学士学位论文--leavesclassificationandleafmassestimation数模竞赛二等奖
Tsoumakas在文献21提出...
国内图书分类号：TP181 学校代码：10213 国际图书分类号：004.91 密级：公开工学硕士学位论文多类标聚类树分类方法优化及并行化实现硕士研究生：陈武导师：叶允明教授申请学位：工学硕士学科：计算机科学与技术所在单位：深圳研究生院答辩日期：2012年12月授予学位单位：哈尔滨工业大学Classified Index: TP181U.D.C: 004.91Thesis for the Master Degree in Engineering OPTIMIZATION AND PARALLELIZATION OF MULTI-LABEL CLUSTER TREECLASSIFICATION METHODCandidate：Wu ChenSupervisor：Prof.Yunming YeAcademic Degree Applied for：Master of Engineering Speciality：Computer Science & Technology Affiliation：Shenzhen Graduate SchoolDate of Defence：December, 2012Degree-Conferring-Institution：Harbin Institute of Technology哈尔滨工业大学工学硕士学位论文摘要近年来，多类标分类问题成为学术研究的一个热点，多类标分类技术是解决多类标分类和类标排序两大任务的重要技术手段，为了更有效地解决多类标文本分类问题，一种新的基于聚类树的多类标文本分类算法在2011年被提出，并得到了充分的实验验证。
但是基于多类标聚类树文本分类算法在分类策略上也存在着不足，没能充分利用类标间的信息，对样本的分类预测完全依赖于类标掩盖数组和纯度。
同时，随着互联网的发展，数据规模不断扩大，如何在海量数据下加快算法运行速度也是本文关注的问题。
Team#15357 A Model of Leaves’ Classification and Weight Evaluation
Fig.1 Tree diagram
Team#15357
page 2 of 23
Fig.2 Structure of tree
1.1.2 Leaf of a tree
“Typically a leaf is a thin, flattened organ borne above ground and specialized for photosynthesis [3]”, shown as picture below (figure.3)
1.2 Problem Restatement
The shapes of a tree‟s leaves are a response to quite a few different factors; one is its genetic control of gene expression. Referring to the article published by Tomotsugu Koyama on „The Plant Cell‟ November 2010[4], he and his research team carry out an idea that TCP Transcription Factors Regulate the Activities of ASYMMETRIC LEAVES1 and miR164, as Well as the Auxin Response, during Differentiation of Leaves in Arabidopsis. The other is the ecosystem‟s limiting factors such as local temperature, humidity, sunlight, landscape, etc. Both the two factors above will bring huge impacts on leaves, which will be revealed on tree‟s feature attribute. In this paper, we will focus on the relationship between the shape of leaves and the tree‟s feature attribute, and then carry out a mathematical model to provide a solution for categorization of leaves‟ shape. On that basis, we provide realistic formulas of weight calculation separately for leaves. We also do sensitivity, feasibility and accuracy analysis to this method in this paper.
南京农业大学研究生学位论文格式规范(20170510)
附件4农业大学研究生学位论文格式规（2016年12月21日，第十一届校学位评定委员会第八次全会修订）学位论文是研究生从事科研工作成果的主要体现，是研究生申请学位的重要依据。
为了提高研究生学位论文的质量，做到学位论文在容和格式上的规化，特作如下规定：一、论文容要求研究生学位论文应用汉语撰写（特殊学科如外国语言文学、翻译硕士可用本学科语言撰写），国际学生可用英文撰写（必须附中文摘要）。
论文容应层次分明，数据可靠，文字简练，推理严谨，立论正确。
论文容一般应由以下几个主要部分组成：封面、英文封面、原创性声明及授权书（详见附件1）、目录（包括图表目录、符录目录）、中文摘要、英文摘要、符号及缩略语等的说明、论文正文、参考文献、附录、致、攻读学位期间取得的学术成果目录。
具体要求如下：（一）封面采用研究生院印发的统一封面格式，封页上填写分类号、学号、论文题目、作者、指导教师、申请学科门类（学位类别）、一级学科名称、二级学科名称（领域名称，专业学位不设领域可不填写）、研究方向、答辩日期等容。
（二）目录依次列出文的主要章节标题，标题应简明扼要。
（三）中文摘要及关键词容应涉及本项科研工作的目的和意义、研究方法、结论及意义。
注意突出学位论文中具有创新性的成果和新见解的部分。
文字应简短明了。
选择约4—6个关键词。
（四）英文摘要及关键词应与中文摘要及关键词基本相对应，要符合英语语法，语句通顺。
（五）符号说明说明论文中所用符号及缩略语所表示的意义及单位。
未用或所用符号不多的论文可省略此部分。
（六）绪论在论文主体前，容为：该研究工作的实用价值与理论意义；研究背景及国外文献综述；论文所要解决的问题。
通过绪论，读者就能全面了解学位论文的目的、意义和工作容。
切忌将论文目录直接复制作为绪论容。
（七）论文主体论文主体由文献综述与实验两部分组成，也可只含实验部分。
人文学科的论文用实证分析等取代实验部分。
文献综述应将与论文容有关的国外研究进展作回顾与分析，篇幅不宜超过实验部分。
《专业英语》 The Classification of Horticultural Plants
The Classification of Horticultural Plants
Objectives of today’s lecture
Learn some common terms used to group plants
Learn the scientific protocols used to name plants so they can be universally recognized
Biennials
Plants that require all or part of two growing seasons; vegetative growth in the first year, followed by overwintering (low temperature); biennials flower in the second growing season, e.g. hollyhocks, carrot
Forsythia
Maple
Daylily
tulips
Classification based on life cycle
Note that many biennials and perennials are grown as annuals
Root crops such as carrots and beets are grown and harvested in one season before they flower
Limitations of these classification systems
These classifications are not understood throughout the world, in different languages or across cultures
孟德尔--植物杂交实验论文(1865年)英文及中译
Mendel's Paper in EnglishExperiments in Plant Hybridization (1865)by Gregor MendelRead at the meetings of February 8th, and March 8th, 1865[1] Introductory RemarksExperience of artificial fertilization, such as is effected with ornamental plants in order to obtain new variations in color, has led to the experiments which will here be discussed. The striking regularity with which the same hybrid forms always reappeared whenever fertilization took place between the same species induced further experiments to be undertaken, the object of which was to follow up the developments of the hybrids in their progeny.To this object numerous careful observers, such as Kölreuter, Gärtner, Herbert, Lecoq, Wichura and others, have devoted a part of their lives with inexhaustible perseverance. Gärtner especially in his work Die Bastarderzeugung im Pflanzenreiche , has recorded very valuable observations; and quite recently Wichura published the results of some profound investigations into the hybrids of the Willow. That, so far, no generally applicable law governing the formation and development of hybrids has been successfully formulated can hardly be wondered at by anyone who is acquainted with the extent of the task, and can appreciate the difficulties with which experiments of this class have to contend.A final decision can only be arrived at when we shall have before us the results of detailed experiments make on plants belonging to the most diverse orders.Those who survey the work done in this department will arrive at the conviction that among all the numerous experiments made, not one has been carried out to such an extent and in such a way as to make it possible to determine the number of different forms under which the offspring of the hybrids appear, or to arrange these forms with certainty according to their separate generations, or definitely to ascertain their statistical relations.It requires indeed some courage to undertake a labor of such far-reaching extent; this appears, however, to be the only right way by which we can finally reach the solution of a question the importance of which cannot be overestimated in connection with the history of the evolution of organic forms.The paper now presented records the results of such a detailed experiment. This experiment was practically confined to a small plant group, and is now, after eight years' pursuit, concluded in all essentials. Whether the plan upon which the separate experiments were conducted and carried out was the best suited to attain the desired end is left to the friendly decision of the reader.[2] Selection of the Experimental PlantsThe value and utility of any experiment are determined by the fitness of the material to the purpose for which it is used, and thus in the case before us it cannot be immaterial what plants are subjected to experiment and in what manner such experiment is conducted.The selection of the plant group which shall serve for experiments of this kind must be made with all possible care if it be desired to avoid from the outset every risk of questionable results.The experimental plants must necessarily:1.Possess constant differentiating characteristics.2.The hybrids of such plants must, during the flowering period, beprotected from the influence of all foreign pollen, or be easily capable of such protection.The hybrids and their offspring should suffer no marked disturbance in their fertility in the successive generations.Accidental impregnation by foreign pollen, if it occurred during the experiments and were not recognized, would lead to entirely erroneous conclusions. Reduced fertility or entire sterility of certain forms, such as occurs in the offspring of many hybrids, would render the experiments very difficult or entirely frustrate them. In order to discover the relations in which the hybrid forms stand towards each other and also towards their progenitors it appears to be necessary that all member of the series developed in each successive generations should be, without exception, subjected to observation.At the very outset special attention was devoted to the Leguminosae on account of their peculiar floral structure. Experiments which were made with several members of this family led to the result that the genus Pisum was found to possess the necessary qualifications.Some thoroughly distinct forms of this genus possess characters which are constant, and easily and certainly recognizable, and when their hybrids are mutually crossed they yield perfectly fertile progeny. Furthermore, a disturbance through foreign pollen cannot easily occur, since the fertilizing organs are closely packed inside the keel and the anthers burst within the bud, so that the stigma becomes covered with pollen even before the flower opens. This circumstance is especially important. As additional advantages worth mentioning, there may be cited the easy culture of these plants in the open ground and in pots, and also their relatively short period of growth. Artificial fertilization is certainly a somewhat elaborate process, but nearly always succeeds. For this purpose the bud is opened before it is perfectly developed, the keel is removed, and each stamen carefully extracted by means of forceps, after which the stigma can at once be dusted over with the foreign pollen.In all, 34 more or less distinct varieties of Peas