Near Real-Time Agricultural Simulations on the Web
Identifieur interne : 000505 ( Istex/Corpus ); précédent : 000504; suivant : 000506Near Real-Time Agricultural Simulations on the Web
Auteurs : Goshko A. Georgiev ; Gerrit HoogenboomSource :
- Simulation [ 0037-5497 ] ; 1999-07.
Abstract
Easy access to the Internet allows farmers to search for site-specific information and applications. The agricultural scientific community has developed computer simulation models and decision support systems during the last 20 years in order to transfer scientific knowledge to farmers. We describe an at tempt to create an Interrzet-based decision support system for delivering weather data and executing near real-time weather applications and crop simu lation models on the Web. A user accesses an easy- to-use interface to select management scenarios and run crop simulation models remotely. The weather data inputs are linked to data collected by the Geor gia Automated Environmental Monitoring Net work. A user defines a scenario by selecting a crop, cultivar, planting date, plant density and spacing, irrigation schedules and fertilizer inputs. After de fining all inputs associated with the scenario, the simulation model runs remotely on the server. The proposed distributed processes scheme can be imple mented on different platforms. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust and simplified access to crop simulation models for the user community.
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DOI: 10.1177/003754979907300104
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ISTEX:9D911AE705F7BD80646C02209BAEF37876CDEEB2Le document en format XML
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Georgiev</name><affiliation><mods:affiliation>Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA</mods:affiliation></affiliation></author><author wicri:is="90%"><name sortKey="Hoogenboom, Gerrit" sort="Hoogenboom, Gerrit" uniqKey="Hoogenboom G" first="Gerrit" last="Hoogenboom">Gerrit Hoogenboom</name><affiliation><mods:affiliation>Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:9D911AE705F7BD80646C02209BAEF37876CDEEB2</idno><date when="1999" year="1999">1999</date><idno type="doi">10.1177/003754979907300104</idno><idno type="url">https://api.istex.fr/document/9D911AE705F7BD80646C02209BAEF37876CDEEB2/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000505</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000505</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Near Real-Time Agricultural Simulations on the Web</title><author wicri:is="90%"><name sortKey="Georgiev, Goshko A" sort="Georgiev, Goshko A" uniqKey="Georgiev G" first="Goshko A." last="Georgiev">Goshko A. 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The agricultural scientific community has developed computer simulation models and decision support systems during the last 20 years in order to transfer scientific knowledge to farmers. We describe an at tempt to create an Interrzet-based decision support system for delivering weather data and executing near real-time weather applications and crop simu lation models on the Web. A user accesses an easy- to-use interface to select management scenarios and run crop simulation models remotely. The weather data inputs are linked to data collected by the Geor gia Automated Environmental Monitoring Net work. A user defines a scenario by selecting a crop, cultivar, planting date, plant density and spacing, irrigation schedules and fertilizer inputs. After de fining all inputs associated with the scenario, the simulation model runs remotely on the server. The proposed distributed processes scheme can be imple mented on different platforms. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust and simplified access to crop simulation models for the user community.</div></front></TEI><istex><corpusName>sage</corpusName><author><json:item><name>Goshko A. 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The agricultural scientific community has developed computer simulation models and decision support systems during the last 20 years in order to transfer scientific knowledge to farmers. We describe an at tempt to create an Interrzet-based decision support system for delivering weather data and executing near real-time weather applications and crop simu lation models on the Web. A user accesses an easy- to-use interface to select management scenarios and run crop simulation models remotely. The weather data inputs are linked to data collected by the Geor gia Automated Environmental Monitoring Net work. A user defines a scenario by selecting a crop, cultivar, planting date, plant density and spacing, irrigation schedules and fertilizer inputs. After de fining all inputs associated with the scenario, the simulation model runs remotely on the server. The proposed distributed processes scheme can be imple mented on different platforms. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust and simplified access to crop simulation models for the user community.