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。     

基于人工神经网络的叶脉信息提取--植物活体机器识别研究I

叶片的识别是识别植物的重要组成部分,特别在野外识别植物活体尤其重要.叶脉的脉序是植物的内在特征,包含有重要的遗传信息.但由于叶脉本身的多样性,利用单一特征的图像处理方法难以有效地提取叶脉.为了充分利用图像的信息,本文提出了一种基于人工神经网络的叶脉提取方法.该方法利用边缘梯度、局部对比度和邻域统计特征等10个参数来描述像素的邻域特征,并将其作为神经网络的输入层.实验结果表明,与传统方法相比,经过训练的神经网络能够更准确地提取叶脉图像,为进一步的叶片识别打下了良好的基础.     

基于人工神经网络的叶脉信息提取——植物活体机器识别研究Ⅰ

叶片的识别是识别植物的重要组成部分,特别在野外识别植物活体尤其重要。叶脉的脉序是植物的内在特征,包含有重要的遗传信息。但由于叶脉本身的多样性,利用单一特征的图像处理方法难以有效地提取叶脉。为了充分利用图像的信息,本文提出了一种基于人工神经网络的叶脉提取方法。该方法利用边缘梯度、局部对比度和邻域统计特征等10个参数来描述像素的邻域特征,并将其作为神经网络的输入层。实验结果表明,与传统方法相比,经过训练的神经网络能够更准确地提取叶脉图像,为进一步的叶片识别打下了良好的基础。     

植物叶片形态的生态功能、地理分布与成因

叶片是植物与环境进行水气交换的重要场所, 形态多变。叶片形态可直接影响植物的生理生化过程, 反映植物的资源获取策略。该文以叶片大小、叶形、叶缘特征(有无叶齿)和叶型(单、复叶)等形态性状为例, 总结了当前叶片形态的研究进展, 分析了叶形态性状的生态功能, 综述叶片形态的地理分布, 探讨叶片形态性状变化的驱动因素及其对生态系统功能的影响。现有研究主要聚焦于局域尺度的特定类群, 关注叶大小、叶缘具齿性以及叶型的地理分布与生态成因, 发现叶片的形态发育受基因调控, 叶形态性状与其他性状相互权衡, 其空间变异受气温和降水量共同驱动。以叶大小为代表的叶片形态性状影响水分和养分循环, 能够反映气候变化下的群落响应, 也可用于预测生态系统初级生产力。今后应结合新方法获得覆盖度高且区域无偏的数据, 探索叶形态在长时间尺度上的适应性进化, 研究叶形态特征及其对生态系统功能影响的尺度推绎。该文有助于从叶片的角度认识植物对环境变化的响应, 以性状为桥梁将个体适合度、群落动态与生态系统功能联系起来, 能够加深对植物群落生态学和功能生物地理学等相关领域研究进展的了解。     

基于叶形特征的切花菊品种鉴别北大核心CSCD

通过测定、计算获得40个切花菊品种叶片的6个定性分级性状及叶片的长宽比、尖削度、裂片长宽比、裂片开张度等14个叶形结构参数。以6个定性分级性状为变量,用聚类法选取叶形相似性大的18个切花菊品种,通过多元判别分析法对18个品种叶片的形态结构参数进行数值化鉴别。结果表明,18个叶形相似的品种多元判别的平均拟合率为88.28%,达到了判别品种的目的。说明根据叶形的测量数据能对切花菊品种进行有效鉴别。     

基于叶形特征的切花菊品种鉴别

通过测定、计算获得40个切花菊品种叶片的6个定性分级性状及叶片的长宽比、尖削度、裂片长宽比、裂片开张度等14个叶形结构参数。以6个定性分级性状为变量,用聚类法选取叶形相似性大的18个切花菊品种,通过多元判别分析法对18个品种叶片的形态结构参数进行数值化鉴别。结果表明,18个叶形相似的品种多元判别的平均拟合率为88．28％,达到了判别品种的目的。说明根据叶形的测量数据能对切花菊品种进行有效鉴别。     

