The purpose of this study was to identify, select and analyze international experiences for farmmodels and to establish an operational monitoring center, forecast-signaling systemsand predictability model.e plant diseases and pests, farm production, diseases and natural damages(frosts, floods, etc.) using a set of criteria and tools within the project "Strengthening forecast-signalsin agriculture through the development of innovative services in the context of economicdevelopment regional.

This study presents the micro-simulation model of the farm that uses data collected on the farmthrough questionnaires. Farm production and financial data from on-farmquestionnairesare combined with area-specific climate data, including various measurements of rainfall, temperatureand soil moisture. The model is evaluated as a statistical model that links farmresults (e.g., arable crops, livestock products, vegetables, fruits, etc.), with the use of inputs (eg fuel, chemical fertilizers, labor, etc.) and changes in farm stock (e.g. change in live stock) with fixed farminputs, input and product prices, climate variables and other control variables.

The study also outlines descriptions of similar international practices / policies for agricultural fieldmeasurement and monitoring systems, pest disease issues in agriculture and livestock, legal and institutional framework for agricultural information systems, disease predictability models and software respectively, the impact of agriculture from meteorological events and the need to set upa modern forecasting system.