請用此 Handle URI 來引用此文件: http://hdl.handle.net/11455/25611
標題: 作物資料庫及適栽作物推薦
Crop Database And Crop Suitability Recommendations
作者: 王鼎鈞
Wang, Ding-Jiun
關鍵字: 作物資料庫
出版社: 土壤環境科學系所
引用: 台南區農業改良場,2013。網址:http://book.tndais.gov.tw/Brochure/tech48.htm,瀏覽日期:[2013/6/10]。 申雍、陳守泓,2006。農業氣象資訊在專家決策系統之應用與發展。作物、環境與生物資訊,3(1):51-63。 行政院農委會農糧署,2006。農產品交易行情站。 網址:http://amis.afa.gov.tw/,瀏覽日期:[2013/6/9] 行政院農業委員會農業試驗所,1999。國家作物種原中心種原目錄之五綜合作物,pp.A1-A4。 吳蕙如,1999。區域性農地作物適栽評估系統建立。國立中興大學,碩士論文。 呂秀英、呂椿棠,2006。作物專家系統的建構與挑戰。作物、環境與生物資訊,3:40-50。 李達源、陳仁炫,2010。蔬菜園土壤肥料管理手冊。悅翔數位印刷有限公司。 林正錺,1994。農地問題與農地資源規劃利用之關係。農委會 83 科技-2.13-企-05。 林正錺、林重光、林毓雯,1990。農地資源資訊系統概述。土壤肥料通訊,28:2-5。 林正錺、林重光、林毓雯,劉蒼棽,1992。土壤污染防治資訊系統建立,第三屆土壤污染防治研討會論文集,國立中興大學土壤環境科學所,pp. 61-75。 林欣華,1996。台灣農地作物適栽性評估之地理資訊系統建立。國立中興大學,碩士論文。 林貞,2006。臺灣農業產銷資訊化之現況。作物、環境與生物資訊,3(1):33-39。 邱垂錫,1983。農業氣象學。大興圖書印製有限公司。 姚銘輝,2005。 農業氣象災害資訊系統之建立。94農科-8.2.1-農-C1(2)。 洪筆峰,1985。農業生產組織之理論與實務。卡來實務有限公司。 范明仁、魏趨開,1995。國家作物種原中心運作流程。作物種原保育技術研習會專刊,pp.97-121。 郭鴻裕、劉滄棽、朱戩良,2003。土壤資料庫建置與土壤保育。國土資訊系統成果展示研討會論文集,pp.297-306。 陳仁芳,2007。森林動態樣區資料庫與管理系統之建立-以楠梓仙溪上游常綠闊葉森林動態樣區為例。靜宜大學,碩士論文。 陳會安,2009。SQL server 2008 資料庫系統 設計與開發實務。學貫行銷股份有限公司,台北市。 黃三益,2004。資料庫的核心理論與實務。臺灣東華,臺北市。 黃友宣,2012。台灣農地價格區位分析。國立中興大學,碩士論文。 黃彥禎,2005。台灣農地適栽作物評估系統比較。國立中興大學,碩士論文。 農業委員會台灣農家要覽增修訂再版策劃委員會,1995。台灣農家要覽農作篇(二)。財團法人豐年社,台北市。 農業試驗所,2013a,土壤資料庫系統擴展與在國土保安應用網站。 網址: http://taiwansoil.tari.gov.tw/Web.Net2008/index_1/main1-1.aspx,瀏覽日期:[2013/6/9]。 農業試驗所,2013b,農業氣象諮詢系統。 網址:http://amis.tari.gov.tw/MapManager/Result/Weather_Result.aspx,瀏覽日期:[2013/6/9]。 廖玉華,2001。土壤與肥料資訊系統之建立。國立中興大學,碩士論文。 魏甫錦,2001。種子影像資料庫之建構與系統分析。國立臺灣大學,碩士論文。 Adams, S. S., Stevension, W. R., Delhotal, P., & Fayet, J. 2008. An expert system for diagnosis of post-harvest potato diseases. EPPO Bulletin 20(2): 341-347. Ahas, R., A. Aasa, A. Roose, U. Mark, and S. Silm. 2008. Evaluating passive mobile positioning data for tourism surveys: an Estonian case study. Tourism Management 29:469-486. Beaudette, D. E., and A.T. O''Geen. 2010. An iPhone application for on-demand access to digital soil survey information. Soil Sci. Soc. Am. J. 74:1682-1684. Bentham, M. J., Zazueta, F. S., & Xin-Jian, N. 1998. Farm Smart 2000: A multi-agent decision support system for crop production. In 7th International conference on computers in agriculture, Orlando, Florida, USA p.469-479. Chang, C. S., T. S. Chen, and W. H. Hsu. 2011. The study on integrating WebQuest with mobile learning for environmental education. Computers and education 57:1228-1239. Chen, M.C., J. L. Chen, and T. W. Chang. 2011. Android/OSGI-based vehicular network management system. Computer communications 34:169-183. Chen, P. S. 1976. The entity-relationship model-toward a unified view of data. ACM Transactions on Database Systems 1:9-36. CODD, E. F. 1970. A relational model of data for large shared data banks. Commuications of the ACM 13(6):377-387. Dala-Ali, B., M. A. Lloyd, and Y. Al-Abed. 2011. The uses of the iPhone for surgeons. The surgeon 9:44-48. Devraj., and R. Jain. 2011. PulsExpert: An expert system for the diagnosis and control of diseases in pulse crops. Expert Systems with Applications 38:11463-11471. Doluschitz, R., and Schmisseur, W. E.. 1988. Expert system: Applications to agriculture and farm management. Computers and Electronics in Agriculture 2:173-182. FAO. 2011. Ecocrop database. FAO Available:http://ecocrop.fao.org/ecocrop/srv/en/home (accessed 9 Jun. 2013). FAO. 1976. A framework for land evaluation. Soils bulletin 32. Rome. Feigenbaum, E. A. 1977. The art of artificial intelligence: Themes and case studies of knowledge engineering. p.1014-1029. In: Proc. of the 5th IJCAI, Cambridge, MA. Grove, R. F. 2000. Design and development of knowledge-based systems on the web. In Proceedings of ISCA 2000: 9th International Conference on Intelligence Systems: Artificial Intelligence Applications for the New Millennium, Louisville, KY, USA p. 147-150. International Telecommunications Union. 