</p></abstract><textClass><keywords scheme="keyword"><list><head>keywords</head><item><term>World Wide Web</term></item><item><term>Internet</term></item><item><term>agricul ture</term></item><item><term>weather</term></item><item><term>crop model</term></item><item><term>decision support system</term></item><item><term>Web-based simulation</term></item><item><term>farming</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1999-07">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/9D911AE705F7BD80646C02209BAEF37876CDEEB2/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="corpus sage not found" wicri:toSee="no header"><istex:xmlDeclaration>version="1.0" encoding="UTF-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//NLM//DTD Journal Publishing DTD v2.3 20070202//EN" URI="journalpublishing.dtd" name="istex:docType"></istex:docType><istex:document><article article-type="other" dtd-version="2.3" xml:lang="EN"><front><journal-meta><journal-id journal-id-type="hwp">spsim</journal-id><journal-id journal-id-type="publisher-id">SIM</journal-id><journal-title>Simulation</journal-title><issn pub-type="ppub">0037-5497</issn><publisher><publisher-name>Sage Publications</publisher-name><publisher-loc>Sage CA: Thousand Oaks, CA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.1177/003754979907300104</article-id><article-id pub-id-type="publisher-id">10.1177_003754979907300104</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group></article-categories><title-group><article-title>Near Real-Time Agricultural Simulations on the Web</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Georgiev</surname><given-names>Goshko A.</given-names></name><aff>Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA</aff></contrib></contrib-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hoogenboom</surname><given-names>Gerrit</given-names></name><aff>Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA</aff></contrib></contrib-group><pub-date pub-type="ppub"><month>07</month><year>1999</year></pub-date><volume>73</volume><issue>1</issue><fpage>22</fpage><lpage>28</lpage><abstract><p><italic>Easy access to the Internet allows farmers to search for site-specific information and applications. The agricultural scientific community has developed computer simulation models and decision support systems during the last 20 years in order to transfer scientific knowledge to farmers. We describe an at tempt to create an Interrzet-based decision support system for delivering weather data and executing near real-time weather applications and crop simu lation models on the Web. A user accesses an easy- to-use interface to select management scenarios and run crop simulation models remotely. The weather data inputs are linked to data collected by the Geor gia Automated Environmental Monitoring Net work. A user defines a scenario by selecting a crop, cultivar, planting date, plant density and spacing, irrigation schedules and fertilizer inputs. After de fining all inputs associated with the scenario, the simulation model runs remotely on the server. The proposed distributed processes scheme can be imple mented on different platforms. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust and simplified access to crop simulation models for the user community.</italic></p></abstract><kwd-group><kwd>World Wide Web</kwd><kwd>Internet</kwd><kwd>agricul ture</kwd><kwd>weather</kwd><kwd>crop model</kwd><kwd>decision support system</kwd><kwd>Web-based simulation</kwd><kwd>farming</kwd></kwd-group><custom-meta-wrap><custom-meta xlink:type="simple"><meta-name>sagemeta-type</meta-name><meta-value>Other</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>search-text</meta-name><meta-value>22 Technical ArticleNear Real-Time Agricultural Simulations on the Web SAGE Publications, Inc.1999DOI: 10.1177/003754979907300104 Goshko A. Georgiev Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA Gerrit Hoogenboom Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA Easy access to the Internet allows farmers to search for site-specific information and applications. The agricultural scientific community has developed computer simulation models and decision support systems during the last 20 years in order to transfer scientific knowledge to farmers. We describe an at tempt to create an Interrzet-based decision support system for delivering weather data and executing near real-time weather applications and crop simu lation models on the Web. A user accesses an easy- to-use interface to select management scenarios and run crop simulation models remotely. The weather data inputs are linked to data collected by the Geor gia Automated Environmental Monitoring Net work. A user defines a scenario by selecting a crop, cultivar, planting date, plant density and spacing, irrigation schedules and fertilizer inputs. After de fining all inputs associated with the scenario, the simulation model runs remotely on the server. The proposed distributed processes scheme can be imple mented on different platforms. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust and simplified access to crop simulation models for the user community. World Wide Web Internet agricul ture weather crop model decision support system Web-based simulation farming 1. Introduction The rapid expansion of the Internet has provided opportunities for many different applications. Easy access to the Internet allows farmers to search for site-specific information and applications, which can help them in making informed decisions. The agricultural scientific community has developed computer simulation models and decision support systems during the last 20 years. The main objective of these computer-based tools is to provide an effective means to transfer scientific knowledge to the farmers and to help support their decision-making. Recent advances in communication technologies and Internet access have opened new opportunities, as well as challenges, to make this information available. In this paper, we describe an attempt to create an Internet-based decision support system for delivering weather data and executing near real-time weather applications and crop simulation models on the Web (http://www.griffin.peachnet. edu/ bae). Using Internet technology, a user can be provided with an easy-to-use interface through which he can select one or more management scenarios and run crop simulation models, remotely. The weather data inputs are linked to the weather data collected by the Georgia Automated Environmental Monitoring Network (AEMN). A user can select more than 35 different locations where the weather stations of the AEMN are operational. After site selection, a user can define a particular management scenario by selecting a crop, 2523 cultivar, planting date, plant density and spacing, irrigation schedules and fertilizer inputs. After defining all inputs associated with a particular management scenario, the simulation model runs remotely on the server. The proposed distributed processes scheme can be implemented, using different hardware and software platforms. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust, and simplified access to crop simulation models and help their implementation to the user community. The increasing demand from different customers for near real-time weather information and weather- based applications has led to the development of World Wide Web sites for delivery of weather data [12]. The interface of these systems should be intuitive to use. The individual pages of these Websites should be dynamically updated with near real-time weather information on a continuous basis. In addition, the Website should provide an interface between weather data and different applications, so that the user can have the capability to run custom queries on the server, which are calculated dynamically and delivered immediately. The Web-based simulation session held during the 1996 Winter Simulation Conference was the best attended session within the modeling methodology track of the conference [17]. Fishwick [5] offers a perspective on the issue of Web-based simulation. He identifies many potential impacts of Web-based simulation technologies, with emphasis on education and training, publication and simulation programs. In January 1998, the first conference dedicated to the topic of Web-based simulation (WEBSIM'98) was held, as part of the annual Society for Computer Simulation Western MultiConference [6]. During this conference, Page [17] presented a literature review on Web-based simulation. He suggested five areas of focus: (1) simulation as hypermedia, (2) simulation research methodologies, (3) Web-based access to simulation programs, (4) distributed modeling and simulation, and (5) simulation of the World Wide Web. The backbone of any decision support system is some type of simulation model which is able, based on input data, to estimate important output parameters. Many simulation models have been developed for use in agricultural research [23, 26]. However, they are coded using high-level programming languages, such as C++, FORTRAN, and Pascal. Most of these programs are not able to run directly on the Web. Since the Internet is playing a very important role in the fields of computer and communication technologies, a growing number of attempts have been made to develop user-friendly interfaces between these models and Web browsers, so that simulation results can be available for on-line use. Pan et al. [19] developed a special object-oriented model to simulate plant growth, using the Java programming language. The same technology was used to bring the Environmental Policy Integrated Climate (EPIC) model [25] on-line and make it available to the research community. Other systems include P1@ntelInfo, a Danish information system for crop production [15], the water quality model GLEAMS [ 16] and the cotton model GOSSYM-COMAX [1]. Many attempts have been made to enable Web-based computer-aided design (CAD) applications [9, 10, 21]. Others have tried to make access to on-line data and applications more flexible, complete and accurate [2, 3, 7, 8, 13, 14, 18, 22]. The objective of this paper is to present the development of a user-friendly interface for the delivery of weather data, and for the execution of near real-time weather applications and crop simulation models, using Internet technology. 