胡杨叶片碳水化合物及可溶性蛋白特征与叶形变化和个体发育阶段的关系

通过野外调查和室内分析,研究胡杨叶形变化及其碳水化合物及可溶性蛋白含量随个体生长发育阶段的变化规律。结果显示：（1）叶形指数随着胡杨胸径（树龄）的增加以及树冠由基向顶方向而逐渐减小,与树高和胸径均呈现极显著负相关。(2)叶片可溶性糖含量变化与个体发育阶段没有关系,在不同的发育阶段以及树冠的不同垂直空间保持在一个较高的稳定水平;叶片淀粉含量与胸径呈显著负相关,与叶形指数呈显著正相关,与叶片宽度呈极显著负相关;叶片可溶性蛋白含量与叶形指数呈显著正相关,与叶片长度呈极显著正相关。综合分析认为,胡杨叶形变化不仅存在于个体发育的不同阶段,同时存在于树冠的不同垂直空间,胡杨的叶形变化（异形叶性）是因个体发育阶段的不同而出现的生物学特征。在胡杨叶形指数随个体发育阶段、树冠由基向顶方向表现出逐渐减小的过程中,叶片淀粉含量随胸径增加、叶形指数减小和叶片宽度增加而减少;叶片可溶性蛋白含量随叶形指数和叶片长度的减小而减少。胡杨叶片淀粉、可溶性蛋白代谢可能在其叶片长度和宽度变化中具有调节作用。     

叶形标本拓印法

每种植物的叶片都有自己的特征,可以根据这些特征来识别植物。一般多采用压制腊叶标本来保存这些特征。但是腊叶标本易损坏、较难保存。我们采用了拓印法制得叶形标本,效果也不错。具体做法是将叶片展开、压平,叶背放于印泥台上,用手均匀轻轻摩压,取下叶片并将有印泥的一面放在一张白纸上,     

十五种叶形吸虫的数值分类研究

本文对中国15种叶形吸虫成虫的12项成虫形态特征进行了聚类分析和主成分分析,结果表明:运用8种不同的聚类方法所得到的谱系分枝图基本一致,即15种叶形吸虫明显地可分为两大亚群,它们分别与Phyllodistomum和Catoptroides亚属相对应。主成分分析所得到的坐标定位图则进一步证实了这一结果,并且显示了在叶形属吸虫中,成虫体形因素、卵黄腺类型及生殖腺相互位置等特征是该属吸虫的主要分类依据。     

雌雄异株的大戟科植物中叶片大小和形状的性别差异

雌雄异株的大戟科植物中叶片大小和形状的性别差异 作为自然选择的对象,叶片大小和形状能够发挥适应性作用,并且随叶龄而改变。在雌雄异株的植物中,叶片大小和形状因性别而不同,在大多数情况下,雌性的叶片较大。以往研究表明,Adriana tomentosa在叶裂方面存在性别差异。在本研究中,我们探讨了在叶片大小、形状和生理生态等方面是否存在其他性别差异,以及这些差异是否与A. tomentosa的性别适应性和繁殖作用有关。我们测定了生 长在澳大利亚东部的两个不连续种群的雌性和雄性植物的幼叶和老叶的物理化学特征,主要包括：叶面积、周长、锯齿、圆形度、长宽比、圆度以及生态生理指标,包括SLA、干物质质量、叶片水分、RWC、δ ¹³C、δ ¹⁵N同位素比、碳氮含量和碳氮比。同时还测定了叶裂、叶片损伤程度和光合色素含量。在这两个种群中,植物性别显著影响几乎所有与叶片形态相关的参数,如面积、周长、圆形度、长宽比和圆度。与预期相反,我们发现两个种群的雄性具有较大的叶面积且与叶龄无关。雄叶裂片较多,周长较长,但它们较少伸长且锯齿较少。雌性和雄性叶片的生理生态指标差异不大。叶片损伤程度因性别而异,但也因种群而异。叶面积和叶形在性别间的差异不能被生理生态因素所补偿。然而,叶面积可能由其他与叶片形态相关的生理生态机制补偿,因为与雄性相比,雌性的叶面积较小,但叶片锯齿较大。     

