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A neural network ensemble method for precision fertilization modeling

A neural network ensemble method for precision fertilization...

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亚洲精细农业与计算机农业应用联合大会

作者： Helong yua,b, Dayou Liua,Guifen Chena,b,Baocheng Wanb,Shengsheng Wanga,Bo Yanga a College of computer Science and technology,Jilin University, Changchun,Jilin Province, P. R. China, 130012 b College of Information technology,Jilin Agricultural University,Changchun,Jilin Province, P. R. China, 130118

There exists nonlinear relationship between fertilizer input and soil nutrient. To calculate the fertilization rate more precisely, a novel neural network ensemble method has been proposed, in which the K-means clustering method is used to select an optimal network individual and Lagrange multiplier is used to combine these selected networks. Based on the above neural network ensemble method, a fertilization model is constructed. In this model, the soil nutrient and the fertilization rate are taken as neural network inputs and yield is taken as output. This model transforms the calculation of fertilization rate into solving a programming problem, which can calculate the fertilization rate with maximum yield and maximum profit as well as forecast the yield. Furthermore, this fertilization model has been tested on the fertilizer effect data. The results show that the forecasting value of neural network ensemble is more accurate than individual neural network. The fertilization model constructed in this paper not only can precisely simulate the nonlinear relationship between yield and soil nutrient but also can adequately make use of the existing fertilizer effect data.

关键词： neural network ensemble precision fertilization clustering algorithm Lagrange Multiplier method

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An Interactive Digital Design System for Corn Modeling

An Interactive Digital Design System for Corn Modeling

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亚洲精细农业与计算机农业应用联合大会

作者： Boxiang Xiao, Xinyu Guo, Xiaohong Du, Weiliang Wen, Xue Wang, Shenglian Lu 1 China National Engineering Research Center for Information technology in Agriculture, Beijing, China, Beijing, P. R. China

An interactive digital design system for corn modeling is presented in this paper. The system designed and developed based on growth model of corn, thus the digital design for corn is suitable for biological and physiological characteristics according to the natural growth process of corn. The framework is supported by agricultural knowledge model in steps: knowledge model, mathematical model, geometric model and display model. Specially, a template-based method is implemented for leaf modeling. The system is composed of several key function modules: computer graphic design, template, geometric modeling, database support, data processing and graphic user interface, and developed by C++ program language based on OpenGL graphic library. Main functions of this system includes plant type design, organs of corn model design, plant model design, corn colony design, display of colony and calculation of light distribution in plant canopy layer. As an interactive digital design tool for corn modeling, the system provides a convenient way for rapid three-dimensional data acquisition and construction.

关键词： Interactive Digital Design System Corn Modeling

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Editorial

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computers and Graphics (Pergamon) 2009年第4期33卷 439-439页

作者： Alvarado, Christine Cani, Marie-Paule Harvey Mudd College Department of Computer Science 1250 N Dartmouth Ave Claremont CA 91711 United States Grenoble University INRIA 655 avenue de l'Europe 38330 Montbonnot France

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Motion Law Analysis And Research of The Ejection Device of Tray Seeder

Motion Law Analysis And Research of The Ejection Device of T...

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亚洲精细农业与计算机农业应用联合大会

作者： Dong Chunwang 1,2 , Hu Bin 1 , Hang lili 1 1.Machinery and Electricity Engineering College, Shihezi University, Shihezi 832003,China 2.Insititute of Cotton The Chinese Academy of Agricultural Sciences Anyang Henan 455000 China

Plug seedling production technique is an important direction of modern facility agriculture, and precision planter is a core component to realize the technique, its seeding performance depend on whether vibration device can upcast the seeds to suspension and free condition. Nowadays, vibration mode of a great number of domestic and foreign planters is continuous excited vibration that by means of electromagnetic vibrator. This mode is easy to occur uneven of the rising height of the seeds and inconsistent of the vibration intensity and other phenomena. This paper studies a new type Seeder, which is independently developed and its special ejection mode can realize precision sowing. The movement mechanism of the ejection device of the air-suction vibration seeder is studied. We obtained the movement rules of the seeds in the vibration plate through the process of theoretical analysis and computer simulation of the movement of the seeds. We optimized the structural design of the seeds plate with the coordinating analysis of finite element simulation, The performance test of the physical prototype shows that the planter has a reliable performance and the rising height of the seeds are even. The studies provide a reasonable structural parameters and the effective theory for research and development of such planting equipment, which has some guiding significance for motion law of the seeds.

关键词： Ejection mechanism, Numerical simulation, Seeder, Motion analysis

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Research on Infield Weeds Detection Technique Based on Machine Vision

Research on Infield Weeds Detection Technique Based on Machi...

