Exploring opportunities for developing a knowledge-based crop forescasting system in the Philippines

Английский. Reliable and timely statistics on crop yields and crop production are important and essential component of a crop monitoring and warning systems for food security assessment. Accurate and up-to-date information regarding expected yields and crop production forescasts considering area planted to the crop are needed by planners and decision-nakers to address local and national food security issues. Generation of accurate and timely crop forescasts is facilitated by using objective systems analysis-based procedures and methodologies that rely on the advances in information and communication technologies as well as on the use of systems tools such as crop simulation models, geographic information systems (GIS), geographic positioning system (GPS), and remote sensing. A knowledge-based crop forescasting system (CFS) can be used to predict crop production given advanced seasonal climate information. The CFS involves four activities, namely: 1)anal ysis and downscaling of seasonal climate outlook2)estimation of crop yield given the climate information3)determination of cropped areaand 4) dissemination of information on crop forecasts. Seasonal climate information at the global or regional level is downscaled to the provincial level using either statistical-empirical techniques on stochastic models. Downscaled seasonal climate forecast for the province is used to generate finer resolution (daily) weather data for the anticipated climate during the crop growing period. These synthetic sequences are inputs to a locally-validated crop simulation model to estimate crop yield given the seasonal climate outlook. Remote sensing and GPS technologies are utilized to determine more accurately the area planted to the crop. Information on local crop forecasts and the appropriate crop production strategies for the seasonal climate outlook are then packaged which can be disseminated via cost-effective communication systems such as t hrough the local radio station, local communication network, or even through short messages system(SMS). It is envisioned that the knowledge-based CFS will complement the present DA-BAS system of generating agricultural statistics and crop forescasts through sample surveys. The use of ICT [Information and Communication technologies]and systems research tools hopes to make the forecasts on crop area, yield and production in the province to be more objective, accurate, and timely. However, effective and efficient implementation and institutionalization of the system reequires addressing challenging issues such as data and information gaps, communications and dissemination of forecast products, and capacity building of personnel.

Английский. CF: UP Foundation, Inc. Professorial Chair Lecture 23 Nov 2004 College, Laguna (Philippines)