were obtained from several seedsmen and subjected to a two year's trial. In the case of one variety there were noticed, among a larger number of plants all alike, a few forms which were markedly different. These, however, did not vary in the following year, and agreed entirely with another variety obtained from the same seedsman; the seeds were therefore doubtless merely accidentally mixed. All the other varieties yielded perfectly constant and similar offspring; at any rate, no essential difference was observed during two trial years. For fertilization 22 of these were selected and cultivated during the whole period of the experiments. They remained constant without any exception.Their systematic classification is difficult and uncertain. If we adopt the strictest definition of a species, according to which only those individuals belong to a species which under precisely the same circumstances display precisely similar characters, no two of these varieties could be referred to one species. According to the opinion of experts, however, the majority belong to the species Pisum sativum; while the rest are regarded and classed, some as sub-species of P. sativum, and some as independent species, such as P. quadratum, P. saccharatum, and P. umbellatum. The positions, however, which may be assigned to them in a classificatory system are quite immaterial for the purposes of the experiments in question. It has so far been found to be just as impossible to draw a sharp line between the hybrids of species and varieties as between species and varieties themselves.[3] Division and Arrangement of the ExperimentsIf two plants which differ constantly in one or several characters be crossed, numerous experiments have demonstrated that the common characters are transmitted unchanged to the hybrids and their progeny; but each pair of differentiating characters, on the other hand, unite in the hybrid to form a new character, which in the progeny of the hybrid is usually variable. The object of the experiment was to observe these variations in the case of each pair of differentiating characters, and to deduce the law according to which they appear in successive generations. The experiment resolves itself therefore into just as many separate experiments are there are constantly differentiating characters presented in the experimental plants.The various forms of Peas selected for crossing showed differences in length and color of the stem; in the size and form of the leaves; in the position, color, size of the flowers; in the length of the flower stalk; in the color, form, and size of the pods; in the form and size of the seeds; and in the color of the seed-coats and of the albumen [cotyledons]. Some of the characters noted do not permit of a sharp and certain separation, since the difference is of a "more or less" nature, which is often difficult to define. Such characters could not be utilized for the separate experiments; these could only be applied to characters which stand out clearly and definitely in the plants. Lastly, the result must show whether they, in their entirety, observe a regular behavior in their hybrid unions, and whether from these facts any conclusion can be reached regarding those characters which possess a subordinate significance in the type.The characters which were selected for experiment relate:1.To the difference in the form of the ripe seeds. These are eitherround or roundish, the depressions, if any, occur on the surface, being always only shallow; or they are irregularly angular anddeeply wrinkled (P. quadratum).2.To the difference in the color of the seed albumen (endosperm).The albumen of the ripe seeds is either pale yellow, bright yellow and orange colored, or it possesses a more or less intense green tint. This difference of color is easily seen in the seeds as their coats are transparent.3.To the difference in the color of the seed-coat. This is eitherwhite, with which character white flowers are constantlycorrelated; or it is gray, gray-brown, leather-brown, with orwithout violet spotting, in which case the color of the standardsis violet, that of the wings purple, and the stem in the axils of the leaves is of a reddish tint. The gray seed-coats become dark brown in boiling water.4.To the difference in the form of the ripe pods. These are eithersimply inflated, not contracted in places; or they are deeplyconstricted between the seeds and more or less wrinkled (P.saccharatum).5.To the difference in the color of the unripe pods.They are eitherlight to dark green, or vividly yellow, in which coloring the stalks, leaf-veins, and calyx participate.*6.To the difference in the position of the flowers. They are eitheraxial, that is, distributed along the main stem; or they areterminal, that is, bunched at the top of the stem and arrangedalmost in a false umbel; in this case the upper part of the stem is more or less widened in section (P. umbellatum).7.To the difference in the length of the stem.The length of the stemis very various in some forms; it is, however, a constant character for each, in so far that healthy plants, grown in the same soil, are only subject to unimportant variations in this character. In experiments with this character, in order to be able todiscriminate with certainty, the long axis of 6 to 7 ft. was always crossed with the short one of 3/4 ft. to 1 and 1/2 ft.Each two of the differentiating characters enumerated above were united by cross-fertilization. There were made for the1st trial 60 fertilizations on 15 plants.2nd trial 58 fertilizations on 10 plants.3rd trial 35 fertilizations on 10 plants.4th trial 40 fertilizations on 10 plants.5th trial 23 fertilizations on 5 plants.6th trial 34 fertilizations on 10 plants.7th trial 37 fertilizations on 10 plants.*One species possesses a beautifully brownish-red colored pod, which when ripening turns to violet and blue. Trials with this character were only begun last year.From a larger number of plants of the same variety only the most vigorous were chosen for fertilization. Weakly plants always afford uncertain results, because even in the first generation of hybrids, and still more so in the subsequent ones, many of the offspring either entirely fail to flower or only form a few and inferior seeds.Furthermore, in all the experiments reciprocal crossings were effected in such a way that each of the two varieties which in one set of fertilizations served as seed-bearer in the other set was used as the pollen plant.The plants were grown in garden beds, a few also in pots, and were maintained in their natural upright position by means of sticks, branches of trees, and strings stretched between. For each experiment a number of pot plants were placed during the blooming period in a greenhouse, to serve as control plants for the main experiment in the open as regards possible disturbance by insects. Among the insects which visit Peas the beetle Bruchus pisi might be detrimental to the experiments should it appear in numbers. The female of this species is known to lay the eggs in the flower, and in so doing opens the keel; upon the tarsi of one specimen, which was caught in a flower, some pollen grains could clearly be seen under a lens. Mention must also be made of a circumstance which possibly might lead to the introduction of foreign pollen. It occurs, for instance, in some rare cases that certain parts of an otherwise normally developed flower wither, resulting in a partial exposure of the fertilizing organs. A defective development of the keel has also been observed, owing to which the stigma and anthers remained partially covered. It also sometimes happens that the pollen does not reach full perfection. In this event there occurs a gradual lengthening of the pistil during the blooming period, until the stigmatic tip protrudes at the point of the keel. This remarkable appearance has also been observed in hybrids of Phaseolus and Lathyrus.The risk of false impregnation by foreign pollen is, however, a very slight one with Pisum, and is quite incapable of disturbing the general result. Among more than 10,000 plants which were carefully examined there were only a very few cases where an indubitable false impregnation had occurred. Since in the greenhouse such a case was never remarked, it may well be supposed that Bruchus pisi, and possibly also the described abnormalities in the floral structure, were to blame.