2. System Components There are three major components in the system presented here. The principal flow of information is presented in Figure 1. The first component is the weather data collection part, called the Georgia Automated Environmental Monitoring Network (AEMN) [11]. The AEMN currently consists of 37 weather stations; it is continuously expanding, with additional stations planned for the future. Each station monitors air temperature, relative humidity, rainfall, solar radiation, wind speed, wind direction, and soil temperatures at 5-, 10- and 20-centimeter depths. Each sensor is scanned at a one-second frequency; all data are summarized every 15 minutes, and at midnight a daily summary is calculated. A microcomputer at the Georgia Experiment Station in Griffin, Georgia, initiates telephone calls to all stations periodically and downloads the recorded data. Data are automatically processed and saved in detailed and daily data files. The weather information is transferred to databases as 15- minute averages or totals, and the databases are updated continuously. The weather computer has an Figure 1. Basic system components and flow of data and information 2624 NFS connection to the weather database server, where data are updated at 15-minute intervals also. At midnight, daily weather summaries are prepared, including daily maximum, minimum, averages and totals. The weather database server transfers summary weather data directories to the World Wide Web server, using FTP protocol. This process provides users immediate access to all basic weather parameters. The second component of the system is the weather database and application server. This is the main system for weather data storage, as well as all weather- based applications. The weather data, as well as executable scripts, are stored on this server. This provides the following capabilities: data and applications are independent of the weather collection system, as well as independent from the World Wide Web server. It also provides an independent development environment without influencing either the basic data collection or data serving tasks. It, thereby, decreases demand for resources of the server. With respect to security, the end-user does not have direct access to either the data or the application sources. Finally, the weather data and applications are also separated from other server tasks and pages. 3. Computer i ecnnoiogy 3.1 Software Basic applications scripts were developed using the PERL language (Version 5.004), the Common Gateway Interface (CGI) Object Library (Version 2.36), and GD Graphics Object Library (Version 1.18). These are freely distributed shareware packages with free licenses. The latest versions of the software can be found at: . http://language.perl.com/CPAN/src/latest.tar.gz for PERL . http://stein.cshl.org/WWW/software/CGI for CGI . http://www.genome.wi.mit.edu/ftp/pub/software/ WWW/GD.html for GD Object Library. Other programs were written using the Bourne shell command interpretator. The simulation models were developed in the FORTRAN programming language and compiled under the UNIX environment. 3.2 Hardware The weather computer is a Pentium 120 MHz microcomputer, running an OS/2 multi-tasking operating system (Version 3). The database and application server is a SUN Ultra 2 Creator workstation with two Super- Sparc processors, running the Solaris Version 2.5.1 operating system. The World Wide Web server is a SUN Ultra Enterprise server model 150, running the Solaris Version 2.6 operating system. The Web server software is Apache freeware Web Server Version 1.3, supporting gateway interface version CGI / 1.1 and HTTP / 1.0 server protocol. 4. Applications The main AEMN World Wide Web data and application screen is shown in Figure 2. The screen is presented Figure 2. Data and application screen 2725 Table 1. Four-day weather summary report for the Georgia Experiment Station, Griffin, Georgia after the user has selected a site from a clickable image map, within the base page of the AEMN home page (http://www.griffin.peachnet.edu/bae). The applications can be separated into two components-data queries and application tasks. With data queries, the user can request current weather conditions; yesterday's conditions as a summary for the last four days; and a summary of the last thirty days for the main weather variables. To save access time and computer resources, all data are stored in different data files. Scripts are being run to only display to the screen the data that have been requested by the user. The user is able to retrieve basic weather elements for a specific period of time. He can also request a report for climate averages, in which data from the nearest weather station for the selected site are displayed. In Table 1, an example of the four-day summary report is presented. For the historical climate data, only basic weather parameters, such as maximum and minimum temperatures, and precipitation, are available [4]. Data application utilities and calculators were developed in a similar manner to present a consistent user interface. The applications have a simplified interface, which allows the user to create simple queries and retrieve specific data, to which mathematical processing and calculations are applied. The degree-day calculator allows a user to choose between different base temperatures, as well as to take into account extreme high temperatures, which have a depressing effect on crop and pest development. The degree-day calculator and the chilling-hours calculator use the 15-minute average weather data files. They, therefore, have a high demand for CPU time because of processing detailed data files. The other calculators use the daily summary data files and are not resource- intensive. The water-balance calculator uses two processes for calculations. It is based on the Priestley- Taylor formula [20] for calculating total potential eva- potranspiration and a separate calculator for integrating total precipitation. The degree-day calculator was modified for application in technical climatology and the air conditioning and heating industry to calculate so-called heating and cooling days. These are variables that show heating or cooling requirements during the winter and summer times, respectively. For all calculators, the user can compare results for the current year with the same time period for the previous three years. A flowchart of the calculators and a sample output screen of the degree-day calculator query results table are presented in Figure 3. 