基于多尺度曲率植物叶片特征提取

基于B-样条小波计算边缘曲线多尺度曲率函数,根据多尺度信息筛选和定位超过一定曲率闲值的精角点,这样的点代表了边缘曲线的主要信息．文中使用了Canny边缘检测算子和数学形态学方法进行图像预处理,B-样条小波降低对噪声及扰动的灵敏性,以提高真实精角点定位水平．综合[1,2]给出新的角特征矢量,并生成角点特征序列CS和弧段特征序列SS．特征序列可作为自适应-时滞单元混合神经网络的输入,通过学习完成图像分类与识别,对基于植物叶片形状识别种类提供辅助。     

Programmed cell death and tissue remodelling in plants

The use of programmed cell death (PCD) to remodel plants at the cellular, tissue, and organ levels is particularly fascinating and occurs in such processes as tracheary element differentiation, lysigenous aerenchyma formation, development of functionally unisexual flowers from bisexual floral primordia, and leaf morphogenesis. The formation of complex leaf shape through the use of PCD is a rare event across vascular plants and occurs only in a few species of Monstera and related genera, and in the lace plant (Aponogeton madagascariensis). During early development, the lace plant leaf forms a pattern of equidistantly positioned perforations across the surface of the leaf, giving it a lattice-like appearance. Due to the accessibility and predictability of this process, the lace plant provides highly suitable material for the study of developmentally regulated PCD in plants. A sterile lace plant culture system has been successfully established, providing material free of micro-organisms for experimental study. The potential role of ethylene and caspase-like activity in developmentally regulated PCD in the lace plant is currently under investigation, with preliminary results indicating that both may play a role in the cell death pathway.     

Comparison of dwarf bamboos (Indocalamus sp.) leaf parameters to determine relationship between spatial density of plants and total leaf area per plant

The relationship between spatial density and size of plants is an important topic in plant ecology. The self‐thinning rule suggests a ?3/2 power between average biomass and density or a ?1/2 power between stand yield and density. However, the self‐thinning rule based on total leaf area per plant and density of plants has been neglected presumably because of the lack of a method that can accurately estimate the total leaf area per plant. We aimed to find the relationship between spatial density of plants and total leaf area per plant. We also attempted to provide a novel model for accurately describing the leaf shape of bamboos. We proposed a simplified Gielis equation with only two parameters to describe the leaf shape of bamboos one model parameter represented the overall ratio of leaf width to leaf length. Using this method, we compared some leaf parameters (leaf shape, number of leaves per plant, ratio of total leaf weight to aboveground weight per plant, and total leaf area per plant) of four bamboo species of genus Indocalamus Nakai (I. pedalis (Keng) P.C. Keng, I. pumilus Q.H. Dai and C.F. Keng, I. barbatus McClure, and I. victorialis P.C. Keng). We also explored the possible correlation between spatial density and total leaf area per plant using log‐linear regression. We found that the simplified Gielis equation fit the leaf shape of four bamboo species very well. Although all these four species belonged to the same genus, there were still significant differences in leaf shape. Significant differences also existed in leaf area per plant, ratio of leaf weight to aboveground weight per plant, and leaf length. In addition, we found that the total leaf area per plant decreased with increased spatial density. Therefore, we directly demonstrated the self‐thinning rule to improve light interception.     

Leaf cutting‐patterns and general cradle formation process of thirteen Apoderinae (Coleoptera: Attelabidae) in Korea: Cradles of Attelabidae in Korea I

The distinctive feature of leaf‐rolling weevils is their special care for their progeny. In many species among the family Attelabidae, the female recognizes the size and shape of the leaf of the host‐plant and does the leaf cutting by a definite method. The location of cutting line, length and shape becomes the basic information in understanding the most fundamental structure of female's recognition process and cradle formation strategy. Leaf cutting is not only the process of withering the leaf by blocking the water flow along the main vein but also the process of making reversal easy at the leaf‐blade part. The difference in forms of cutting line, leaf blade, interval or dispersion of nibble marks on the stem and pitch of leaf rolling has effects on the shape of the completed cradle. In the present paper we provide leaf‐cutting patterns and the cradle formation process for 13 species of subfamily Apoderinae. We also provide a pictorial key of the cradle for the first time in Korea.     

