Abstract
Su ürünleri sektörü gerek istihdam ve gerekse elde edilen ürünlerin sağlıklı beslenmeye katkısı nedeniyle oldukça önemlidir. Bu sektörün yeterli hızda ve sürdürülebilir düzeyde büyüyebilmesi için sektörde görülen hastalıklar ve mücadele yöntemlerinin belirlenmesi ve bu bağlamda daha etkin önlemlerin alınması önem arzetmektedir. Bu çalışmada Erzurum il ve ilçelerinde bulunan kara ve baraj balık tesislerinde hali hazırda kullanılan ilaç ve aşıların kullanım düzeyleri belirlenmiş, aquakültür ortamında balıkların enfeksiyon hastalıkları ve bu hastalıklar için kullanılan ilaçlar ve aşılar hakkında bilgiler ve etkili yaklaşımlar belirlenmiştir. Bu kapsamda bölgedeki 41 çiftlik yöneticisiyle yapılan anketler aracılığıyla tesis yönetimi uygulamalarını incelenmiştir. Çalışma sonunda işletmelerin ortalama 51,58 kg ilaç kullandıkları, 50-100 ton kapasite ile üretimde bulundukları ve en çok tercih edilen su kaynağının (%59) göller olduğu belirlenmiştir. İşletmeler çoğunlukla (%54) açık devre sistem ve %84 oranında palet yemi kullanmakta olup üretimin %75’ini gökkuşağı alabalığı oluşturmaktadır. En sık görülen hastalıklar bakteri ve mantar enfeksiyonları ile paraziter ve viral hastalıklardır. Tercih edilen ilaçların dezenfektan, antibiyotik, antiparaziter, takviye ve fungusitler olduğu tespit edilmiştir. Üreticiler %68 kapasite ile çalışmakla birlikte bu duruma yetersiz talep, yüksek maliyetler ve hastalıkları sebep olarak ifade etmişlerdir. Yapılan istatistiksel analizler, 22 önemli kriter temelinde iki farklı grup belirleyen kümeleme analiziyle bölgeye özgü önemli bulgular ortaya koymuştur. 'Diana' yönteminin en uygun kümeleme yaklaşımı olarak belirlendiği sonuçlar, tesis yönetimi stratejilerinin iyileştirilmesi için uygulanabilir öneriler sunmaktadır. Elde edilen bulgular, çiftliklerin ilaç kullanım alışkanlıklarına dair detaylı bilgiler sağlamış ve bölgedeki işletmelerin ihtiyaçlarını daha iyi anlamayı mümkün kılmıştır. Sonuç olarak, bu çalışma, yalnızca işletmelerin stratejik yönetimine değil, aynı zamanda bölgesel kalkınmaya yönelik politika geliştirme süreçlerine de önemli katkılar sağlayacaktır.
Keywords
References
- Assefa, A., & Abunna, F. (2018). Maintenance of fish health in aquaculture: review of epidemiological approaches for prevention and control of ınfectious disease of fish. Veterinary Medicine International, 2018(1), 5432497. https://doi.org/10.1155/2018/5432497
- Banerjee, A., & Dave, R.N. (2004). Validating clusters using the Hopkins statistic. International Conference on Fuzzy Systems, Proceedings Book, 149 153, Budapest, Hungary. https://doi.org/10.1109/FUZZY.2004.1375706
- Brailas, A., Tragou, E., & Papachristopoulos, K. (2023). Introduction to qualitative data analysis and coding with QualCoder. American Journal of Qualitative Research, 7(3), 19-31. https://doi.org/10.29333/ajqr/13230
- Charrad, M., Ghazzali, N., Boiteau, V., & Niknafs, A. (2014). NbClust: An R package for determining the relevant number of clusters in a data set. Journal of Statistical Software, 61, 1 36. https://doi.org/10.18637/jss.v061.i06
- Chong, R., Bousfield, B., & Brown, R. (2011). Fish disease management by the agriculture, fisheries and conservation department (AFCD), Hong Kong. Fish Disease Management, 1(8), 1–12. Çöteli, F.T. (2024) Fisheries Products. Retrieved from https://arastirma.tarimorman.gov.tr/tepge/Documents
- Dandi, S.O., Abarike, E.D., Abobi, S.M., Doke, D.A., Lyche, J.L., Addo, S., & Cudjoe, K.S. (2024). Knowledge attitudes and practices of antibiotic use among small, medium and large scale fish farmers of the stratum ıı of the Volta Lake of Ghana. Antibiotics, 13(7), 582. https://doi.org/10.3390/antibiotics13070582
- Duman, H. (2024). Evaluation of the impact of environmental conditions on dairy cattle milk yield using machine learning algorithms. Doctoral dissertation. Iğdır University, Turkey.