[4] The Forms of the HybridsExperiments which in previous years were made with ornamental plants have already affording evidence that the hybrids, as a rule, are not exactly intermediate between the parental species. With some of the more striking characters, those, for instance, which relate to the form and size of the leaves, the pubescence of the several parts, etc., the intermediate, indeed, is nearly always to be seen; in other cases, however, one of thetwo parental characters is so preponderant that it is difficult, or quite impossible, to detect the other in the hybrid.This is precisely the case with the Pea hybrids. In the case of each of the 7 crosses the hybrid-character resembles that of one of the parental forms so closely that the other either escapes observation completely or cannot be detected with certainty. This circumstance is of great importance in the determination and classification of the forms under which the offspring of the hybrids appear. Henceforth in this paper those characters which are transmitted entire, or almost unchanged in the hybridization, and therefore in themselves constitute the characters of the hybrid, are termed the dominant, and those which become latent in the process recessive. The expression "recessive" has been chosen because the characters thereby designated withdraw or entirely disappear in the hybrids, but nevertheless reappear unchanged in their progeny, as will be demonstrated later on.It was furthermore shown by the whole of the experiments that it is perfectly immaterial whether the dominant character belongs to the seed plant or to the pollen plant; the form of the hybrid remains identical in both cases. T his interesting fact was also emphasized by Gärtner, with the remark that even the most practiced expert is not in a position to determine in a hybrid which of the two parental species was the seed or the pollen plant.Of the differentiating characters which were used in the experiments the following are dominant:1.The round or roundish form of the seed with or without shallowdepressions.2.The yellow coloring of the seed albumen [cotyledons].3.The gray, gray-brown, or leather brown color of the seed-coat, inassociation with violet-red blossoms and reddish spots in the leaf axils.4.The simply inflated form of the pod.5.The green coloring of the unripe pod in association with the samecolor of the stems, the leaf-veins and the calyx.6.The distribution of the flowers along the stem.7.The greater length of stem.With regard to this last character it must be stated that the longer of the two parental stems is usually exceeded by the hybrid, a fact which is possibly only attributable to the greater luxuriance which appears in all parts of plants when stems of very different lengths are crossed. Thus, for instance, in repeated experiments, stems of 1 ft. and 6 ft.in length yielded without exception hybrids which varied in length between 6 ft. and 7 [and] 1/2 ft.The hybrid seeds in the experiments with seed-coat are often more spotted, and the spots sometimes coalesce into small bluish-violet patches. The spotting also frequently appears even when it is absent as a parental character.The hybrid forms of the seed-shape and of the [color of the] albumen are developed immediately after the artificial fertilization by the mere influence of the foreign pollen. They can, therefore, be observed even in the first year of experiment, whilst all the other characters naturally only appear in the following year in such plants as have been raised from the crossed seed.[5] The First Generation From the HybridsIn this generation there reappear, together with the dominant characters, also the recessive ones with their peculiarities fully developed, and this occurs in the definitely expressed average proportion of 3:1, so that among each 4 plants of this generation 3 display the dominant character and one the recessive. This relates without exception to all the characters which were investigated in the experiments. The angular wrinkled form of the seed, the green color of the albumen, the while color of the seed-coats and the flowers, the constrictions of the pods, the yellow color of the unripe pod, of the stalk, of the calyx, and of the leaf venation, the umbel-like form of the inflorescence, and the dwarfed stem, all reappear in the numerical proportion given, without any essential alteration. Transitional forms were not observed in any experiment.Since the hybrids resulting from reciprocal crosses are formed alike and present no appreciable difference in their subsequent development, consequently these results can be reckoned together in each experiment. The relative numbers which were obtained for each pair of differentiating characters are as follows:•Expt. 1. Form of seed. -- From 253 hybrids 7324 seeds were obtained in the second trial year. Among them were 5474 round or roundish ones and 1850 angular wrinkled ones. Therefrom the ratio 2.96:1 is deduced.•Expt. 2. Color of albumen. -- 258 plants yielded 8023 seeds, 6022 yellow, and 2001 green; their ratio, therefore, is as 3.01:1.In these two experiments each pod yielded usually both kinds of seed. In well-developed pods which contained on the average 6 to 9 seeds, it often happened that all the seeds were round (Expt. 1) or all yellow (Expt.2); on the other hand there were never observed more than 5 wrinkled or 5 green ones on one pod. It appears to make no difference whether the pods are developed early or later in the hybrid or whether they spring from the main axis or from a lateral one. In some few plants only a few seeds developed in the first formed pods, and these possessed exclusively one of the two characters, but in the subsequently developed pods the normal proportions were maintained nevertheless.As in separate pods, so did the distribution of the characters vary in separate plants. By way of illustration the first 10 individuals from both series of experiments may serve.Experiment 1 Experiment 2Form of Seed Color of AlbumenPlants Round Angular Yellow Green1 45 12 25 112 27 8 32 73 24 7 14 54 19 10 70 275 32 11 24 136 26 6 20 67 88 24 32 138 22 10 44 99 28 6 50 1410 25 7 44 18As extremes in the distribution of the two seed characters in one plant, there were observed in Expt. 1 an instance of 43 round and only 2 angular, and another of 14 round and 15 angular seeds. In Expt. 2 there was a case of 32 yellow and only 1 green seed, but also one of 20 yellow and 19 green.These two experiments are important for the determination of the average ratios, because with a smaller number of experimental plants they show that very considerable fluctuations may occur. In counting the seeds, also, especially in Expt. 2, some care is requisite, since in some of the seeds of many plants the green color of the albumen is less developed, and at first may be easily overlooked. The cause of this partial disappearance of the green coloring has no connection with thehybrid-character of the plants, as it likewise occurs in the parental variety. This peculiarity is also confined to the individual and is not inherited by the offspring. In luxuriant plants this appearance was frequently noted. Seeds which are damaged by insects during their development often vary in color and form, but with a little practice insorting, errors are easily avoided. It is almost superfluous to mention that the pods must remain on the plants until they are thoroughly ripened and have become dried, since it is only then that the shape and color of the seed are fully developed.•Expt. 3. Color of the seed-coats. -- Among 929 plants, 705 bore violet-red flowers and gray-brown seed-coats; 224 had whiteflowers and white seed-coats, giving the proportion 3.15:1.•Expt. 4. Form of pods. -- Of 1181 plants, 882 had them simply inflated, and in 299 they were constricted. Resulting ratio,2.95:1.•Expt. 5. Color of the unripe pods. -- The number of trial plants was 580, of which 428 had green pods and 152 yellow ones.Consequently these stand in the ratio of 2.82:1.•Expt. 6. Position of flowers. -- Among 858 cases 651 had inflorescences axial and 207 terminal. Ratio, 3.14:1.•Expt. 7. Length of stem. -- Out of 1064 plants, in 787 cases the stem was long, and in 277 short. Hence a mutual ratio of 2.84:1.In this experiment the dwarfed plants were carefully lifted and transferred to a special bed. This precaution was necessary, as otherwise they would have perished through being overgrown by their tall relatives. Even in their quite young state they can be easily picked out by their compact growth and thick dark-green foliage.If now the results of the whole of the experiments be brought together, there is found, as between the number of forms with the dominant and recessive characters, an average ratio of 2.98:1, or 3:1.The dominant character can have here a double signification; namely, that of a parental character, or a hybrid-character. In which of the two significations it appears in each separate case can only be determined by the following generation. As a parental character it must pass over unchanged to the whole of the offspring; as a hybrid-character, on the other hand, it must maintain the same behavior as in the first generation.[6] The Second Generation From the HybridsThose forms which in the first generation exhibit the recessive character do not further vary in the second generation as regards this character; they remain constant in their offspring.It is otherwise with those which possess the dominant character in the first generation. Of these two-thirds yield offspring which display the dominant and recessive characters in the proportion of 3:1, and therebyshow exactly the same ratio as the hybrid forms, while only one-third remains with the dominant character constant.The separate experiments yielded the following results: •Expt. 1. Among 565 plants which were raised from round seeds ofthe first generation, 193 yielded round seeds only, and remained therefore constant in this character; 372, however, gave both round and wrinkled seeds, in the proportion of 3:1. The number of the hybrids, therefore, as compared with the constants is 1.93:1.