Turkish Journal of Fisheries and Aquatic Sciences
2026, Vol 26, Num, 9 (Pages: TRJFAS29306)
Quantitative Global Typologies of Rainbow Trout Production from FAO Statistics
2 Iğdır Üniversitesi, Ulaştırma Hizmetleri Bölümü, Iğdır, Türkiye DOI : 10.4194/TRJFAS29306 Viewed : 158 - Downloaded : 447 Rainbow trout (Oncorhynchus mykiss) has become a cornerstone species in global freshwater aquaculture due to its adaptability, high nutritional value, and strong consumer demand. However, production levels differ substantially across countries, reflecting a variety of ecological, economic, and technological conditions. This study provides a quantitative, data-driven classification of worldwide rainbow trout production in order to identify common patterns and emerging trends. Using official FAO statistics covering the years 2016-2023 for 77 countries, we calculated three key indicators mean annual production, coefficient of variation (CV), and linear production trend and applied hierarchical cluster analysis based on Ward`s method with Manhattan distance. Internal validation measures confirmed the robustness of the resulting clusters, while statistical significance was assessed using non-parametric Kruskal- Wallis tests followed by Dunn`s pairwise comparisons. The analysis identified three distinct producer profiles. The first cluster, comprising 63 countries, is characterized by relatively low but stable production. The second cluster (11 countries) also represents low volume producers but exhibits high temporal variability, suggesting inconsistent or fragmented production systems. The third cluster includes only three countries Turkey, Iran, and Russia but shows markedly high production volumes with strong upward trends, positioning them as global growth leaders. By distinguishing stable, volatile and rapidly expanding producers, this study fills a gap in the literature and provides a framework for guiding aquaculture policy, investment and sustainability initiatives at the global scale. Keywords : Oncorhynchus mykiss Aquaculture Global production Clustering analysis Sustainability