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亚洲精细农业与计算机农业应用联合大会

作者： LI Dong-ming Agricultural University of Hebei College of Mechanical and Electrical Engineering, Hebei Baoding 071001

The weed is one of the important factors which affect our country agricultural product quality and output. At present using the herbicide spraying, especially extensive spraying to remove weeds. This kind spraying method not only enhances the agricultural costs, but also undermines the land quality, pollutes the environment, and does not favor the agricultural sustainable development. In response, using computer vision technology to identify weeds and to determine the location and types of weeds was studied in this paper, and it provided theoretical and technical support for accuracy of automated spraying herbicides for the crops field. Main contents are as follows: (1) Introduced the development of weed detection at home and abroad;proposed the research necessity, feasibility and methods. (2) Discussed the pretreatment methods of filtering out the image noise;compared the mean filtering method with median filtering method, the latter was chosen in this experiment. (3) Studied the method which used color characteristic of color image to segment green plants and soil background in view of weed detection in complex background. This paper mainly elaborated segmentation under the RGB and HIS color models. Considered the real time operation, the study used color space and color components, as a characterization of the image color information threshold parameters. Using automatic threshold segmentation realized the segmentation between the weed area and background *** experimental results showed that the classified statistics the different color components obtained color space and the color characteristic components suited green plants and soil background *** was practical and effective that threshold parameters expressing images colors information divided weeds from the background area. (4) In view of the drilling crops, considered the system execution the speed, has first used the position characteristic law recognition between the lines weed;Regarding

关键词： Machine vision, Weed detection, Position feature, Shape feature BP Neural Network

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DESIGN OF ACQUIRING AND PROCESSING PLATFORM OF NEAR-GROUND REMOTE SENSING IMAGES WITH TWO-CHANNEL

DESIGN OF ACQUIRING AND PROCESSING PLATFORM OF NEAR-GROUND R...

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亚洲精细农业与计算机农业应用联合大会

作者： Zhao Ruijiao 1 , Li Minzan 2 1 Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China. 2 Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China.

An acquiring platform of near-ground remote sensing images is developed to collect visible image and NIR image synchronously and then get the reflectance information form crop images. The platform contains: a 2-CCD multi-spectral camera, two collecting boxes, a field computer with two gigabit net interfaces and an image processing system. First, a true color image of field crops is processed with 2G-R-B gray and Median Filtering Algorithm, and OTSU is used to separate plants from ground. Then the binary image is returned back to original R gray image and the average gray value of R image is acquired. Finally, using linear module between reflectance and gray value the reflectance of crop in red waveband can be caculated. Test results show that the acquiring platform works well and there exists remarkable correlation between results by above image processing method and that of ASD spectrometer, and it provides theoretical basis for crop status monitoring with digital image processing.

关键词： multi-spectral camera, near-ground remote sensing, image segment, reflectance extraction

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Design and development of Detection and Analysis System for Wheat Stripe Rust Resistance Genes

Design and Development of Detection and Analysis System for ...

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亚洲精细农业与计算机农业应用联合大会

作者： Song Qiang 1 , Wang Lianzhi 1 , Xu Shichang 2 1College of Information and Electrical Engineering, China Agricultural University, Beijing, China 2Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China

To improve the efficiency and veracity of the detection and analysis of the wheat stripe rust resistance genes, the detection and analysis system for wheat stripe rust resistance genes (SRGDAS) was designed and developed, through introducing the experience and knowledge of the experts in the agricultural domain into computer. This system is based on the MVC (Model-View-Controller) design pattern, and combined with the component and framework design thought and technology. Taking the detection method and actual analysis process adopted by domain experts into full consideration, developed the knowledge base, the knowledge acquisition facility, the inference engine, the explanation facility, as well as the friendly man-machine interface. This system is principally used to derive the stripe rust resistance genes from the wheat cultivars according to the phenotypes of the tested wheat cultivars infected by Puccinia striiformis. Additionally, it can analyze the existence credibility of the derived known genes in terms of the all-around information of the wheat cultivars. Adopting the clustering method, it can also process the derived unknown genes according to the wheat cultivars resistance characteristics. This system is applied to practice and validated by the detection and analysis experimental data, which verifies the feasibility and validity of this system.

