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SURVEY ON THE DEVELOPMENT OF CROP MODELS IN INDONESIA. A Progress Report by : Budi I . Setiawan, K.Honda , R . Chinnachodteeranun, Gardjito , M.Taufik . BACKGROUND. IMPORTANCE TO KNOW ACCURATE PLANT GROWTH , HARVEST TIME & EXPECTED YIELDS
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SURVEY ON THE DEVELOPMENT OF CROP MODELS IN INDONESIA A Progress Report by: Budi I. Setiawan, K.Honda, R. Chinnachodteeranun, Gardjito, M.Taufik
BACKGROUND • IMPORTANCE TO KNOW ACCURATE PLANT GROWTH, HARVEST TIME& EXPECTED YIELDS • CROP MODEL NEED TO BE DEVELOPED AS A VALUABLE TOOL. • CROP MODEL SHOULD BE USABLE & UNDERSTANDABLE BY ANY CONCERNING PARTIES: • Farmers • Managers • Supervisors • Policy makers • Model Developers Crop Modelling
BACKGROUND • CROP MODEL SHOULD ENABLE TO RESPONSE DYNAMIC ENVIROMENTAL CHANGES. • CROP MODEL SHOULD CONSIDER INFLUECING FACTORS: • Determining factors: • Genotype, solar radiation, temperature, and else. • Limiting factors: • Water, soil nutrients, and else. • Reducing factors: • Pests, deseases, weeds, pollution, and else. Crop Modelling
BACKGROUND • TO CREATE SUCH CROP MODEL NEEDS: • Robust monitoring system. • Interactive to various users. • Capable to developed by others. • Common data be shared by others. • BEFORE CREATING SUCH CROP MODEL NEED TO KNOW DEVELOPMENT OF CROP MODEL. • Status • Constraint • Trend Crop Modelling
PURPOSES • To know crop models for 6 commodities developed in Indonesia: • Paddy • Corn • Cassava • Sugarcane • Oil Palm • Rubber • To the status of the models • To identify scientits and institutions developing the models. • To form a research network on crop models. Crop Modelling
METHODS • Collect articles, research reports, etc. • Communice with the authors. • Round table discussions. • Select competent scientists and institutions. • Site visit to the selected institutions. • Interview with other scientists in sites. • Hold seminar and workshop. Crop Modelling
RESULTS • Documents: • Paddy: 13 docs. • Corn: 20 docs. • Cassava: 4 docs. • Sugarcane: 8 docs. • Oil Palm: 10 docs. • Rubber: 5docs. • Crop Models: • Most models based on statistical analysis • There were ORYZA _W and 2000 but only for introduction. • Others: System Dynamics, Artificial Neural Networks Crop Modelling
RESULTS • NEW DEVELOPMENTS IN PADDY FIELDS BASED ON CLIMATE MEASUREMENT AND PREDICTION FOR: • Determining planting calendar. • Cultivation methods. • Estimating dry season. • Estimating pest outbreaks. Crop Modelling
WEB BASED INFORMATION PEST OUTBREAKS CLIMATE PREDICTION Crop Modelling
INSTRUMENTATION Crop Modelling
TELEMETRY STATIONS Crop Modelling
MONITORING SYSTEM Crop Modelling
FIRST ROUND DISCUSSIONBogor, Saturday/11 Feb 2012 Crop Modelling
THANK YOU Budi I. Setiawan, K.Honda, R. Chinnachodteeranun, Gardjito, M.Taufik Crop Modelling