A simulation study on the importance of size-related changes in leaf morphology and physiology for carbon gain in an epiphytic bromeliad

This study addresses the question of how size-related changes in leaf morphology and physiology influence light absorption and carbon gain of the epiphytic bromeliad Vriesea sanguinolenta. A geometrically based computer model, Y-plant, was used for the three-dimensional reconstruction of entire plants and for calculation of whole plant light interception and carbon gain. Plants of different sizes were reconstructed, and morphological and physiological attributes of young and old leaves, and small and large plants were combined to examine the individual effects of each factor on light absorption and carbon gain of the plant. The influence of phyllotaxis on light absorption was also explored. Departure of measured divergence angles between successive leaves from the ideal 137.5 degrees slightly decreased light absorption. The only morphological parameter that consistently changed with plant size was leaf shape: larger plants produced more slender foliage, which substantially reduced self-shading. Nevertheless, self-shading increased with plant size. While the maximum rate of net CO(2) uptake of leaves increased linearly with plant size by a factor of two from the smallest to the largest individual, the potential plant carbon gain (based on total foliage area) showed a curvilinear relationship, but with similar numerical variation. We conclude that leaf physiology has a greater impact on plant carbon gain than leaf and plant morphology in this epiphytic bromeliad.     

Automatic Detection of Diseased Tomato Plants Using Thermal and Stereo Visible Light Images

Accurate and timely detection of plant diseases can help mitigate the worldwide losses experienced by the horticulture and agriculture industries each year. Thermal imaging provides a fast and non-destructive way of scanning plants for diseased regions and has been used by various researchers to study the effect of disease on the thermal profile of a plant. However, thermal image of a plant affected by disease has been known to be affected by environmental conditions which include leaf angles and depth of the canopy areas accessible to the thermal imaging camera. In this paper, we combine thermal and visible light image data with depth information and develop a machine learning system to remotely detect plants infected with the tomato powdery mildew fungus Oidium neolycopersici. We extract a novel feature set from the image data using local and global statistics and show that by combining these with the depth information, we can considerably improve the accuracy of detection of the diseased plants. In addition, we show that our novel feature set is capable of identifying plants which were not originally inoculated with the fungus at the start of the experiment but which subsequently developed disease through natural transmission.     

3D lidar imaging for detecting and understanding plant responses and canopy structure

Understanding and diagnosing plant responses to stress will benefit greatly from three-dimensional (3D) measurement and analysis of plant properties because plant responses are strongly related to their 3D structures. Light detection and ranging (lidar) has recently emerged as a powerful tool for direct 3D measurement of plant structure. Here the use of 3D lidar imaging to estimate plant properties such as canopy height, canopy structure, carbon stock, and species is demonstrated, and plant growth and shape responses are assessed by reviewing the development of lidar systems and their applications from the leaf level to canopy remote sensing. In addition, the recent creation of accurate 3D lidar images combined with natural colour, chlorophyll fluorescence, photochemical reflectance index, and leaf temperature images is demonstrated, thereby providing information on responses of pigments, photosynthesis, transpiration, stomatal opening, and shape to environmental stresses; these data can be integrated with 3D images of the plants using computer graphics techniques. Future lidar applications that provide more accurate dynamic estimation of various plant properties should improve our understanding of plant responses to stress and of interactions between plants and their environment. Moreover, combining 3D lidar with other passive and active imaging techniques will potentially improve the accuracy of airborne and satellite remote sensing, and make it possible to analyse 3D information on ecophysiological responses and levels of various substances in agricultural and ecological applications and in observations of the global biosphere.