•Expt. 2. Of 519 plants which were raised from seeds whose albumen was of yellow color in the first generation, 166 yieldedexclusively yellow, while 353 yielded yellow and green seeds in the proportion of 3:1. There resulted, therefore, a division into hybrid and constant forms in the proportion of 2.13:1.For each separate trial in the following experiments 100 plants were selected which displayed the dominant character in the first generation, and in order to ascertain the significance of this, ten seeds of each were cultivated.•Expt. 3. The offspring of 36 plants yielded exclusively gray-brown seed-coats, while of the offspring of 64 plants some had gray-brown and some had white.•Expt. 4. The offspring of 29 plants had only simply inflated pods;of the offspring of 71, on the other hand, some had inflated and some constricted.•Expt. 5. The offspring of 40 plants had only green pods; of the offspring of 60 plants some had green, some yellow ones.•Expt. 6. The offspring of 33 plants had only axial flowers; of the offspring of 67, on the other hand, some had axial and some terminal flowers.•Expt. 7. The offspring of 28 plants inherited the long axis, of those of 72 plants some the long and some the short axis.In each of these experiments a certain number of the plants came constant with the dominant character. For the determination of the proportion in which the separation of the forms with the constantly persistent character results, the two first experiments are especially important, since in these a larger number of plants can be compared. The ratios 1.93:1 and 2.13:1 gave together almost exactly the average ratio of 2:1. The sixth experiment gave a quite concordant results; in the others the ratio varies more or less, as was only to be expected in view of the smaller number of 100 trial plants. Experiment 5, which shows the greatest departure, was repeated, and then in lieu of the ratio of 60:40, thatof 65:35 resulted. The average ratio of 2:1 appears, therefore, as fixed with certainty. It is therefore demonstrated that, of those forms which posses the dominant character in the first generation, two-thirds have the hybrid-character, while one-third remains constant with the dominant character.The ratio of 3:1, in accordance with which the distribution of the dominant and recessive characters results in the first generation, resolves itself therefore in all experiments into the ratio of 2:1:1, if the dominant character be differentiated according to its significance as a hybrid-character or as a parental one. Since the members of the first generation spring directly from the seed of the hybrids, it is now clear that the hybrids form seeds having one or other of the two differentiating characters, and of these one-half develop again the hybrid form, while the other half yield plants which remain constant and receive the dominant or the recessive characters in equal numbers.[7] The Subsequent Generations From the HybridsThe proportions in which the descendants of the hybrids develop and split up in the first and second generations presumably hold good for all subsequent progeny. Experiments 1 and 2 have already been carried through 6 generations, 3 and 7 through 5, and 4, 5, and 6 through 4, these experiments being continued from the third generation with a small number of plants, and no departure from the rule has been perceptible. The offspring of the hybrids separated in each generation in the ratio of 2:1:1 into hybrids and constant forms.If A be taken as denoting one of the two constant characters, for instance the dominant, a the recessive, and Aa the hybrid form in which both are conjoined, the expressionA + 2Aa + ashows the terms in the series for the progeny of the hybrids of two differentiating characters.The observation made by Gärtner, Kölreuter, and others, that hybrids are inclined to revert to the parental forms, is also confirmed by the experiments described. It is seen that the number of the hybrids which arise from one fertilization, as compared with the number of forms which become constant, and their progeny from generation to generation, is continually diminishing, but that nevertheless they could not entirely disappear. If an average equality of fertility in all plants in all generations be assumed, and if, furthermore, each hybrid forms seed of。
落花与凋落叶混合比例对黄土丘陵区刺槐林地凋落物分解的影响
植物科学学报 2023，41（2）：183～192Plant Science Journal DOI：10.11913/PSJ. 2095-0837. 22232张晓曦，刘凯旋，田爽，刘洪妤，王羿人，张蔓，王星，曾磊. 落花与凋落叶混合比例对黄土丘陵区刺槐林地凋落物分解的影响[J]. 植物科学学报，2023，41（2）：183−192Zhang XX，Liu KX，Tian S，Liu HY，Wang YR，Zhang M，Wang X，Zeng L. Effects of fallen flower and leaf litter ratios on the decomposi-tion of Robinia pseudoacacia L. forest litter in hilly regions of the Loess Plateau[J]. Plant Science Journal，2023，41（2）：183−192落花与凋落叶混合比例对黄土丘陵区刺槐林地凋落物分解的影响张晓曦1, 2 *，刘凯旋1，田爽1，刘洪妤1，王羿人1，张蔓1，王星1，曾磊1（1. 延安大学生命科学学院，陕西延安 716000； 2. 陕西省红枣重点实验室（延安大学），陕西延安 716000）摘 要：落花是森林凋落物的重要组成部分，明确其在林地凋落物混合分解中的作用有助于理解和预测林地养分的循环过程。
本研究以林龄为33 a的刺槐（Robinia pseudoacacia L.）人工林产生的落花、凋落叶以及落花占比分别为30%、20%、10%和5%的花叶混合凋落物为对象，使用微生物接种法，在室内控制条件下（20℃～25℃、避光恒湿）进行为期62 d的早期分解实验，研究不同比例花叶混合凋落物的分解速率以及碳（C）、氮（N）和磷（P）释放速率的影响。
结果显示：（1）落花比例达到10%时，花叶混合凋落物的分解速率显著高于纯叶凋落物，且当落花比例提高到20%～30%时，混合凋落物的分解速率再次显著提高，但花叶混合并未对凋落物的分解速率产生显著的非加和效应。
基于数字图像处理的树叶识别论文---黄金版要点
目录摘要 (1)英文摘要 (2)1 引言 (2)1.1 选题背景及意义 (3)1.2 国内外研究的进展 (3)1.2.1 树叶识别的研究进展 (3)1.2.2 神经网络的研究进展 (4)1.3 论文的主要内容与组织结构 (4)1.3.1 论文的主要内容 (4)1.3.2 组织结构 (4)2 树叶图像预处理 (4)2.1 图像采集 (4)2.2 图像裁剪 (5)2.3 图像平滑 (6)2.4 图像分割 (8)2.4.1 最大类间方差法 (8)2.4.2 matlab实现及效果图 (8)2.5 边缘检测 (9)3 树叶图像特征提取 (11)4 基于神经网络的树叶识别 (13)4.1 BP网络基本理论 (13)4.2 隐含层数的选取 (13)4.3 节点数的选取 (13)4.4 BP网络的建立 (14)4.5 树叶识别 (14)4.6 GUI界面设计 (14)4.7 结果分析 (16)5 总结与展望 (16)5.1 总结论文的主要工作 (16)5.2 展望论文的不足 (16)参考文献 (16)致谢 (17)基于神经网络的树叶识别系统研究机电与信息工程学院电子信息工程曹文君（20903031002）指导老师：吕军（助教）摘要：植物是生物圈的重要组成部分，其中，叶片是植物的一个重要特征，不同的植物叶片在叶形及叶脉等外部特征上都不尽相同，这就使我们能够很好地利用植物叶片的特征来对植物分类。
过去这类工作是由人工完成，不但工作量大，而且工作效率比较低。
随着数字图像处理技术的快速发展，我们可以有效地借助计算机进行辅助操作，这样可以提高识别的准确性，从而提升了工作效率。
本文重点工作有：应用数字图像处理技术对采集到的叶片做图像预处理；提出了基于BP神经网络的方法进行树叶的识别，并构造了一个基于神经网络的集成分类器模型。
最后，对本系统进行了仿真测试，取得了较好的结果。
关键词：图像处理；神经网络；集成分类器Recognition System of Leaf Images Based onNeuronal NetworkCao Wenjun Director：Lv Jun（A ssistant）(School of Mechanical Electrical and Information Engineering ,Huangshan University , Huangshan,China, 245041)Abstract：The plant is an important component of the biosphere ,and a leaf is a key character of the plant ,different plant may be different in leaf type as well as the leaf vein ,and this enables us to use the plant leaf to carry on the classification of the plant .In the past ,this kind of work was by completes artificially ,the work load was also very heavy ,moreover the working efficiency was relatively quite low .Along with the computer image processing technology's fast development ,we can use the computer to help us with this work ,then enhance the recognition accuracy and promote the working efficiency .The main work of this article includes :use digital image processing technology to pretreat the leaf image ;propose method based on BP neural network recognition of the leaves ,besides ,constructed a model based on neural network ensemble classifier .Finally carried on the experiment test to this system ,hen get to the good result .Key Words：image processing；neural network；ensemble classifier1 引言1.1选题背景及意义大千世界，植物是普遍存在于自然界的。
外文翻译
外文翻译毕业设计题目：植物叶片的形状特征提取及分类研究原文1： Shape based leaf image retrieval译文1：基于形状的叶片图像检索原文2：Feature extraction and automatic recognitionof plant leaf using artificial neural network 译文2：利用人工神经网络实现植物叶片的特征提取与自动识别Shape based leaf image retrievalZ. Wang, Z. Chi and D. FengAbstract: The authors prescnt an efficient two-stage approach for leaf image retrieval by using simple shape features including centroid-contour distance (CCD) curve, eccentricity and angle code histogram (ACH). In thc first stage, the images that are dissimilar with the query image will be first filtcred out by using ecccutricicy to reduce the search space, and fine retrieval will follow by using all three sets of features in the reduced search space in the second stage. Different from eccentricity and ACH, the CCD curve is ncither scaling-invariant nor rotation-invariant.Therefore, normalisation is required for the CCD curve to achieve scaling invariance, and starting point location is required to achieve rotation invariance with the similarity measure of CCD curves. A thinning-based method is proposed to locate starting points of leaf image contours, so that the approach used is more computationally cfficient. Actually, the method can bencfit other shape representations that are sensitive to starting points by reducing the matching timc in image recognition and retrieval. Experimental results on 1400 leaf images from 140 plants show that the proposed approach can achieve a better retrieval performance than both the curvature scale space (CSS) method and the modified Fourier descriptor (MFD) method. In addition, the twostage approach can achieve a performance comparable to an exhaustive search, but with a much reduced computational complexity.1 IntroductionPlant identification is a process resulting in the assignment of each individual plant to a descending series of related plant groups in ternis of their common characteristics.Such a task is very demanding in biology and agriculture, such as for the discovery of new species, plant resource surveys and plant species database management. So far, this time-consuming process has mainly been carried out by