5. Crop Simulation Model Computer simulation can be an effective tool for simulating growth and development of a particular crop as a function of environmental conditions and management scenarios. More than 100 crop models have been developed during the past 20 years. An extensive database of different crop simulation models can be found at the Internet address http://dino.wiz.uni- kassel.de/modeCdb/server.html. Unfortunately, most of the available models were not developed to facilitate Figure 3. A flowchart for the weather application calculators and a sample output screen for the degree-day calculator 2826 the comparison of model outputs and experimental data. Many efforts have been made to standardize data for model inputs and outputs. The Decision Support System for Agrotechnology Transfer (DSSAT) [24] defined standard input and output data formats, as well as identifying a minimum data set needed for these models to operate. Currently 17 models are available. The most important ones include models for maize, wheat, barley, sorghum, millet, rice, soybean, peanut, dry bean, and tomato. All crop models share a common input-output format, and operate on a daily time step. They have a similar level of physiological detail and are based on an understanding of the biological processes. The DSSAT software consists of a set of computer programs that run on a personal computer. The programs are accessible under a shell designed to enter, store and manipulate weather, soil and crop data; run crop simulation models; and analyze crop model outputs. The contemporary, process-oriented crop simulation models include tens of thousands of lines of code and require a large amount of computer resources. Fortunately, current advances in computer technology have made the need for these resources less important. However, the question of which operating system to use and how to provide model updates still remains. There is a certain need for skills and computer literacy to be able to run models and to understand their outputs. This is one of the main reasons that the models and decision support systems remain at the research level and are not very popular as a decision support tool to estimate crop growth scenarios. Furthermore, to run a simulation model the user needs to collect data from different sources and convert them to the format models can use, which can be time consuming and tedious. 6. Results and Discussion Using the latest Internet programming technology, it is possible to provide users with the capability to run these crop simulation models remotely. Different examples of on-line models, such as EPIC and Nitrogen Crop Response Model, can be found at ~p://sr~.~~~. edu/humus/epic.html and http://www.qpais.co.uk/nable/ nitrogen.html, respectively. Our Web application is an attempt to simplify the entries needed to run the models so that the user has access to the latest state-of-the- art simulation technology. There is also a cost benefit, saving resources and time to install and maintain computer software and continuously update models, and to provide immediate access to the latest version of the model. Linking the models with current weather data, collected through the AEMN, also allows the user to have site-specific estimations in near real time. In Figure 4, the flowchart of the crop model user interface is presented. Inputs are separated in different screens, and the current selections are presented cumulatively on each subsequent screen. At every step, the user can return back and change selections which have been made previously. He can select the crop he is interested in, and choose a soil profile typical for his farm or region. Because of the high spatial soil variability and difficulties in collecting reliable soil information, only generic soil profiles are currently available. With an extensive development of a soil database, it is possible to connect the current soil database to an external spatially distributed soil database, which can be used for model estimations for the specific region. Weather data from the current year are automatically extracted from the weather database, as well as data for the last 30-year period from the nearest site with weather observations. These current and historical weather data Figure 4. Organizational flowchart for the simulation processes 2927 Table 2. A summary table for soybean simulation results; maturity group 5 cultivar, planted in Griffin, Georgia are used as input to conduct the simulations. A user can select basic management parameters, such as cultivar, planting date, plant density, row spacing and planting depth. In future versions additional selections will be added for different