Diagnosis and treatment of flexibacteriosis of koi carp (Cyprinus carpio koi)

Ornamental fish farming is an intensively developing area in aquaculture. A significant volume of contraband products and the lack of sanitary and quarantine measures is an important problem associated with the development of this knowledge area. The article is devoted to the problem of timely detection and diagnosis of flexibacteriosis of carp, affecting one of the most popular and expensive objects of ornamental fish farming, koi carp. The main causes of fish diseases are natural outbreaks of infections and infection with pathogens from water sources, as well as violations of the rules of transportation and quarantine of imported fish. Timely and constant veterinary control makes it possible to assess the epizootic situation for fish diseases, the degree of pollution of the fishery reservoir and make recommendations for optimizing preventive measures that ensure the epizootic well-being of the fishery reservoir in the conditions of integrated technology. The cultivation of koi by amateurs in private ponds, aquariums poses a danger of introducing infections into other reservoirs, including natural ones, as well as regions where the outbreak has never been recorded. The main task is the prevention of diseases, which can be ensured by monitoring the water quality of the water supply source, as well as the use of a complex of veterinary and sanitary measures, including veterinary control over the transportation of fish, preventive quarantine of imported material and quarantine in dysfunctional farms, preventive disinfection and disinfection of structures, inventory, pond beds; regular ichthyopathological examination of the farm; preventive antiparasitic treatment of fish.

A Machine Learning Approach for Early Detection of Fish Diseases by Analyzing Water Quality

Early detection of fish diseases and identifying the underlying causes are crucial for farmers to take necessary steps to mitigate the potential outbreak and thus to avert financial losses with apparent negative implications to the national economy. Typically, fish diseases are caused by viruses and bacteria; according to biochemical studies, the presence of certain bacteria and viruses may affect the level of pH, DO, BOD, COD, TSS, TDS, EC, PO43-, NO3-N, and NH3-N in water, resulting in the death of fishes. Besides, natural processes, e.g., photosynthesis, respiration, and decomposition, also contribute to the alteration of water quality that adversely affects fish health. Being motivated by the recent successes of machine learning techniques, a state-of-art machine learning algorithm has been adopted in this paper to detect and predict the degradation of water quality timely and accurately. Thus, it helps to take preemptive steps against potential fish diseases. The experimental results show high accuracy in detecting fish diseases specific to water quality based on the algorithm with real datasets.

Polyculture in fish farming as a method of preventing fish diseases

Methods of prevention of fish diseases are aimed at destroying parasites in the host body and in the fish habitat — in the reservoir (chemoprophylaxis, increasing fish resistance), at preventing parasites from entering the reservoir (limiting the import of fish, import of healthy fish, quarantine measures, etc.), as well as preventing their spread and entry into the host body. It is shown that polyculture is not only the most effective method of using the natural forage base of the reservoir and, as a result, increasing fish productivity, but also a means of preventing mass infectious and other fish diseases. To prevent mass infectious diseases of fish and death from them both in safe and unfavorable ponds of carp fish farms, it is advisable to grow other fish species together with carp that do not suffer from diseases peculiar to carp. As a result, so-called sparse species plantings of fish are created in the ponds, while the total biomass remains high. At the same time, the natural food supply of ponds is most fully used and a kind of biological buffer is created that prevents the emergence and spread of contagious diseases. Polyculture can play a particularly important role in pond farms that already have certain problems with rubella, filometroidosis, botryocephalosis, carp pox, etc. Long-term studies of breeding herds in pond farms have shown that most of them have single foci of diseases, which, if there are optimal conditions for the pathogen, are ready to immediately respond with an outbreak of the disease or are generally quarantined for a particular fish disease. When determining the objects of polyculture, it is necessary to reduce the proportion of fish species that have a significant number of common diseases.