botanists. A significant improvement can be expected if the plant identification can be carried out by a computer, automatically or semautomatically,assisted by image processing and computer vision techniques. By using a computer-aided plant identification system, non-professionals can also identify many plant species. This will promote an interest in studying plant taxonomy and ecology, and lift primary and secondary biology education standards at various levels, and promote the use of infonnation technology for modernising the managcmcnt of botanical gardens,natural reserve parks and forest plantation.A computer plays three major roles in computer-aided plant identification: information storage and retrieval,automatic image and text information processing, and the use of machine learning techniques for deriving decision trees for plant identification. Fig. 1 shows the simplified block diagram that we proposed for a computer-aided living plant identification system. In identifying plant species, huinan beings will observe one or more of the following: the whole plant (form, size etc.), leaves (organisation,shape, margin, venation patterns etc.), flowers(inflorescence, growing position, colour, size, symmetry etc.), stem (shape, nodc, bark patterns, outer character etc.), fruits (size: colour, outer character, quality etc.).Some of these human observations can be carried out bya computer when the corresponding images are provided.However, automatic (machine) plant recognition from colour images is still one of the most difficult tasks in computer vision, duc to: (i) lack of proper models or representations, (ii) a great number of biological variations that a species of plants can take, and (iii) imprecise image prc-processing techniques such as edge detection andcontour extraction, thus resulting in possible missing features. Owing to many difficulties involved, research and development in computer-aided identification is still in its infancy.Plant leaves have an approximately two-dimensional nature an4 therefore, they are most suitable for machine processing. As the shape of plant leaves is one of the most important features for characterising various plants visually, the study of leaf image retrieval schemes will be an important stage for developing a plant identification system. By using such a leaf retrieval subsystem, a user can have a number of top-matched leaves together with their whole plant images and text descriptions displayed on the screen, which will help the user to further refine his/her identification by doing more observations.Im ef a/. [ I ] and Abbasi ef a/. [2] have done some preliminary work on plant recognition and classification with the shape features of plant leaves. Im ef a/. used a hierarchical polygon approximation representation of leaf shape to recognize Acer tree family varieties. A curvature scale space (CSS) image was used to'iepresent leaf shapes for chrysanthemum variety classification by Abbasi et a/. [2]. They represented each object with the maxima of its curvature zero-crossing CSS image contours and the similarity between two different shapes was expressed with a real value by matching their maxima sequences. In most situations, a user may even not know what species a plant is and he/she expects the computer to provide more information for further investigation and decision-making.Shape is one of the most important features for characterizing an object and is commonly used in object recognition,matching and registration. Many investigations on shape representation [3-5], such as chain codes, centroid-contour distance (CCD) curve, medial axis transform (MAT) [6],Fourier descriptors (FDs) [7-91, wavelet descriptors [IO],moment invariants (MI) [ I I ] and deformable templates[12, 4], have been carricd out. All of them perform well for some specific applications with their advantages. There alsn have been some succcssiid applications reportcd in the literature [IZ-14]. An important and essential criterion for shapc representation is that the representation is invariant to translation, scaling and rotation of images or objects. Therefore,much research has also been conducted further on the above basic algorithms to achieve better performance and efficiency. In [7-91. the authors achieved translation, scaling and rotation invariance ofFDs by normalisation and matching methods. These FDs are computationally efficient on either FD extraction or FD matching. Rui er al. [I5] proposed a modified Fourier descriptor (MFD) to achieve translation, scaling and rotation invariance, by considering the distances of FD magnitude and phase angle separately.and to decrease the discrctisation noise. Considering its advantages and computational efficiency, we have chosen it as one of the test methods.In this paper, an application of leaf image retrieval based on three simple sets of shape features is presented. First,we introduce a leaf shape representation with the centrnidcontour distance (CCD) curve. There are two main variations for the idea of the CCD curve: one is that the contourpoints are selected so that the central angles between twn sequential contour points are equal, the other is proposed by Chang et ul. [16]in which high-curvature feature points are selected. To preserve contour information, we make use of all the sample points along contours by following the basic CCD curve idca. It will he demonstrated that this translation-invariant representation can achieve scaling invariancc by normalisation and the rotation invariancc with CCD similarity measure can be achieved by aligning starting points. Considering the exhaustive aligning whichis time-consuming, a thinning-based starting-point location method is proposed to reduce the matching time. Actually,such a method will benefit other shape representations which are sensitive to starting points. On the other hand,an angle code histogram (ACH) is adopted to characterize local fcatures of the leaf shape, because the CCD curvc is poor in characterising the local details after being normalised.After studying the ways for leaf classification by botanists,we propose using a two-stage approach which makes use of the eccentricity measure only in the first stage so as to further reducethe rctrieval time, ACH and the CCD curve are combined with the eccentricity feature in the second stage of fine retricval.2 Centroid-contour distance (CCD) curveTracing a leaf contour can be considered as circling around its centroid. The tracing path along one direction (clockwise or anticlockwise) from a fixed starting point represents a shape contour uniquely, i.e. a contour point sequence corresponds to a shape uniquely ifthe starting point is fixed.This is actually the basic idea for the chain code representation of a shape.作者：Z. Wang, Z. Chi and D. Feng国籍：中国出处：/xpl/articleDetails.jsp?tp=&arnumber=1192289&queryText%3DShape+based +leaf+image+retrieval基于形状的叶片图像检索摘要：作者呈现了一种二阶段的高效方式实现叶片图像检索，这种方式使用轮廓质心距离曲线（CCD）、偏心率和倾角码直方图（ACH）这些简单的图形特征来完成。
基于并行残差卷积神经网络的多种树叶分类
文献标识码：A
Multiple types of leaves ′ classification based on parallel
residual convolution neural network
WEI Shuwei，ZENG Shangyou，ZHOU Yue，WANG Xinjiao
（College of Electronic Engineering，Guangxi Normal University，Guilin 541004，China）
normalization；testing effect contrast
引
（K⁃Nearest Neighbor，KNN）[2] 等被引入，然而，随着大数
言
据时代的到来，这些传统的分类算法暴露出越来越多的
世界上没有完全相同的两片树叶，但是同一种树木
不足，比如难以提取特征和训练时间过长等。
20 世纪 60 年代开始，学者们相继提出了各种人工
and the testing effects of the two networks are contrasted. The accuracy obtained with the above two methods are respectively
15.36% and 9.36% higher than that obtained with the traditional Alexnet network，and the highest accuracy reaches 90.67%，
2020 年 5 月 1 日
第 43 卷第 9 期
96
DOI：10.16652/j.issn.1004⁃373x.2020.09.023
基于植物图像的甘蓝型油菜叶片面积测量方法
武汉轻工大学学报Journal of Wuhan Polytechnic University Voy.40No.2Ape.2021第40卷第2期2021年4月文章编号：2095-386(2021)02-0018-06DOI：10.3969/j.issn.2095-386.2021.02.004基于植物图像的甘蓝型油菜叶片面积测量方法陈家茜，刘昌华（武汉轻工大学数学与计算机学院，武汉430023）摘要：针对使用Otus阈值法对叶片进行分割时存在的误差大、分割后目标区域不完整的问题,提出了一种基于分水岭算法对甘蓝型油菜叶片进行分割的方法#首先使用拍摄设备在现场采集相关农作物叶片的图像,再通过Sobel算子和形态学操作对叶片进行预处理,之后通过分水岭算法对标记过的植物叶片图像进行分割得到目标图像，最后通过统计目标区域的像素点个数计算叶片面积。
实验结果表明，使用此方法可以解决Otus阈值法分割区域不完整的问题，有效地将测量误差降低在2.2%以下#关键词：植物叶片面积；图像处理；MATLAB；分水岭算法;机器视觉中图分类号:TP301.6文献标识码:ALeaf araa measurament of Brassica napus based on plant imageCHEN Jia-x-,LIU Chang-Uua(SohooyoeMathematoosand ComputeeSooenoe，Wuhan PoyyteohnooUnoeeesoty，Wuhan430023，Ch ona) Abstract:In order to solve the problems of U/v evor and incomplete G/V re-ion in seamenting leaves using OTUs thresholf method,a method based on watershed algorithm was proposed G seamenl the leaves of Brassico napus. Usongthosmethod tosegmentpyantyeaeesoan e e otoeeyyompeoeetheaooueaoyoeyeaeaeeameasueement.Foestyy，theomageoeeeyeeantoeop yeaeesosoo y e oted bytheoameeaon sote，and then theyeaeesaeepeepeooe s ed bySobey operator and mo/hologicol operation.After the above operations,the marked plant leaf image is se-mented by wa-teeshed aygoeothmtogetthetaegetomage.Fona y y，theyeaeaeeaosoayouyated byoountongthenumbeeoepoteyson the tar/el area.The expe/mental results show that this method con solve the problem of incomplete OTUs threshold se-mentation,and tfectively reduce the measurement evor to less than2.2%.Key words：pint leaf area%image processing%MATLAB%watershed algorithm%machine vision1引言光合作用、呼吸作用和蒸腾作用是植物类生物生长最重要的化学反应,而这些化学反应都在植物体的叶片上进行。