planting methods and other management scenarios. Irrigation strategies can be built using different input options. The amount of data needed is kept as small as possible to insure an easy-to-use interface, to avoid complex screens, and to minimize the number of screens. Up to 10 different irriga- tions are allowed. The user can select the irrigation amount, the irrigation method, and irrigation efficiency. In Figure 4 the standard fertilizer application options are also presented. Time can be presented in two ways, as days after planting, and as month and day of the year. Currently, the user is able to select only a few inputs-real management data and events, as well as data to plan different management scenarios until the end of the growing season. The system can simulate tactical scenarios for "what- if" type of options very well. Queries that can be conducted include, "What if I apply additional fertilizer this week?" or, "What if I skip an irrigation event this week?" After entering all the required information, the next step is to start the simulation model. Intermediate computer input files are created, as well as other data files required to run the simulation. Depending on the input options selected and system load, the approximate server response time is about 20 seconds. During this delay the current-year simulations are run, as well as simulations using 30 years of historical data, assuming no change in management. In total, 60 different simulations are conducted for one management scenario. Results are presented in two ways: in a table to dis- play a summary of the results (Table 2), and in time- series graphs to display plant growth and rainfall during the growing season (Figures 5 and 6). For both cases, the simulation for the current year is compared to the average, worst and best cases for the last 30 years. Basic information such as expected yield and above- ground biomass, as well as important phenological stages, is presented. This information can be used for planning purposes. As an example, a user can plan additional irrigation activities during the most impor- tant periods of plant development or can plan for equipment availability at expected maturity dates. 7. Conclusion Current advances in computer technology and communications have made it possible to publish and provide sophisticated modeling methods and applications to more users. Using Internet technology, a user can be provided with an easy-to-use interface through which he can select one or more management scenarios and run crop simulation models remotely. The proposed distributed processes scheme allows for the Figure 5. Output graph for crop growth and development Figure 6. Output graph for cumulative rainfall and water stress 3028 separation of the current tasks on different computers, while at the same time combining the output into one product. This results in a seamless system for the user; different platforms can be used for implementing this scheme. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust, and simplified access to crop simulation models and help their implementation to the user community. As an indicator for the growing user interest in Web technology, we can use as an example the number of requests received by our Web server. Since our Web service became active in 1998, the number of hits has increased exponentially from a few thousand per month initially to more than 20,000 during the month of February 1999. 8. References Bauske, E.M. , Harker, K.S., Simpson, E.H., Getz, R.R. "Application of Weather Information for Cotton Production in the Southeast ." Proceedings Beltwide Cotton Conferences, Vol. 1, pp 398-400, Nashville, TN, 1996. Boesen, B.D. , Bojer, O.Q., Secher, B.J., Murali, N.S., Secher, J.M., Frahm, J. "A Computer-based Decision Support System for Selection of Varieties ." Proceedings of the Workshop on Decision Systems in Crop Protection, SP Rapport Statens Planteavlsforsog , No. 15, pp 19-34, 1996. Conte, E. "Database on Pesticides Accessed Through the Internet. Successful Applications of Information and Communication Technologies in Plant Protection." Proceedins of the 1st Workshop of the European Network for Information Technology in Agriculture, Supplement 1, pp 155-162, Rome, Italy, 1997. Earth Info, Database Guide for EarthInfo CD NCDC Summary of the Day. EarthInfo, Inc ., Boulder, CO, 1997. Fishwick, P.A. "Web-based Simulation: Some Personal Observations ." Proceedings of the 1996 Winter Simulation Conference , pp 772-779, 1996. Fishwick, P.A., Hill, D.R.C., Smith, R. (eds). Proceedings of the International Conference on Web-Based Modeling and Simulation, SCS Simulation Series, No. 30(1), 1998. Getz, R.R., Harker, K.S., Ihle, D.M., Adams, S.D., Simpson III, E.H. "Regional Delivery of Agricultural Weather Information Using the Internet ." Proceedings of 5th International Conference "Computers in Agriculture," ASAE, pp 712-717, 1994. Hale, S.A., Blanchard, S.M., Abrams Jr., C.F., Walker, J.C. "World Wide Web Applications in Biological and Agricultural Engineering at North Carolina State University." ASAE Paper #943531, 1994 . Hauck, S., Knol, S. "Data Security for Web-based CAD." Proceedings of the 35th Design Automation Conference, San Francisco, pp 788-793, 1998. Hensen, J.L.M. , Janak, M., Kaloyanov , N.G., Rutten, P.S.G. "Introduction to Building Energy Simulation Classes on the Web." ASHRAE Transactions, Vol. 104, Pt 1A, pp 488-493,1998. Hoogenboom, G. "The Georgia Automated Environmental Monitoring Network." Preprints 22nd Conference on Agricultural and Forest Meteorology with Symposium on Fire and Forest Meteorology, pp 343-346, AMS, Boston, 1996. Hoogenboom G. , Georgiev, G., Clarke , B., Gresham, D.D., Harbers, G. "Internet Tools for Delivery of Weather Data and Applications." 