关键词： wheat stripe (yellow) rust, resistance gene, gene postulation, MVC pattern

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An Ontology for Insect Identification Expert System

An Ontology for Insect Identification Expert System

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亚洲精细农业与计算机农业应用联合大会

作者： WU Maifang 1 , ZHAO Huiyan 2 1. College of Information Engineering, Northwest A&F University, China 2. College of Plant Protection, Northwest A&F University, China

Researches on insect identification expert system have been more and more and made headway. Whereas, because of the complexity, dynamic and fuzziness of insect management, knowledge base and database are not complete and dynamic in most expert system, so, these systems possibly just provide some readily interprets and judgments, but not exact solvent. An ontology defines the terms used to describe and represent an area of knowledge. Ontologies include computer-usable definit ions of basic concepts in the domain and the relationships among them. As a result, ontologies are widely used for its specification, reliability and reusability. Knowledge in ontologies based System could not only be classified, but also be organized and associated. Then, Inference engine could reason using the knowledge to satisfy *** this paper, an ontology for insect is developed. After identify ing the purpose and the scope of the expert system, by analy zing the do main of insects, we use ins ect morphology and taxonomy as foundation, and Integrate existing ontologies, and then combine wide ranges of approaches to develop insect ontology. Protégé3.1 is used for ontology development of concepts and relationships that represent insect morphology and *** is ontology will be used in insect identification expert system, wh ich can help to indentify the natural enemy of aphid in various crops, and provide management strategies fro m which eco logy and environ ment benefit, and accordingly protect the environment as well as economic benefits.

关键词： Expert System, Ontology, konwledge engineering, OW L, insect morphology and taxono my

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Eggs Fresh Degree Detection Based on VFW and AIN

Eggs Fresh Degree Detection Based on VFW and AIN

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亚洲精细农业与计算机农业应用联合大会

作者： ZHU Zhihui, WEN Youxian Huazhong Agricultural University, China

Eggs are an important part of daily life nutritious foods of animal origin, but they are easily perishable. With development of the computer image processing technology, non-destructive detection of egg quality based on machine vision have a good future. But real-time machine vision system is generally composed of expensive hardware, which limits its application. The paper proposed that collected egg image by VFW(video for windows)and identified egg fresh degree by artificial immune network(AIN). VFW increased video capture flexibility, reduced dependence on the video equipment, reduced costs. Artificial immune network is a new intelligent method simulating biological immune system, which has strong information processing ability. It is a complex system with self-adaption, self-learning, self-organization, parallel and balanced distribution. It aims at using ideas gleaned from immunology to develop systems that will be capable of performing a wide range of tasks in various research areas such as noise tolerance, self-learning, self-organization and memory, thus providing new ideas and methods for egg fresh degree identification. In the paper, the pixel area ratio of Egg yolk to the whole egg, the ratio of air room height to major axis length and egg folk color information (H, I, S) were selected as characteristic parameters. The characteristic parameters were trained by artificial immune network to obtain memory antibody set. The memory antibody set identified new samples by use of K-Nearest Neighbor(KNN) method. The test shows the use of VFW can reduce costs, the correct identifying rate of white shell egg and brown shell egg fresh degree is 93.45%, 92.05% respectively. In order to verify the effectiveness of the artificial immune network algorithm, The paper used BP network and support vector machine to identify same samples. The results show, compared with BP network and support vector network, artificial immune network has higher precision,smaller samples and st

关键词： Egg, Fresh degree, Detection, VFW, Artificial Immune Network

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RECOGNITION OF THE TEA SPROUT BASED ON COLOR AND SHAPE FEATURES

RECOGNITION OF THE TEA SPROUT BASED ON COLOR AND SHAPE FEATU...

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亚洲精细农业与计算机农业应用联合大会

作者： Fuzeng Yang 1,3 , Liangliang Yang 1 , Yanna Tian 2 , Qing Yang 11 College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi,712100, China 2 College of Information Engineering, Northwest A&F University, Yangling, Shaanxi,712100, China 3 College of computer Science and Engineering, Northwestern Polytechnical University, Xi’an Shanxi 710072, China

There are not enough workforces in China in picking tea sprout today, which usually result in missing the optimum picking period of tea sprout. The picking machine currently used improves the picking efficiency indeed. However, the old leaves are picked together with the sprout, more seriously the sprout is damaged at the same time. So, it is in great need of an intelligent picking machine that can recognize and pick the sprout with the minimum sprout damage. This paper presents an image process method based on the tea sprout color and shape features, which was used to recognize the "Wuzi Xianhao" (A Famous Green Tea of Shaanxi, China) tea sprout grown at Xixiang county of Shaanxi province around the Pure Brightness (5th solar term). Firstly, the green component of the tea leaf image in RGB color space was extracted. Secondly, green component image was segmented using double threshold method. Lastly, the edge of tea sprout is detected according to its shape feature. The experimental results illustrate that this recognizing method of the tea sprout based on color and shape features can recognize the tea sprout and the right detection rate is 94%, which provides a effective method for automatic tea sprout picking.

关键词： Tea sprout, Recognition, Color feature, Shape feature

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