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Team # 15263 Page 0 of 23Leaves_Classification_and_Leaf_Mass_EstimationLeaves Classification and Leaf Mass EstimationSummaryFor the first problem, we establish our neural network model to classify leaves of trees by taking eight characteristics of leaf into consideration. The eight characteristics consist of sawtooth number, petiole length, blade length, blade width, blade thickness, leaf area and circular degree. Our results are summarized in a conclusion that we classify leaves into fourteen types including linear, lanceolate, oblanceolate, spatulate, ovat, obovate, elliptic, oblong, deltoid, reniform, orbicular, peltate, perfoliate and connate. Our neural network implement the classification task reliably and correctly.For the second problem, we set up our AHP model to figure out the reasons why leaves have the various shapes and come to a conclusion that gene, auxin, climate and disease are the main reasons which lead to various shapes.For the third problem, we discuss this issue from the perspective of growth evolutionary and hormones, build cells mechanic model to solve this problem and sum up the conclusion that the shapes are inclined to minimize overlapping individual shadows that are cast so as to maximize exposure. The shape is effected by the distribution of leaves within the volume of the tree and its branches.For the fourth problem, we use statistical analysis knowledge to analyse the data among tree profiles, branching structure and leaf shapes, after mathematically analyzing, finally find that leaves shapes have a direct relation with the tree profile and branching structure,For the fifth problem,we formulate our volumetric method for leaf mass estimation and linear regression model for seeking and comparing the correlation between the leaf mass and tree height, tree mass and crown volume. We obtain that crown volume has the highest correlation with tree leaf mass. So we make use of the crown volume to estimate the leaf mass.At last ,we write one page summary sheet of our key findings.Key words: neural network, leaf classification, leaf mass estimation, AHP, leaf shape, volumetric method, linear regression modelContentsContents 0Ⅰ. Introduction (1)Ⅱ. Some Definitions (1)Ⅲ. General Assumptions (1)Ⅳ. Symbols (2)Ⅴ. Problem analysis (2)Ⅵ. Models (3)6.1 Neural network model to classify tree leaves (3)6.1.1 Neuromime (3)6.1.2 Multi-layer perceptron network (4)6.1.3 Back-propogation (5)6.1. 4 NN’s use to classify leaves (6)6.2 Studying the reasons of the various shapes that leaves have (6)6.2.1 Set up a AHP model to value these base factors (6)6.2.2 Paired comparison matrix structure (7)6.2.3 Calculation of the weight vector and the consistency test (8)6.3 Optimize leaves shape for maximize exposure (9)6.3.1 Explain and answer requirment (9)6.3.2 Set up a Elastic mechanics model (9)6.4 Tree profile and branching structure’s influence on leaf shape. (10)6.4.1 Analysis about the impact of tree profile to leaf shape (10)6.4.2 Electric tree branch angle’s impact analysis (13)6.5 Estimation of the leaf mass (14)6.5.1 Build up a volumetric model (14)6.5.2 The correlation of leaf mass vs. mean crown radius’s cubic (15)6.5.3 The correlation between the leaf mass and the height of the tree (16)6.5.4 The dry leaf mass vs. the volume of the tree (17)6.5.5 The relationship between the leaf mass and mean crown radius (18)Ⅶ. Conclusions (19)Ⅷ. Strengths and Weakness of the Model (19)Ⅸ. Future Work (20)Ⅹ. References (20)Key Findings (21)Ⅰ. IntroductionAs is known to all，there are not two leaves exactly alike. Plant leaves have diverse and elaborate shapes and venation patterns. The beauty of them has attracted curiosity of many people involving biologists, physicists, mathematician, artists, computer scientists, etc. for a long time. The leaf study of forests and of individual tree is important to understand resource allocation of trees, atmosphere—biosphere exchange processes, and the energy budget, it would also be valuable for individual tree growth.The aim of this article is to develop models for leaf shapes classification and to figure out the main factors which lead to the various leaf shapes. At the same time, we find out the interaction between tree (It’s profile/branching structure) and tree leaf. Though there are so many methods to estimate the leaf mass. We solve this problem through a correlation between the leaf mass and the size characteristics of the tree.Ⅱ. Some Definitions●LeafTo a plant, leaves are food producing organs. Leaves "absorb" some of the energy in the sunlight that strikes their surfaces and also take in carbon dioxide from the surrounding air in order to run the metabolic process of photosynthesis.●Phototropism[1]Phototropism is directional growth in which the direction of growth is determined by the direction of the light source. It causes the plant to have elongated cells on the farthest side from the light. Phototropism is one of the many plant tropisms or movements which respond to external stimuli.●Polar Auxin Transport(PAT) [2]PAT is the regulated transport of the plant hormone auxin in plants. It is an active process, the hormone is transported in cell-to-cell manner and one of the main features of the transport is its directionality (polarity). The polar auxin transport has coordinative function in plant development, the following spatial auxin distribution underpins most of plant growth responses to its environment and plant growth and developmental changes in general.●Apical Dominance[3]It is the phenomenon whereby the main central stem of the plant is dominant over other side stems; on a branch the main stem of the branch is further dominant over its own side branch.Ⅲ. General Assumptions●The influence of variation in thickness of leaves can be neglect.●We do not take the influence of the artificial factor into consideration.●Regardless of the influence of deformation of cell.●We regard the crown of the tree as a half sphere.●The leaves in the crown are evently distributed.●Neglect genic mutation influence.Ⅳ. Symbols（Mark：Other symbols will be given in the specific model）Ⅴ. Problem analysisThe first question requires us to build a mathematical model to describe and classify leaves. We think that the standard of classification is the shape of leaf. So we need to study the characteristics of leaf and to ensure that how to define a type of leaf by the combination of some characteristics. In addition, we should figure out how and how much these characteristics have influence on defining a type of leaf. So we take eight characteristics into consideration including master sawtooth number, petiole length, blade length, blade width, blade thickness, leaf area and circular degree. We find that neural networks hold the capacity to process huge data and can be used to describe cognition, classification and some other intelligent behaviors. So we make a decision to use the neural networks to make a classification of tree leaves.The second question requires us to figure out the reasons that why the leaves have various shapes. It is easy to know that the shape of a leaf mainly decided by the gene of the tree. But we know that the leaves of the same tree always have different shapes with the same genes. So we can draw a conclusion that the shape of leaf is not only decided by the gene of the tree as well as influenced by environmental factors. We choose these factors to analyze the specific influence on the forming process ofthe shape of leaf by using an AHP model.The third question wants us to get know of that whether the leaf have a “hobby ” to keep a state to maximize exposure and minimize overlapping individual shadows that are cast. In addition, if the shape of leaf is effected by the distribution of branches and the volume of the tree. So we should make a survey to make it clear that the relationship between crown ’s surface area and the leaf area of a total tree. Then we need to study the sunshine ’s influence on the formation of leaf.We think the fourth question ’s aim is to research that whether the tree profile or the branching structure has influence on leaf shape. In this question we think that the “profile ” of a tree is the crown, and there is a possibility that different crown has different influence on the leaf shape.The last question is require us to find a correlation between the leaf mass and the size characteristics of the tree (height, mass, volume defined by the profile), and then make use of one or more of this characteristics to estimate the leaf mass of a tree.