LONG-TERM INSIGHTS INTO REGIONAL TRENDS AND FORECASTING IN GLOBAL SHEEP MEAT PRODUCTION

OpenAlex · İngilizce

This study analyses long-term trends in sheep meat production using data collected over a period of more than 50 years, which includes a wide variety of regions with different production systems and challenges. The production of meat is of significant importance to global food security and nutrition, providing sources of protein and essential nutrients. Using ARIMA modelling, the research evaluates historical patterns and forecasts future dynamics, providing valuable insights into the global sheep meat industry. Global sheep meat production trends were analyzed by examining major producer countries, including Algeria, Australia, China, New Zealand, and Türkiye, as well as the European Union, a significant collective producer, and overall global production, thereby highlighting regional differences in production trends and the crucial factors influencing each. The findings indicate that China is expected to maintain its growth trend, whereas production in the European Union may continue to decline in the short term without strategic interventions. ARIMA projections indicate that production in Algeria and Türkiye is likely to remain at a consistent growth trend, while Australia and New Zealand are expected to decline following marginal fluctuations. Although the European Union countries are still among the first 3 with the highest production capacity, it was found that the trend of decline in recent years is likely to persist. On a global scale, there is a projected annual increase in sheep meat production. By utilising these forecasts, the global sheep meat industry can more effectively manage the challenges and thereby ensure an ongoing role in the global food system. The present study underscores the vital necessity for long-term planning and international collaboration to ensure the sustainability and competitiveness of sheep meat production on a global scale. Keywords: Livestock, Time series predictions, Sustainability, ARIMA modeling