23rd Conference on Agricultural and Forest Meteorology, AMS, pp 251-253, Boston , 1998. Huang, P.G., Jacob, J.D. "On the Development of an Intelligent Code Validation System for Rapid Transfer of Turbulence Model Technology." FEDSM98-5100, ASME, Fairfield, NJ, 1998. Jamerson R. "Enterprise Demands Real-time Plant-floor Data." InTech, Vol. 45, No. 7, pp 38-40, 1998. Jensen, A.L. , Thysen, I., Secher, B.J.M. "Decision Support in Crop Production Via the Internet." Successful Applications of Information and Communication Technologies in Plant Protection, Proceedings of the 1 st Workshop of the European Network for Information Technology in Agriculture , Petria . No 7, Supplement 1, pp 147-154, 1997. Manguerra, H.B. , Engel, B.A. "Java-Based Internet/WWW Front-end for an Integrated Hydrologic and Pesticide Risk Analysis Model." ASAE Paper #972053, St. Joseph, MI, 1997. Page, E. "The Rise of Web-based Simulation: Implications for the High Level Architecture." Proceedings of the 1998 Winter Simulation Conference, Vol. 2, pp 1663-1668, 1998 . Pan, X., Hesketh, J.D., Huck, M.G. "A Web Interface to Databases Associated with a Plant Growth Simulator ." Computers and Electronics in Agriculture, Vol. 21, pp 207-217, 1998. Pan, X., Hesketh, J.D., Huck, M.G. "An Object-oriented and Internet Based Simulation Model for Plant Growth ." Proceedings of Seventh International Conference on Computers in Agriculture, Orlando, FL, pp 345-351, 1998. Priestley, C.H.B., Taylor, R.J. "On Assessment of Surface Heat Flux and Evaporation Using Large Scale Parameters." Monthly Weather Review, Vol. 100, pp 81-92, 1972. Regnier, J., Wilamowski, B. "SPICE Simulation and Analysis Through Internet and Intranet Networks." IEE Circuits and Device Magazine, Vol. 14, No. 3, pp 9-12, 1998. Ten Eyck, J. , Sampath, G. "Object Model for Problem Solving and Its Application." Conference Proceedings, IEEE SOUTH-EASTCON 1998 , pp 57-60, 1998. Tsuji, G.Y., Hoogenboom, G., Thornton, P.K. (eds). Understanding Options for Agricultural Production. Kluwer Academic Publishers, Dordrecht, The Netherlands, 1998. Tsuji, G.Y., Uehara, G., Balas, S. (eds). DSSAT v3. University of Hawaii, Honolulu, HI, 1994. Wang, H., Collapalli, J., Srinivasan, R. "Hydrologic Modelling on the WWW: EPIC On-line." ASAE Paper #983146, 1998. Whisler, F.D., Acock, B., Baker , D.H., Fye, R.E., Hodges, H.F., Lambert, J.R., Lemmon, H.E., McKinion, J.M., Reddy, V.R. "Crop Simulation Models in Agronomic Systems ." Advances in Agronomy, Vol. 40, pp 141-208, 1986. Goshko Georgiev is a Post-Doctoral Research Associate in the Department of Biological and Agricultural Engineering, the University of Georgia. He received his MSc from Odessa Institute of Hydrology and Meteorology in the Ukraine and his PhD from Hydro-Meteorological Research Center of Russia. Prior to joining the University, he was a Research Associate at the National Institute of Meteorology and Hydrology, Bulgaria. He is work- ing on developing crop simulation model applications, interface between them and GIS, near-real-time data assimilation, and decision support utilities. His research interest includes developing and advancing data processing, system analysis, decision support tools and computer applications to study the impact of environmental conditions on natural resources. Gerrit Hoogenboom is currently an Associate Professor in the Department of Biological and Agricultural Engineering, the University of Georgia. He received his BSc and MSc from Wageningen Agricultural University in The Netherlands and his PhD from Auburn University. Prior to joining the University of Georgia, he worked as a Post-Doctoral Research Associate at the University of Florida. During the last few years he has coordinated the development of the Decision Support System for Agrotechnology Transfer, which includes a suite of crop simulation models, data utilities and application programs. His research interests include developing and advancing computer models to study the impact of environmental conditions on agricultural production, food security and economic sustainability.</meta-value></custom-meta></custom-meta-wrap></article-meta></front><back><ref-list><ref><citation citation-type="confproc" xlink:type="simple"><name name-style="western"><surname>Bauske, E.M.</surname></name> , <name name-style="western"><surname>Harker, K.S.</surname></name>, <name name-style="western"><surname>Simpson, E.H.</surname></name>, <name name-style="western"><surname>Getz, R.R.</surname></name> "<article-title>Application of Weather Information for Cotton Production in the Southeast</article-title> ." <conf-name>Proceedings Beltwide Cotton Conferences</conf-name>, Vol. 1, pp 398-400, <conf-loc>Nashville, TN</conf-loc>, <conf-date>1996</conf-date>.</citation></ref><ref><citation citation-type="confproc" xlink:type="simple"><name name-style="western"><surname>Boesen, B.D.