Ⅵ. Models6.1 Neural network model to classify tree leavesOur duty is to find an approach to how to classify leaves. We use Neural network model NN to classify tree leavesAs for classification, Neural network model is greatly able to get a fairly ideal conclusion. To distinguish one leaf shape patterns from each other, Neural network model is optimal . Through a study sample progress on and off, in which we adjust ()w i accordingly. Eventually our model is so “smart” as to identify different leaf shapes. A leaf sample characterize 8 features as mentioned-above. And it is necessary for us to explain the model and we separate NN as three parts to expatiate.6.1.1 NeuromimeThe follow graph is a base part of NN .Figure 6.1-1： neuromimeSolution to input signal:1p k kj j j u w x ==å(1)Where w is the weight, x is the input node value:k k k v u q =- (2)k is Threshold value:()k k y v j = (3) ()j is activation function, k y is the output of a neuron in the successivelayer. The activation function ()v jis a nonlinear function and is given by: ()()11exp v v j =+- (4) 6.1.2 Multi-layer perceptron networkThis is the main structure of NN .Figure 6.1-2：Multi-layer perceptron networkThe structure of the Artificial Neural Network ANN in this work contains three layers: input, hidden and output layers as shown in figure 6.1-2. We use input layer to input the characteristics of the leaves. Each layer contains ,i j and k nodes. The node is also called neuron or unit. This study summarized eight factors for ANN input, that is to say 8i =. The eight input units are sawtooth number, petiole length, blade length, blade width, blade thickness, leaf area and circular degree.For the hidden layer we make 3j =. The function of the output layer is to output classified information corresponding to the input data. The value of k ranges from the types of leaves we need to identify. The jk w is denoted as numerical weights between input and hidden layers, ij w between hidden and output layers as alsoshown in figure 6.1-2.In fact, as for a sample of “s ”, the input of the hidden layer is: 21s s j jk k k h w I ==å (5)The corresponding output state: 21()()s ss j jk j k k H h w I j j ===å (6)Therefore, the superimposed signal i received is: 332111()ss s jk i ij j ij k j j k h w H w w I j =====邋?(7)The final output of the network is: 332111()()(())ss z s jk i i ij j ij k j j k O h w H w w I j j j j ======邋?(8)We hope the final output is idealization. For example. For example,after learning maple leaf ‘s features, if the output is like the form of ()1,0,1,0,1,1,0, we called the output like this the ideal output, the ideal output is noted for {}s i T .Figure 6.1-2： Different types of shapes ()a Linear. ()b Lanceolate. ()c Oblanceolate. ()d Spatulate. ()e Ovate. ()f Obovate. ()g Elliptic.()h Oblong. ()i Deltoid. ()j Reniform. ()k Orbicular. ()l Peltate. ()m Perfoliate ()n Connate.6.1.3 Back-propogationIn order to minimizing the differences between actual output and desired output ，we choose BP algorithm,which is one part of NN .As set forth, the error obtained when training a pair (pattern) consisting of both input and output given to the input layer of the network is given by: 255,1()()2i i i s E w T O =-å (9)Where 5i T is the i th component of the desired output vector and 5i O is thecalculated output of i th neuron in the output layer.Combine (8) with (9), we can draw: 23255,111()[(())]2jk i ij k s i j k E W T w w I j j ===-邋? (10)This is a nonlinear function which is continuously differentiable. In order to obtain the minimum point and the value, the most convenient is to use the steepest()E W , when 10()()E W E W <, we get the ideal value of the variables ,i j w 6.1. 4 NN ’s use to classify leavesThrough NN , single several models leaves and grouping and number of them. Then , learning each group, NN is acquaintance each models. If want to classify one leaf. We are able to let NN to solve this problem, eventually, we classify the leaf as like-model.6.2 Studying the reasons of the various shapes that leaves have.Leaves have a variety of forms. There are lots of reasons account for leaves varying in shapes and size, listed as follows: Overall, the reasons can be divided into external and internal factors.External factors:● Seasons and climate (including wind, sunlight, moisture, temperature); ● Plant diseases and insect pests;● Artificial factor;Internal factors:● Deformation of cells, moisture loss of Mesophyll cells may cause volumedecrease;● Phytohormone auxin;● Difference gene.we believe that there exits 4 base factors that lead to the variety of leaves shape. They are climate, disease, phytohormone and gene. And we endeavor find out reasons to them.climate: the change of sun shine ，water ，temperature ，humidity which alters leaves shape.disease: through effecting the activity of an enzyme, so that influence leaves shape.Phytohormone auxin: have influence on gene expressiongene: through DNA determine the general leaf shape6.2.1 Set up a AHP model to value these base factorsWe solve this problem based on the reasons listed above. After analyzing all of them, we hold an opinion that human attempt is usually fairly haphazard. Since we view all the leaves ’ living environment is stable, we don ’t take artificial factor intoconsideration. We definite "total impact" as "target layer”, and climate, disease, phytohormone, gene as the "criterion layer". As shown in the following figure 6.2-1:Figure 6.2-1：reasons for the various shapes6.2.2 Paired comparison matrix structureTo analyze the e ffects of electric vehicles’ widespread use on the environment, social, economic and health, we each take two factors:,(,1,2,4)i j C C i j = (11) ,(,1,2,4)i j C C i j = (12)They are used to represent environmental, economic, social and health by turns. All results are available the following pairwise comparison matrix: 1(),0,i j n n i j j i i j A a a a a ´=>=(13)i ij j c a c = (14) Obviously:1ii a = (15) The result we used paired comparison of the paired comparison matrix is:121211232111221111232A 轾犏犏犏犏犏=犏犏犏犏犏臌When we take comparison of them qualitatively, there are five clear hierarchy in people's minds usually, which is expressed as:Table 6.1-1: the meaning of the Measure 1-9 ，6.2.3 Calculation of the weight vector and the consistency testUse MATLAB software to calculate the pairwise comparison matrix for the largest eigenvalue and the maximum eigenvector that the eigenvalue corresponding. Then we will normalization the above-mentioned vector, the normalized results as the weight vector of the comparison factor. Following the results:4.2072,(0.4226,0.3081,0.2563,0.0131)T l z ==Usually, the pairs comparison matrix is not the same array. But if its feature vectors of eigenvalue corresponding can be used as a weight vector of factors to be compared, the extent of its inconsistency should be within the range of:0.1CI CR RI=< (16) Selecting 0.1 in this type has a certain subjective wishes.1n CI n l -=- (17) CI represents consistency index, RI represents its Random Consistency Index, CR represents its consistency ratio.From the equation above we can draw:4.207240.0690741CI -==-From the table above, we can get:4n =The corresponding RI is 0.900.069070.07670.10.90CR ==<This means our model has passed the consistency test, z can be used as a weight vector.From the analysis we elicit a conclusion that gene is maximally impacted, and then gene, phytohormone, climate, dease is following.6.3 Optimize leaves shape for maximize exposure6.3.1 Explain and answer requirmentFrom the model 2’s conclusion we get above, we acquaint that sunlight is a critical factor for plants. Plants are photoautotrophs, obtain their own energy through photosynthesis and produce oxygen in the meantime. From evolutionary considerations, it seems that the leaves always in a favorable direction, so that they can maximize their exposure to the sun. As is considered above, sunlight changes the blade shape through influencing the distribution of growth hormones. Thus we discuss this issue from the perspective of growth hormones. First of all, we need to know more specifically how growth hormones affect leaves. Growth hormones is a directional transport, but sometimes it transports to the backlight. By inhibiting the growth of the shaded side to effects the phototropism movement of plants. Due to this pheno menon leaves “do their best efforts” make themselves exposed. In other words , It is to minimize mutual shading impact. We try to build cells mechanic model to solve this problem, meanwhile, explain reasons for this phenomenon.Conclusion: plants always “optimize ” their leaves shape for maximize exposure. Put another way, they are “minimize” overlapping individual shadows that are cast . The result can primely explain the reasons. 