A Decision Support System for Economically Sustainable Sheep and Goat Farming

Area of Science:

• Agricultural Science
• Animal Science
• Farm Management

Background:

• European sheep and goat sectors face challenges with low professionalization and fragmented farming systems.
• A need exists for tools to support strategic decision-making in small ruminant production.

Purpose of the Study:

• To present iSAGEDSS, a web-based application for annual management planning in European sheep and goat farming.
• To assess the application's accuracy in predicting farm performance and its impact on management efficiency.

Main Methods:

• Development of a web-based application (iSAGEDSS) using data from meat sheep, dairy sheep, and dairy goat systems across Europe.
• Creation of an algorithm to assess nutritional management's impact on production and financial outcomes.
• Validation through a case study on Greek dairy sheep farms, comparing actual data with model predictions under various scenarios.

Main Results:

• iSAGEDSS demonstrated high prediction accuracy for gross margin (circa 9% error) and production (circa 4% error).
• The application effectively simulated management decisions, including gross margin maximization and milk price fluctuations.
• The study confirmed the tool's potential to improve financial, production, and grazing management efficiency.

Conclusions:

• iSAGEDSS is a valuable tool for European small ruminant farmers, aiding in strategic annual management planning.
• The application supports enhanced decision-making for improved profitability, productivity, and environmental sustainability in sheep and goat farming.