</surname></name> , <name name-style="western"><surname>Bojer, O.Q.</surname></name>, <name name-style="western"><surname>Secher, B.J.</surname></name>, <name name-style="western"><surname>Murali, N.S.</surname></name>, <name name-style="western"><surname>Secher, J.M.</surname></name>, <name name-style="western"><surname>Frahm, J.</surname></name> "<article-title>A Computer-based Decision Support System for Selection of Varieties</article-title> ." <conf-name>Proceedings of the Workshop on Decision Systems in Crop Protection, SP Rapport Statens Planteavlsforsog</conf-name> , No. 15, pp 19-34, <conf-date>1996</conf-date>.</citation></ref><ref><citation citation-type="confproc" xlink:type="simple"><name name-style="western"><surname>Conte, E.</surname></name> "<article-title>Database on Pesticides Accessed Through the Internet. 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ASAE Paper #983146, <year>1998</year>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Whisler, F.D.</surname></name>, <name name-style="western"><surname>Acock, B.</surname></name>, <name name-style="western"><surname>Baker , D.H.</surname></name>, <name name-style="western"><surname>Fye, R.E.</surname></name>, <name name-style="western"><surname>Hodges, H.F.</surname></name>, <name name-style="western"><surname>Lambert, J.R.</surname></name>, <name name-style="western"><surname>Lemmon, H.E.</surname></name>, <name name-style="western"><surname>McKinion, J.M.</surname></name>, <name name-style="western"><surname>Reddy, V.R.</surname></name> "<article-title>Crop Simulation Models in Agronomic Systems</article-title> ." <source>Advances in Agronomy</source>, Vol. <volume>40</volume>, pp <fpage>141</fpage>-<lpage>208</lpage>, <year>1986</year>. </citation></ref></ref-list></back></article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Near Real-Time Agricultural Simulations on the Web</title></titleInfo><titleInfo type="alternative" lang="en" contentType="CDATA"><title>Near Real-Time Agricultural Simulations on the Web</title></titleInfo><name type="personal"><namePart type="given">Goshko A.</namePart><namePart type="family">Georgiev</namePart><affiliation>Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA</affiliation></name><name type="personal"><namePart type="given">Gerrit</namePart><namePart type="family">Hoogenboom</namePart><affiliation>Department of Biological and Agricultural Engineering The University of Georgia Griffin, Georgia, USA</affiliation></name><typeOfResource>text</typeOfResource><genre type="other" displayLabel="other"></genre><originInfo><publisher>Sage Publications</publisher><place><placeTerm type="text">Sage CA: Thousand Oaks, CA</placeTerm></place><dateIssued encoding="w3cdtf">1999-07</dateIssued><copyrightDate encoding="w3cdtf">1999</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Easy access to the Internet allows farmers to search for site-specific information and applications. The agricultural scientific community has developed computer simulation models and decision support systems during the last 20 years in order to transfer scientific knowledge to farmers. We describe an at tempt to create an Interrzet-based decision support system for delivering weather data and executing near real-time weather applications and crop simu lation models on the Web. A user accesses an easy- to-use interface to select management scenarios and run crop simulation models remotely. The weather data inputs are linked to data collected by the Geor gia Automated Environmental Monitoring Net work. A user defines a scenario by selecting a crop, cultivar, planting date, plant density and spacing, irrigation schedules and fertilizer inputs. After de fining all inputs associated with the scenario, the simulation model runs remotely on the server. The proposed distributed processes scheme can be imple mented on different platforms. Client/Server, CGI, Perl and other Internet technologies are providing a cost-effective, robust and simplified access to crop simulation models for the user community.</abstract><subject><genre>keywords</genre><topic>World Wide Web</topic><topic>Internet</topic><topic>agricul ture</topic><topic>weather</topic><topic>crop model</topic><topic>decision support system</topic><topic>Web-based simulation</topic><topic>farming</topic></subject><relatedItem type="host"><titleInfo><title>Simulation</title></titleInfo><genre type="journal">journal</genre><identifier type="ISSN">0037-5497</identifier><identifier type="eISSN"></identifier><identifier type="PublisherID">SIM</identifier><identifier type="PublisherID-hwp">spsim</identifier><part><date>1999</date><detail type="volume"><caption>vol.</caption><number>73</number></detail><detail type="issue"><caption>no.</caption><number>1</number></detail><extent unit="pages"><start>22</start><end>28</end></extent></part></relatedItem><identifier type="istex">9D911AE705F7BD80646C02209BAEF37876CDEEB2</identifier><identifier type="DOI">10.1177/003754979907300104</identifier><identifier type="ArticleID">10.1177_003754979907300104</identifier><recordInfo><recordContentSource>SAGE</recordContentSource></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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|texte= Near Real-Time Agricultural Simulations on the Web
}}
| This area was generated with Dilib version V0.6.28. |  |