6.3.2 Set up a Elastic mechanics modelWe choose Elastic mechanics model to simplify and imitate Physical force of mesophyll cells. We assume that each cell of leaf is subject to two forces, one is the expansive force in f generated by cytoplasm of cells inside; another one is external tension out f generated by cell wall, as shown in figure 6.3-1.Figure 6.3-1：Elastic rigid modelIn order to describe the two physical forces leaf cells suffered more accurately. We can build contractive spring to present the expansive force of the cell, similarly, tension springs can be used to express the tension between the cells. Therefore, only these two forces balance each other, a cell can stay in stable geometry which can use the following equation to express.0()in out f f k s s =-=--Where S is cells’ original length in the saturated state, 0S presents the length after power expansion and p is external impulse, k represents spring stiffness.This model describe because of the photosynthesis, cells affected by growth hor mones, leading to a result that the shapes “minimize” overlapping individual shadows that are cast, so as to maximize exposure.Thus, a leaf tends to increase the surface area as large as possible to maximize metabolic capacity, because metabolism produces the energy and materials required to sustain and reproduce life.6.4 Tree profile and branching structure’s influence on leaf shape.We strive to explore the relationships between distribution of leaves within the “volume” of the tree and leaves shape.6.4.1 Analysis about the impact of tree profile to leaf shapeWe analyze this problem based on biology. We take the influence of wind into consideration in addition to those four factors above. Especially for those huge trees, spatial distribution would influence the leaf shape, namely the answer to this question is positive. Because of the complexity of genetic mutation, we solve this problembased on environment and auxin without regard to gene mutation. We use the impact of wind instead of environmental influence.Auxins are not synthesized in all cells (even if cells retain the potential ability to do so, only under specific conditions will auxin synthesis be activated in them). For that purpose, auxins have to be translocated toward those sites where they are needed. Translocation is driven throughout the plant body, primarily from peaks of shoots to peaks of roots. Polar auxin transport would lead to phyllotaxis disorder and leaves of different size. (from development mechanism of the leaves). As the result, some leaves well be enriched response to uneven distribution of the auxins.[8] Leaves away from sun may have bigger leaf area to get more sunlight. Due to the influence of wind, the downwind leaves were significantly better than those in upwind direction.Conclusion: leaves shape are influenced by leaves ’ three-dimensional effect at the tree and its branches.6.4.1.1 Set up mathematic functionsSpace analysis on a tree as is shown in figure. Now we choose a leaf located in (,,)x y z to study its’ shape. Determine leaf shape through integrated impacts of auxin, sunlight and wind. We provide a coefficient h to indicate the leaf shape:Figure 6.4-1：Tree space coordinate systemWe provide a coefficient h to indicate the leaf shape:/(*)s l b h =Where s is leaf area, l is the length of leaf, b is the width of leaf. Find out space function expressions about the three factors:Where N is Auxin concentrations, F is Light flux, S is leaf surface, F is wind force, v is wind speed and k is a constant coefficient, which used to quantify the influence of windThen we can get:Auxin concentrations:(,,)N N x y z =Light flux:*T d S F =òLeaves_Classification_and_Leaf_Mass_EstimationWe introduce2(,,)*(,,)F x y z k v x y z = (18)Then we can get:(,,)(,,)(,,)s f N F l g N F b h N F =F =F =F (19)(,,)*(,,)*(,,)*(,,)x y z v x y z x y z N x y z h a b g =+F + (20)where v is weed speed, F is Luminous flux, which used to quantify the influence of wind, ,,a b g is the corresponing weight coefficient.6.4.1.2 Whether tree branching influence leaves shape.Firstly, we believe that the main feature of tree profile would be tree shape. due to the subtle differences of light, temperature, humidity and velocity of wind among different tree shapes ,so that leaf shapes are various. In a word, leaf shapes are relative to tree shapes. There is a graph we can offer.Table 6.4-1: some explanationTable 6.4-2 : The canopy characteristics indexes under different tree shape Tree shape LAIELADPMLAISFDSFCSFOpen cebter shape *1.338a *6.843a *14a *0.203a *0.211a *0.210a Spindle shape 1.807ab 2.359b 34b0.168ab 0.123b 0.129b Disperse lamination shape1.617b4.851ab*19a0.126b0.127b0.128bNote: Different letters in columns of the table show the significant differences(0.05a =)Trees with open cebter shape ()OCS have the advantages of receiving more sunlight. It ’s LAI lower than the other two, 35.1% lower than spindle shape ()SS , 20.9%lower than disperse lamination shape DLS .OCS has larger light site coefficient than the other two shapes. Its’ISF , DSF and GSF are 17.2%、41.7%、 38.6% larger than SS and is 37.9%、39.8%、39.0% larger than DLS .Trees with Spindle shape have growing weakness, no apparent spacing betweenlayers and poor lighting. Its’ LAI is the biggest among the three shapes. Its’ increasing rang of ISF is 25% higher than DLS , its ’ DSF and GSF is 3.3%, 0.8%- lower than DLS .So it is obviously that leaf shape relates to tree shape. 6.4.2 Electric tree branch angle’s impact analysisIn addition to tree profile, tree branch angles also influence leaf shapes. Figure shows different tree branch angle effect on the tree area.When two new branch units (unit 3 and unit 5) arise from the distal end of a previous unit (mother unit) there is a regular asymmetry in the branch angle s (θ1 and θ2, respectively) a previous theoretical model for treelike bodies to develop a reliable computer simulation of tree geometry for this species. The treelike bodies in the original, theoretical model were developed with only two parameters, the ratio of mother to daughter branch unit lengths and the asymmetry of forking.Figure 6.4-2 : T ree branch angle’s impact on leaf area.Figure 6.4-2 is variation of the effective leaf area of a branch tier depending on the branch angles, 1q and 2q . The titer of the five lateral branch complexes is simulated with three orders of bifurcation according to the rules of Terminalia-branching. The divergence angle of the first branch unit of each branch complex equals 138.5. The sign of the branch angles of the first branch unit in each successive branch complex alternate. The ratios of branch lengths of units 3 and 5 to that of their mother unit are 0.94 and 0.87, respectively. The radius of the leaf disk approximation is 0.8 where the length of the longest distal branch unit is unity. Simulations of the branch tiers are projected on a horizontal plane. 1q and 2q , respectively, are as follows: (a)10 and -30-; (b) 40 and 30-; (c)24.6 and 41.4; (d) 10 and 50-; (e) 40 and 50-. Maximum effective leaf area is (c)Figure shows that the observed branch angles result in the maximum effective leaf surface possible for a branch system that follows this pattern of branching. In addition, the natural constraints on bifurcation of lateral branches result in a greatereffective leaf area per leaf cluster than when branching is unrestrained.Conclusion: We get the conclusion that branching pattern in Terminalia is correlated with efficient presentation of leaf surface to direct sunlight rather than simply with maximum total leaf surface.6.5 Estimation of the leaf massAs is known to all, a tree usually has tens of thousands of leaves which we cannot accurately count even by modern instruments. So it ’s hard to calculate the leaf mass of a tree precisely. But we can try to looking for some characteristics which may have a correlation with the leaf mass of a tree. After consulting some articles and books related to calculating the leaf mass, we establish our volumetric method for leaf mass estimation.6.5.1 Build up a volumetric modelA volumetric approach for estimating leaf mass has superiority, because of its relatively simple non-destructive data requirements in field surveys, its potential applicability to the plethora of species found in natural landscapes, and its flexibility in modeling both tree and shrub morphology.A big tree usually has many characteristics, such as stump diameter, crown depth, crown protection, tree height, ground-crown distance ()h , mean crown radius ()r , trunk circum breast height and DBH (diameter at breast height ()d ). We think that “volume defined by the profile” is the crown of the tree. From the names, we know that the characteristics are easy to measure ( Some letters mean is shown below, we put a broad-leaved tree as the research object ).Figure 6. 5-1: some characteristics of a treeIn order to simplify our model and also make our model has more researchsignificance, we choose broad-leaved tree as the research object. We regard the crown of the tree as a half sphere, and through the ball volume formula 343V r p =，we get the volume of the crown.Any three points which can form a unit area on the half sphere form a closed volume with sphere center, we assume that the leaf mass of every closed volume is equal. That is to say, the leaves in the crown are evenly distributed (Schematic diagram is below).Figure 6.5-2: 1s is a unite area and every volume liake green part is equalWe make the leaf mass of the unite volume equal to r ()3/kg m , so the leaf mass of a tree is:323g m V r r pr == (21)From the equation above we can get: the leaf mass of a tree is proportional to the crown r adius’s cubic .6.5.2 The correlation of leaf mass vs. mean crown radius’s cubicIn order to prove the formula above is correct, we find some data in the table 6.5-1 to check the relationship between mean crown radius and dry leaf mass.Table 6.5-1: 14 blue oak trees’s data of mean crown radius and dry leaf mass TreeMean crown radiusCrown r adius’s cubicDry leaf mass(.)no()m()3m()kg1 1.1 1.331 3.752 2 8 9.753 1.1 1.331 2.214 1.4 2.744 5.235 1.8 5.832 6.796 1.2 1.728 1.957 1.1 1.331 4.428 1.5 3.375 5.389 3.6 46.656 29.30 10 1.1 1.331 1.83 11 1.5 3.375 5.23 12 1.2 1.728 2.20 13 1.8 5.832 9.04 142.19.2615.93The figure 6.5-3 shows that the relationship between leaf weight and mean crownradius’s cubic was quite linear. Linear model is chosen to describe the correlation of l eaf mass vs. mean crown radius’s cubic because leaf mass should increase as the square of the crown radius, and for this correlation an 2R of 0.9088 is obtained (Figure 6.5-3).。