- Gan, G., Ma, C., & Wu, J. (2020). Data clustering: theory, algorithms, and applications. Society for Industrial and Applied Mathematics. Retrieved from https://epubs.siam.org/doi/book/10.1137/1.9781611976335
- Giordani, P., Ferraro, M. B., & Martella, F. (2020). An Introduction to Clustering with R. Springer.
- Hensley, S., Fox, J., Cummins, M., Franks, M., Bird, M., Wells, C., & Miller, J. (2024). The key to coding qualitative data: examples from the 4th youth retention study. Journal of Extension, 62(1), 15. https://doi.org/10.34068/joe.62.01.15
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- Kassambara, A. (2017). Practical Guide to Cluster Analysis in R. Retrieved from https://xsliulab.github.io/Workshop/2021/week10/r-cluster-book.pdf
- Koca, S.B., Terzioğlu, S., Didinen, B.İ., & Yiğit, N.Ö. (2011). Environmentally friendly production in sustainable aquaculture. Ankara University Journal of Environmental Sciences, 3(1), 107-114. (in Turkish with English abstract)
- Kuhn, M., & Johnson, K. (2013). Applied Predictive Modeling. https://doi.org/10.1007/978-1-4614-6849-3
- Kumar, V., Roy, S., Meena, D.K., & Sarkar, U.K. (2016). Application of probiotics in shrimp aquaculture: ımportance, mechanisms of action, and methods of administration. Reviews in Fisheries Science & Aquaculture, 24(4), 342-368. https://doi.org/10.1080/23308249.2016.1193841
- Parmenter, D. (2007). Pareto's 80/20 Rule for Corporate accountants. Retrieved from https://ndl.ethernet.edu.et/bitstream/123456789/18486/1/197.pdf
- Patil, P.K., Mishra, S.S., Pradhan, P.K., Manna, S.K., Abraham, J.T., Solanki, H.G., & Jena, J. (2022). Usage pattern of chemicals, biologicals and veterinary medicinal products in Indian Aquaculture. Reviews in Aquaculture, 14(4), 2038-2063. https://doi.org/10.1111/raq.12688
- Peeler, E.J., & Taylor, N.G. (2011). The application of epidemiology in aquatic animal health-opportunities and challenges. Veterinary Research, 42(1), 94. https://doi.org/10.1186/1297-9716-42-94
- Plant, K.P., & LaPatra, S.E. (2011). Advances in fish vaccine delivery. Developmental and Comparative Immunology, 35(12), 1256-1262. https://doi.org/10.1016/j.dci.2011.03.007
- Rico, A., Satapornvanit, K., Haque, M.M., Min, J., Nguyen, P.T., Telfer, T.C., & Brink, P.J. (2012). Use of chemicals and biological products in asian aquaculture and their potential environmental risks: A critical review. Reviews in Aquaculture, 4(2), 75-93. https://doi.org/10.1111/j.1753-5131.2012.01062.x
- Romero, J., Feijoó, C.G., & Navarrete, P. (2012). Antibiotics in aquaculture–use, abuse and alternatives. Health and Environment in Aquaculture, 159(1), 159-198. https://doi.org/10.5772/28157
- Samanidou, V.F., & Evaggelopoulou, E.N. (2007). Analytical strategies to determine antibiotic residues in fish. Journal of Separation Science, 30(16), 2549-2569. https://doi.org/10.1002/jssc.200700252
- Souza, P. (2022). Innovation in Industrial Research. Csiro Publishing.
- Toomey, D. (2014). R for Data Science. Retrieved from https://www.scribd.com/document/802361299/Ebooks-PDF-download-R-for-Data-Science-1st-Edition-Toomey-full-chapters
- Topal, M. (2017). Investigation and monitoring of tetracycline and degradation products in waters of trout farm. Pamukkale University Journal of Engineering Sciences, 23(3), 74 279. https://doi.org/10.5505/pajes.2016.46704
- Türk, E., & Oğuz, H. (2013). Using medication in aquaculture industry and it's crucial effects on the consumers in terms of public health. Bornova Veteriner Bilimleri Dergisi, 35(49), 35-43.
- Yeo, I.K., & Johnson, R.A. (2000). A new family of power transformations to ımprove normality or symmetry. Biometrika, 87(4), 954-959. https://doi.org/10.1093/biomet/87.4.954
- Yonar, M.E., & Sağlam, N. (2013). Sulphonamides and usage in fish. Menba Journal of Fisheries Faculty, 1(1), 37-42.
