|Keywords:||地理資訊系統;全球衛星定位系統;決策支援系統;作物生長模式;Geographic information System;Global Position System;Decision Support System;Cropping Model||Issue Date:||Apr-2000||Publisher:||農業試驗所||Start page/Pages:||65-78||Source:||水稻精準農業(耕)體系之研究||Abstract:||
Agriculture is becoming more of a system and it is also becoming more of a business. As a system, the constituents involved with arid affected by precision agriculture are heading towards a direction of more directed interaction driven by the data which can be provided. The constituents of precision agriculture include the farmer, agribusiness, the agricultural equipment industry, university researcher, and the general public. As the process becomes more systems oriented, we can expect the data derived from precision agriculture to form the foundation some new opportunities including research. It is also reasonable to expect that these data will provide information for legal decisions, government regulation, and environmental accountability. Cultural practices will evolve from precision agriculture that provide more opportunities for changing the growth and development of the crop during the growing seasons. Crop models will serve as a “blueprint” for the potential growth and development of the crop at a point in time. Management models will be developed to perform whole-farm management, as a system of equipment, environmental factors, crops grown, and crop markets. To deal with variations prevailing in fields and crops of planted, precise agriculture provides the best approach decision-making of farm management to raise income, reduce cost waste as well as lessen the impact on the environment. In conventional agriculture, features of crop and soil in the field were frequently regarded as homogeneous; hence, irrigation, fertilizers and pesticides were applied very uniformly. While precision agriculture copes with spatial variations of crops, soil, and environment in field by technologies of computer, communication and automation. That is to incorporate the field survey of appropriate timing and space scale, geographic information system, and spatial variation analysis model. Thus, not only the best cultivation strategy and yield prediction but also various map layers of space distribution could be well made through crop model and decision analysis model. Eventually, the strategy can be carried out by satellite position and automatic technologies.
|Appears in Collections:||(3)農業化學組|
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