A Decision Support System for Economically Sustainable Sheep and Goat Farming

SIMPLE SUMMARY: The viability of the European sheep and goat sector is threatened by market, policy, social and technical challenges. To address such challenges, innovations for efficient farm management, especially with decision support capabilities, are considered a strategic priority. The iSAGEDSS is a web application, based on the Happy GoatS solution, which allows dairy and meat small ruminant farmers to make annual management plans by testing future what-if scenarios. It is designed for the meat sheep production system in the United Kingdom and Spain, the dairy sheep production system in France and Greece and the dairy goat production system in Greece. Moreover, it addresses all important farm parameters (flock size, production, processing, grazing, feeding, income and costs and farm prices) and utilizing an energy and protein-based algorithm for nutritional management assessment it produces reports, which are focused on profitability and productivity. Environmental-related figures are also estimated. Results are illustrated with simple and easily understood charts and plots. Case study application results showed high prediction accuracy and demonstrated the ability of the system to promote efficient farm management. In this regard, iSAGEDSS is expected to help farmers to adjust to the challenges faced by the sector and remain sustainable. ABSTRACT: The European sheep and goat sector is characterized by low professionalization and management training. Moreover, it is fragmented in terms of production aims and farming systems. Here, iSAGEDSS, a web-based application allowing dairy and meat small ruminant farmers in different countries to make annual management plans by testing future scenarios, is presented. Data were obtained for the meat sheep (United Kingdom and Spain), dairy sheep (France and Greece) and dairy goat production systems (Greece) from partners of the Innovation for Sustainable Sheep and Goat Production in Europe (iSAGE) project. These were used to set default values and ranges for all important farm parameters in each system and country. An algorithm was developed assessing nutritional management and its impact on production and financial performance. Reports focus on profitability, productivity and environmental sustainability. A case study in three dairy sheep farms in Greece was performed. In each case, an evaluation scenario was created using actual farm data that were compared with the estimated ones. Two scenarios testing management decisions for gross margin maximization and milk pricing fluctuations were created. Application results showed high prediction accuracy for gross margin and production estimation (error of circa 9% and 4%, respectively). Moreover, the ability to promote financial, production and grazing management efficiency was demonstrated.