The health management and medication use in trout farms located in Erzurum province and its districts
Abstract
The aquaculture sector is very important both in terms of employment and the contribution of the products obtained to healthy nutrition. In order for this sector to grow at a sufficient speed and at a sustainable level, it is important to determine the diseases and control methods seen in the sector and to take more effective measures in this context. In this study, the level of use of drugs and vaccines currently used in land and dam fish facilities in Erzurum province and districts was determined, information and effective approaches were determined about the infectious diseases of fish in aquaculture environment and the drugs and vaccines used for these diseases. In this context, facility management practices were examined through questionnaires conducted with 41 farm managers in the region. At the end of the study, it was determined that the enterprises used an average of 51.58 kg of medicines, produced with a capacity of 50-100 tonnes and the most preferred water source (59%) was lakes. The enterprises mostly (54%) use open circuit system and 84% use pallet feed and 75% of the production is rainbow trout. The most common diseases are bacterial and fungal infections, parasitic and viral diseases. The preferred medicines are disinfectants, antibiotics, antiparasitics, supplements and fungicides. Although the producers work with 68% capacity, they stated insufficient demand, high costs and diseases as the reasons for this situation. Statistical analyses revealed important findings specific to the region through clustering analysis which identified two different groups on the basis of 22 important criteria. The results, in which the ‘Diana’ method was determined as the most appropriate clustering approach, provide applicable recommendations for improving facility management strategies. The findings provided detailed information on the drug utilisation patterns of the farms and made it possible to better understand the needs of the enterprises in the region. As a result, this study will provide important contributions not only to the strategic management of enterprises, but also to policy development processes for regional development.
Keywords
Ethical Statement
As this study involved a survey, the necessary Ethical Committee Approval (no. 2024/28) was obtained from Iğdır University.
Thanks
We would like to thank Edip Bingöl and Canip Koçak, fisheries engineers at the Erzurum Provincial Directorate of Agriculture, for facilitating our connection with the fish farm authorities for the survey work.
References
- Assefa, A., & Abunna, F. (2018). Maintenance of fish health in aquaculture: review of epidemiological approaches for prevention and control of ınfectious disease of fish. Veterinary Medicine International, 2018(1), 5432497. https://doi.org/10.1155/2018/5432497
- Banerjee, A., & Dave, R.N. (2004). Validating clusters using the Hopkins statistic. International Conference on Fuzzy Systems, Proceedings Book, 149 153, Budapest, Hungary. https://doi.org/10.1109/FUZZY.2004.1375706
- Brailas, A., Tragou, E., & Papachristopoulos, K. (2023). Introduction to qualitative data analysis and coding with QualCoder. American Journal of Qualitative Research, 7(3), 19-31. https://doi.org/10.29333/ajqr/13230
- Charrad, M., Ghazzali, N., Boiteau, V., & Niknafs, A. (2014). NbClust: An R package for determining the relevant number of clusters in a data set. Journal of Statistical Software, 61, 1 36. https://doi.org/10.18637/jss.v061.i06
- Chong, R., Bousfield, B., & Brown, R. (2011). Fish disease management by the agriculture, fisheries and conservation department (AFCD), Hong Kong. Fish Disease Management, 1(8), 1–12. Çöteli, F.T. (2024) Fisheries Products. Retrieved from https://arastirma.tarimorman.gov.tr/tepge/Documents
- Dandi, S.O., Abarike, E.D., Abobi, S.M., Doke, D.A., Lyche, J.L., Addo, S., & Cudjoe, K.S. (2024). Knowledge attitudes and practices of antibiotic use among small, medium and large scale fish farmers of the stratum ıı of the Volta Lake of Ghana. Antibiotics, 13(7), 582. https://doi.org/10.3390/antibiotics13070582
- Duman, H. (2024). Evaluation of the impact of environmental conditions on dairy cattle milk yield using machine learning algorithms. Doctoral dissertation. Iğdır University, Turkey.
- Gan, G., Ma, C., & Wu, J. (2020). Data clustering: theory, algorithms, and applications. Society for Industrial and Applied Mathematics. Retrieved from https://epubs.siam.org/doi/book/10.1137/1.9781611976335
- Giordani, P., Ferraro, M. B., & Martella, F. (2020). An Introduction to Clustering with R. Springer.
