Exploring Opportunities for Developing a Knowledge-based Crop Forecasting System in the Philippines

Professorial Chair Lecture

UPFI Professional Chair Lecture

Place

New CAS Auditorium, UPLB, Laguna

Date

11-23-2004

Abstract

Reliable and timely statistics on crop yields and crop production are important and essential components of a crop monitoring and warning systems for food security assessment. Accurate and up-to-date information regarding expected yields and crop production forecasts considering area planted to the crop are needed by planners and decision makers to address local and national food security issues. Generation of accurate and timely crop forecasts is facilitated by using objective systems analysis-based procedures and methodologies that rely on the advances in information and technologies as well as on the use of system tools such as crop stimulation models, geographic information system (GIS), geographic positioning system (GPS), and remote sensing. A knowledge-based crop forecasting system (CFS) can be used to predict crop production given advanced seasonal climate information. The CFS involved four (4) dissemination of information in crop forecasts. Seasonal climate information at the global or regional level is downscaled to the provincial level using either statistical-empirical techniques or stochastic models. Downscaled seasonal climate forecasts for the province is used to generate finer resolution (daily) weather data for the anticipated during the crop growing period. These synthetic sequences are input s to a locally validated crop simulation model to estimate crop yield given the seasonal time 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 system such as through the local radio station, local communication network, or even through short message system (SMS). It is envisioned that the knowledge based CFS will complement the present DA-BAS system of generating agricultural statistics and forecasts through sample surveys. The use of ICT and systems research tools hopes to make 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 requires addressing challenging issues such as data and information gaps, communications and dissemination of forecasts products, and capacity building of personnel.

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