Logistic regression of some risk factors underlying the outbreak of streptococcusis in rainbow trout (Onchorhynchus mykiss) farms in Haraz River, Mazandaran Province, Iran
Streptococcusis is the one of the most important bacterial fish diseases with outbreak in rainbow trout farms in Iran. The fish farmers have been largely suffered from huge economic losses due to the Streptococcusis outbreaks in different rainbow trout farms in Iran. The present study assessed the effects of some environmental risk factors on incidence of streptococcusis in rainbow trout farms in Haraz River in Mazandaran Province, Iran. A suit of environmental factors including water temperature, nitrite, nitrate, ammonium, water turbidity, DO, water Debi and total count of bacteria were explored as influential factors. Fish and water samples were randomly collected from 10 farm on a monthly basis throughout a year. Isolation and recognition of strep strains were made using biochemical and PCR tests and the data were analyzed by logistic regression method. According to the results, 20% of the differences were explained by the logistic model. Management of these factors might decline the rate of disease outbreak.
| Main Authors: | , , , , |
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| Format: | Journal Contribution biblioteca |
| Language: | other |
| Published: |
2013
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| Subjects: | Streptococcusis, Risk factors, Rainbow trout, Logistic regression, Onchorhynchus mykiss, Fish, |
| Online Access: | http://hdl.handle.net/1834/10680 |
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| Summary: | Streptococcusis is the one of the most important bacterial fish diseases with outbreak in
rainbow trout farms in Iran. The fish farmers have been largely suffered from huge economic
losses due to the Streptococcusis outbreaks in different rainbow trout farms in Iran. The present
study assessed the effects of some environmental risk factors on incidence of streptococcusis in
rainbow trout farms in Haraz River in Mazandaran Province, Iran. A suit of environmental
factors including water temperature, nitrite, nitrate, ammonium, water turbidity, DO, water Debi
and total count of bacteria were explored as influential factors. Fish and water samples were
randomly collected from 10 farm on a monthly basis throughout a year. Isolation and
recognition of strep strains were made using biochemical and PCR tests and the data were
analyzed by logistic regression method. According to the results, 20% of the differences were
explained by the logistic model. Management of these factors might decline the rate of disease
outbreak. |
|---|