Using machine learning technique for disease outbreak prediction in rainbow trout ( Oncorhynchus mykiss ) farms

Abstract

Aquaculture is the fastest growing food production industry in the world due to the increasing demand for pan sized fish (Pridgeon & Klesius, 2012). Rainbow trout production in Turkey's inland waters reached the highest production amount in the last decade in 2021 with 134,174 (Turkish Statistical Institute-TUIK, 2022) tons. Furthermore, Turkey is in the leading position in Europe for rainbow trout production (Lasner et al., 2017), 17.2% of which was realized in Muğla province.In intensive fish farming, providing optimum living conditions for the fish and preserving the health of them are the two most important factors to obtain high quality and high quantity products. Diseases can cause billions of dollars loss in fish production as in other husbandry operations (

Antibiotic susceptibility and resistance genes profiles of Vagococcus salmoninarum in a rainbow trout (Oncorhyncus mykiss, Walbaum) farm

“…The development of efficient fish health management systems is essential for the success of an aquaculture operation ( Boran et al, 2013 ). In recent years, management systems have been improved with the contribution of machine learning techniques ( Yilmaz et al, 2022 ; Yilmaz et al, 2023 ; Çakir et al., 2023 ). Despite the advances in developing new vaccines, drugs and computer-assisted techniques, diseases are still the most devastating problem in fish farms ( Kusuda & Kawai, 1998 ).…”