法,以玉米品种V1和V2为试验材料,定量分析缺钾对玉米生长和发育的影响.从胚芽鞘叶完全展开时,设置营养液中钾的浓度为3个梯度,分别为KH＝8 mmol·L-1;KM＝4 mmol·L-1;KO＝0 mmol·L-1.从胚芽鞘叶完全展开到吐丝期经常浇这3种营养液.用有效积温来计算玉米生长期间所需热量,把每日完好的叶面积作为玉米生长的衡量指标;每天记录每株玉米的叶片数,不管叶片的大小,作为衡量植株生长发育的方法.在每一个钾元素供应水平上,品种V1和V2的叶片数和自播种以来的受热时间呈直线相关.在KO水平上,V1和V2的发育速率分别是10%和15%,相对于KH水平来说是低的.在11片叶子期间,KO水平上的叶面积大约比KH水平上的低46%,KM水平上的叶面积大约比KH水平上的低25%;在玉米抽雄期,KO水平上的叶面积相对于KH来说减少37%,比KM水平上的少26%.这种差异从抽穗期开始一直保持到吐丝期.     

植物叶形的计算机识别系统

植物叶形是识别植物的重要和常用形态特征,建立计算机自动识别系统对于认识和正确识别植物十分重要.本文论述了植物叶形图像识别系统设计中的图像处理、特征提取及分类识别等问题.本系统采用Visual Basic.Net编程工具设计,在Windows 2000/XP平台上通过叶片图像的输入、变换、平滑和分割等识别过程,实现了叶片图像的形状和叶缘特征的结果输出.实验结果表明,该系统能够很好地识别植物的叶形,对14种植物337份叶片样本的叶形测试准确率达93.2%.为植物识别的进一步研究奠定了基础.     

回归方程法测定紫荆叶面积的比较研究

以紫荆成熟叶片为材料,建立起紫荆的叶面积与其叶长、叶宽、以及叶长×叶宽之间的和幂函数、指数函数、线性回归方程。结果表明,叶长与叶面积、叶宽与叶面积、叶长宽积与叶面积的幂函数、指数函数、线性函数均呈正相关关系。9个回归方程均可用于测算紫荆的叶面积,其中以叶长宽积和叶面积的线性方程测算结果更为精确。     

不同栽培措施对凤丹容器苗生长及生理的影响

分别采用不同基质配比(即泥炭和珍珠岩体积比分别为1：0、2：1和3：1)、不同促侧根措施(包括主根截短和200 mg·L-1 IBA溶液灌根单一措施以及上述2种单一措施的复合措施)和不同栽培容器(包括穴盘、营养钵和无纺布育苗袋)对凤丹( Paeonia ostii T. Hong et J. X. Zhang)容器苗进行培育,分析了容器苗的形态指标、单株质量、根冠比及部分生理指标的差异,并在此基础上筛选出适宜凤丹容器苗培育的栽培措施。分析结果表明：在泥炭-珍珠岩(体积比3：1)混合基质中,凤丹容器苗的单株侧根数、单株地下部鲜质量和干质量、根冠比以及叶片的总叶绿素含量、可溶性糖含量和含水量均显著高于其他基质。采取主根截短单一措施或复合措施后,容器苗的单株叶面积、单株侧根数、单株地下部鲜质量和干质量、根冠比及叶片含水量均显著高于对照(不做任何处理)和采取200 mg·L-1 IBA溶液灌根单一措施的容器苗,其中,采取复合措施的容器苗大部分指标最高。在无纺布育苗袋和营养钵中栽培的容器苗的株高、根颈直径、单株侧根数以及叶片的总叶绿素含量、可溶性糖含量和含水量显著高于在穴盘中栽培的容器苗;其中,在无纺布育苗袋中栽培的容器苗的单株侧根数以及叶片的总叶绿素含量和含水量均最高,且这3个指标显著高于在营养钵中栽培的容器苗。研究结果显示：不同栽培措施对凤丹容器苗的生长及生理均有一定影响,总体上看,对根系的单株侧根数、主根长、地下部质量和根冠比以及叶片的叶面积、总叶绿素含量、可溶性糖含量和含水量的影响均较大。根据实验结果,初步筛选出适宜凤丹容器苗培育的栽培措施,即用无纺布育苗袋,以泥炭-珍珠岩(体积比3：1)混合基质为栽培基质,实施主根截短和200 mg·L-1 IBA溶液灌根复合措施。     

An inexpensive,accurate method for measuring leaf area and defoliation through digital image analysis

We report a protocol using a common desk-top scanner and public domain software for measuring existing leaf area and leaf area removed as a result of herbivory. We compared the accuracy and precision of this method to that of a standard leaf area meter. Both methods were used to measure metal disks of a known area, the area of soybean (Glycine max L.) leaves, and the area removed by simulating leaf feeding with a hole-punch. We varied the amount of injury across a low, medium, and high degree of simulated feeding. The mean area of 10 cm2 and 50 cm2 metal disks was more accurately estimated with the leaf area meter than the desk-top scanner. Leaf area estimates from both methods were highly correlated. The desk-top scanner accurately estimated the leaf area removed from the low, medium, or high degree of simulated leaf feeding. However, the leaf area meter overestimated low levels of simulated feeding injury. Though measuring a leaf's surface area with a desk-top scanner requires two steps (creating a digital image file and calculating the area represented by that image), the overall time required to measure leaf injury is shorter than with a leaf area meter. This relatively simple and inexpensive method of estimating leaf area and feeding damage has advantages in certain experimental situations where a prefeeding measurement of the leaf is impossible or undesirable, or when small amounts of feeding occur.     

Black Spot: a platform for automated and rapid estimation of leaf area from scanned images

Leaf area and its derivatives (e.g. specific leaf area) are widely used in ecological assessments, especially in the fields of plant–animal interactions, plant community assembly, ecosystem functioning and global change. Estimating leaf area is highly time-consuming, even when using specialized software to process scanned leaf images, because manual inputs are invariably required for scale detection and leaf surface digitisation. We introduce Black Spot Leaf Area Calculator (hereafter, Black Spot), a technique and stand-alone software package for rapid and automated leaf area assessment from images of leaves taken with standard flatbed scanners. Black Spot operates on comprehensive rule-sets for colour band ratios to carry out pixel-based classification which isolates leaf surfaces from the image background. Importantly, the software extracts information from associated image meta-data to detect image scale, thereby eliminating the need for time-consuming manual scale calibration. Black Spot’s output provides the user with estimates of leaf area as well as classified images for error checking. We tested this method and software combination on a set of 100 leaves of 51 different plant species collected from the field. Leaf area estimates generated using Black Spot and by manual processing of the images using an image editing software generated statistically identical results. Mean error rate in leaf area estimates from Black Spot relative to manual processing was ?0.4 % (SD = 0.76). The key advantage of Black Spot is the ability to rapidly batch process multi-species datasets with minimal user effort and at low cost, thus making it a valuable tool for field ecologists.