- Hensley, S., Fox, J., Cummins, M., Franks, M., Bird, M., Wells, C., & Miller, J. (2024). The key to coding qualitative data: examples from the 4th youth retention study. Journal of Extension, 62(1), 15. https://doi.org/10.34068/joe.62.01.15
- Hopkins, B., & Skellam, J. G. (1954). A new method for determining the type of distribution of plant individuals. Annals of Botany, 18(2), 213–227. https://doi.org/10.1093/oxfordjournals.aob.a083391
- Kassambara, A. (2017). Practical Guide to Cluster Analysis in R. Retrieved from https://xsliulab.github.io/Workshop/2021/week10/r-cluster-book.pdf
- Koca, S.B., Terzioğlu, S., Didinen, B.İ., & Yiğit, N.Ö. (2011). Environmentally friendly production in sustainable aquaculture. Ankara University Journal of Environmental Sciences, 3(1), 107-114. (in Turkish with English abstract)
- Kuhn, M., & Johnson, K. (2013). Applied Predictive Modeling. https://doi.org/10.1007/978-1-4614-6849-3
- Kumar, V., Roy, S., Meena, D.K., & Sarkar, U.K. (2016). Application of probiotics in shrimp aquaculture: ımportance, mechanisms of action, and methods of administration. Reviews in Fisheries Science & Aquaculture, 24(4), 342-368. https://doi.org/10.1080/23308249.2016.1193841
- Parmenter, D. (2007). Pareto's 80/20 Rule for Corporate accountants. Retrieved from https://ndl.ethernet.edu.et/bitstream/123456789/18486/1/197.pdf
- Patil, P.K., Mishra, S.S., Pradhan, P.K., Manna, S.K., Abraham, J.T., Solanki, H.G., & Jena, J. (2022). Usage pattern of chemicals, biologicals and veterinary medicinal products in Indian Aquaculture. Reviews in Aquaculture, 14(4), 2038-2063. https://doi.org/10.1111/raq.12688
- Peeler, E.J., & Taylor, N.G. (2011). The application of epidemiology in aquatic animal health-opportunities and challenges. Veterinary Research, 42(1), 94. https://doi.org/10.1186/1297-9716-42-94
- Plant, K.P., & LaPatra, S.E. (2011). Advances in fish vaccine delivery. Developmental and Comparative Immunology, 35(12), 1256-1262. https://doi.org/10.1016/j.dci.2011.03.007
- Rico, A., Satapornvanit, K., Haque, M.M., Min, J., Nguyen, P.T., Telfer, T.C., & Brink, P.J. (2012). Use of chemicals and biological products in asian aquaculture and their potential environmental risks: A critical review. Reviews in Aquaculture, 4(2), 75-93. https://doi.org/10.1111/j.1753-5131.2012.01062.x
- Romero, J., Feijoó, C.G., & Navarrete, P. (2012). Antibiotics in aquaculture–use, abuse and alternatives. Health and Environment in Aquaculture, 159(1), 159-198. https://doi.org/10.5772/28157
- Samanidou, V.F., & Evaggelopoulou, E.N. (2007). Analytical strategies to determine antibiotic residues in fish. Journal of Separation Science, 30(16), 2549-2569. https://doi.org/10.1002/jssc.200700252
- Souza, P. (2022). Innovation in Industrial Research. Csiro Publishing.
- Toomey, D. (2014). R for Data Science. Retrieved from https://www.scribd.com/document/802361299/Ebooks-PDF-download-R-for-Data-Science-1st-Edition-Toomey-full-chapters
- Topal, M. (2017). Investigation and monitoring of tetracycline and degradation products in waters of trout farm. Pamukkale University Journal of Engineering Sciences, 23(3), 74 279. https://doi.org/10.5505/pajes.2016.46704
- Türk, E., & Oğuz, H. (2013). Using medication in aquaculture industry and it's crucial effects on the consumers in terms of public health. Bornova Veteriner Bilimleri Dergisi, 35(49), 35-43.
- Yeo, I.K., & Johnson, R.A. (2000). A new family of power transformations to ımprove normality or symmetry. Biometrika, 87(4), 954-959. https://doi.org/10.1093/biomet/87.4.954
- Yonar, M.E., & Sağlam, N. (2013). Sulphonamides and usage in fish. Menba Journal of Fisheries Faculty, 1(1), 37-42.
Details
| Primary Language | English |
|---|---|
| Subjects | Pisciculture, Fish Pests and Diseases |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | June 14, 2025 |
| Publication Date | June 15, 2025 |
| Submission Date | January 23, 2025 |
| Acceptance Date | May 12, 2025 |
| Published in Issue | Year 2025Volume: 42 Issue: 2 |