2010. Measuring the information society 2010. Geneva, Switzerland: ITU. Kolhe, S., and Gupta, G. K. 2006. Web-based soybean disease diagnosis and management system. In: Paper presented in Fifth Conference of the Asian federation for Information Technology in Agriculture (AFITA) organized by Indian Society of Agricultural Information Technology (INSAIT) at Indian Institute of Sciences, Bangalore, Karnataka, India, 9-11 Nov. p. 553-559. Kolhe, S., Kamal, R., Saini, H. S., Gupta, G. K. 2007. Prototype Intelligent Information System for Disease Diagnosis in Crops. In: 3rd Indian International Conference on Artificial Intelligence (IICAI-07) , Pune (Maharashtra), India, p. 1582-1594. Kumar, S., and R. B. Mishra. 2010. Web-based expert systems and services. The Knowledge Engineering Review 25:167-198. Lai, J. C., B. Ming, S. K. Li, K. R. Wang, R. Z. Xie., and S. J. Gao. 2010. An Image-Based Diagnostic Expert System for Corn Diseases. Agricultural Sciences in China 9(8):1221-1229. Li., Y. S., and L. F. Hong. 2011. Development of a Non-Pollution Orange Fruit Expert System Software Based on ASP.NET. Agricultural Sciences in China 10(5):805-812. Lopez-Morales, V., Lopez-Ortega, O., Ramos-Fernandez, J., and Munoz, L. B. 2008. JAPIEST: An integral intelligent system for the diagnosis and control of tomatoes diseases and pests in hydroponic greenhouses. Expert Systems with Applications 35(4):1506-1512. Mansingh, G., H. Reichgelt, and K. M. O. Bryson. 2007. CPEST: An expert system for the management of pests and diseases in the Jamaican coffee industry. Expert Systems with Applications 32(1):184-192. Monares, A., S. F. Ochoa, J. A. Pino, V. Herskovic, J. Rodriguez-Covili, and A. Neyem. 2011. Mobile computing in urban emergency situations: improving the support to firefighters in the field. Expert Systems with Applications 38(2):1255-1267. Nwigbo, S. N, and O. C. Agbo. School of Science Education, Expert system: a catalyst in educational development in Nigeria. http://www.hrmars.com/admin/pics/261.pdf (accessed 5 Aug. 2013). Papadopoulos, A., D. Kalivas, and T. Hatzichristos. 2011. Decision support system for nitrogen fertilization using fuzzy theory. Computers and Electronics in Agriculture 78(2):130-139. Patil, S. S., B. V. Dhandra, U. B. Angadi, A. G. Shankar., and N. Joshi. 2009. Web based Expert System for Diagnosis of Micro Nutrients Deficiencies in Crops. Proceedings of the World Congress on Engineering and Computer Science. Rajkishore, P., Rajeev, R. K., and Sinha, A. K. 2006. AMRAPALIKA: An expert system for the diagnosis of pests, diseases and disorders in Indian mango. Knowledge-Based Systems 19(1):9-21. Rajkishore, P., Sinha, A. K., Rajeev, R. K., Prasad, R., and Mei, F. 2002. KISAN: An Expert System for Soil Nutrient Management. Third Asian Conference for Information Technology in Agriculture p. 346-353. Recio, B., F. Rubio, and J. A. Criado. 2002. A decision support system for farm planning using AgriSupport II. Decision Support Systems 36(2):189-203. Ruchter, M., B. Klar, and W. Geiger. 2010. Comparing the effects of mobile computers and traditional approaches in environmental education. Computer and Education 54(4):1054-1067. Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. Official Soil Series Descriptions. Available: http://soils.usda.gov/technical/classification/osd/index.html. (accessed 9. Jun. 2013b). Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. Soil Survey Geographic (SSURGO) Database. Available: http://soildatamart.nrcs.usda.gov. (accessed 9 Jun. 2013a). Sonar, R. M., and A. Saha. 2001. An intergration framework to develop modular hybrid intelligent systems. Frontiers in Artificial Intelligence and Applications 69:1499-1506. Song, H., and Y. He. 2005. Crop nutrition diagnosis expert system based on artificial neural networks. Information Technology and Applications, 2005. ICITA 2005. Third International Conference on , vol.1, no., pp.357,362 vol.1,pp4-7. Thomas, M. B., J. H. Crane, J. J. Ferguson, H. W. Beck, and J. W. Noling. 1997. Two computer-based diagnostic systems for diseases, insect pests, and physiological disorders of citrus and selected tropical fruit crops. HortTechnology 7(3): 293-298. Townsend, C. 1987. Mastering Expert Systems with Turbo Prolog. Macmillan, Inc. Indianapolis, IN. p. 257. Travis, J. W., & Latin, R. X. 1991. Development, Implementation, and Adoption of Expert Systems in Plant Pathology. Annual Review of Phytopathology 29:343-360. USDA, NRCS. 2013. The PLANTS Database (http://plants.usda.gov, 9 June 2013). National Plant Data Team, Greensboro, NC 27401-4901 USA. Xu, C., and H. Liu. 2008. Crop candidates for bioregenerative life support systems in China. Acta Astronautica 63:1076-1080. Zhang, H., L. Zhang, Y. Ren, J. Zhang, X. Xu, X. Ma, and Z. Lu. 2011. Design and Implementation of Crop Recommendation Fertilization Decision System Based on WEBGIS at Village Scale, p. 357-364, In D. Li, et al., (eds.) Computer and Computing Technologies in Agriculture IV. ed. IFIP Advances in Information and Communication Technology. Springer Berlin Heidelberg.
摘要: 農業電子化是一個重要的課題,近年來各種農業相關資料庫、資訊系統的建置也蓬勃發展。目前國外和國內有關作物生長特性的資訊大多是利用聯合國農糧組織建立的ECOCROP,然而其所能提供的資訊並無法顯現出同種作物間因為品種改良而產生的環境需求差異,也無法提供特定品種於不同生長期適合的生長條件與氣象災害條件。 本論文擬建立一個能夠儲存各作物品種在不同生長階段適合的生長條件與氣象災害條件之關聯資料庫。由於這些資料蒐集並不容易,因此本資料庫設計上採用類似維基百科的方式,藉由所開發的網頁平台蒐集四散於各地的作物資料,蒐集的資料再藉由特有的兩段式更新方法對資料品質進行控管。最後利用本作物資料庫配合行政院農業委會農業試驗所之農業氣象諮詢系統,作一簡單的適栽作物推薦作業之模擬應用。
Electronic agriculture is an important subject in recent years. Various agriculture-related databases and information system implementation are also booming. Most crop growth characteristics used by domestic or international experts derived from ECOCROP built by FAO. However, the information from ECOCROP cannot provide the differences between varieties, and cannot offer the most suitable growth conditions or agrometeorological disaster damage conditions for specific growth stage. In this thesis, we intent to establish a crop database which could store suitable growth conditions and damaging weather conditions for different growth stages using relational database management system. In addition, we try to mimic the way of wikipedia did in data collection, because the required crop information is hard to collect. Web pages are designed for easy to collect the crop information scattered in the world. We used “Two Phase Update” method to ensure the quality of the collected data. Finally, we integrate the crop database and the agrometeorological information system built by Taiwan Agricultural Research Institute, Council of Agriculture, to demonstrate a simple application in crop suitability recommendation.
URI: http://hdl.handle.net/11455/25611
其他識別: U0005-0808201315112500
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-0808201315112500


在 DSpace 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。