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An Integrated Gis and Knowledge-based Decision Support System in Assisting Farm-level Agronomic Decision-making

A main task in agriculture production is field management of water and fertilizer. Excessive fertilizer and water application not only waste resource but also pollute the environment. The traditional principle of digital agriculture can only apply in flat or plain place where a large field usually should be partitioned evenly into many little grids and thus decisions on grid-specific agronomic operation can be recommended. This mode of digital agriculture is called grid-level decision-making. But this seldom happens in farming system in mountainous region due to the complex landform where even grids partition cannot be implemented and so this mode is called farm-level decision-making. In this paper, we develop a web-based decision support system that integrates the expert knowledge, analysis model and GIS to assist farm-level agronomic decision-making and that is fit for any circumstances in agriculture production region with efficient knowledge support. The approach adopted involves general GIS spatial data management (geo-referenced digital map, spatial agriculture decision unit, etc.), agronomic diagnosis and decision-making with integration of expert knowledge and analysis model, so that the variable-rate application of water and fertilizer to any regular or irregular cultivated field can be addressed. The core technology involved includes expert knowledge representation, model organization, software data exchange standard and integration of GIS, expert knowledge and analysis model. With this approach and the basic principle of the traditional digital agriculture, it is possible to tap the variable-rate water and fertilizer application to agronomic fields even in the mountainous and remote region and gain maximum benefit with minimum purchased input, which is very useful in mountainous countries with scattered and small-scale agriculture production. The framework of the developed system is a hybrid structure model composed of B/S (Browser/Server) and C/S (Client/Server), which not only extends the capability of decision support service space but also makes the system easy to maintain. A case study is done in Guangzhou city, located in inter-tropical belt in the South of China and covered by mountainous landform, and shows an exciting result. * Corresponding author.