Management Practices, Farmers’ Knowledge of Diseased Fish, and Their Occurrence in Fish Farms in Nyeri County, Kenya

In this study, fish farmers’ management practices, occurrence, and knowledge of fish diseases in Nyeri County, Kenya, were evaluated. Fish farming management practices for small-scale farmers in Kenya have numerous challenges which have led to disease occurrence and reduced production. Moreover, the impact and association of these challenges to farmers’ knowledge of fish diseases and their burden has not been fully studied. A semistructured questionnaire was used to capture farmers’ biodata, fish species farmed, and farmers’ management practices such as handling of nets, pond fertilization, and disposal of fish waste. Farmers’ knowledge of fish diseases was based on their ability to identify independent and dependent variable indicators. Independent variables included clinical signs, decreased feeding, bulging eyes, floating on water, abdominal swelling, bulging eyes, abnormal skin color, reduced growth, and abnormal swimming with fish death as were the dependent variable. A total of 208 farmers were interviewed and included those of tilapia (134), mixed tilapia and catfish (40), catfish (22), rainbow trout, and five dams under cooperative management. Tilapia was the most kept fish species (66.8%) followed by polyculture of tilapia and catfish (20%) and rainbow trout (2%). Most respondents were male (78.5%) over 51 years of age (50%). Fifty percent of the respondents had secondary school education. There was a significant association between deaths and sharing of nets in Kieni East subcounty ( p = 0.0049 , chi-square), while on-farm fish waste disposing appeared to cause higher deaths compared to burning of the waste although not statistically significant ( p = 0.13 ). Few respondents observed decreased feed uptake (<20%) and poor growth. Fifty-seven percent of farmers reported mortalities. Fish poor growth, floating in water, and management practices in subcounties had significant effect on fish deaths. The farmers had knowledge of signs of diseased fish, but there was paucity of knowing the specific causes of disease. Farmers need to be empowered on best aquaculture husbandry to avoid disease transmission and specific fish disease signs to enhance proper reporting of disease for subsequent mitigation measures.

Awareness and Constraints of Aquaculture Biosecurity Among Fish Farmers in Ekiti State, Nigeria

The study investigated the level of awareness and constraints the farmers were facing in adopting effective biosecurity measures in Ekiti State. Primary data were collected using multi-stage sampling technique to randomly select 150 fish growers, out of which 144 questionnaires were recovered. Analysis was carried out using descriptive statistics, four-point Likert scale and multiple regression. The result showed that 76.4% of the fish farmers with mean age of 40.48±10.28years were married, 61.1% owned the land on which they farm their fish, 73.6% operated as small scale fish farmers with farm size of <1 hectare. About 91.0% knew about fish diseases, the main source of pollution on the farm was flooding while some (61.1%) experienced outbreak of fish diseases at juvenile stage. High cost of facilities, lack of financial assistance, poor knowledge on biosecurity, expensive laboratory charges and inadequate monitoring by extension agents was perceived as the major constraints. The farmers need financial help to get adequate facilities and to enlarge their scale of operation. Adequate extension services to enlighten them on the effective biosecurity measures should be adopted.

An overview of fish disease and parasite occurrence in the cage culture of Oreochromis niloticus: A case study in Lake Victoria, Kenya

Cage aquaculture has been on a steady rise in Lake Victoria, Kenya, since 2016, resulting in the current culturing of over 3,600 cages of Tilapia (O. niloticus) (Orina et al., 2018). Unfortunately, there has been limited, if any, focus on fish health aspects. Rise in intensification and commercialization predisposes fish stocks to disease due to rise in stress levels and consequent reduction in the fish immunity. Nutrient rich surroundings create a conducive environment for rapid proliferation of bacterial and saprophytic fungal growth leading to net clogging and consequently a low biological oxygen demand. Such conditions predispose the stocks to infections. This study was conducted to provide a baseline analysis of the health conditions/status of the cultured fish in this region. It encompassed studies from 2016 to 2018 on tilapia of the genus O. niloticus using both experimental (using standard procedures and protocols) and socio-economic studies (using structured questionnaires, see annexure 1). Results found the following occurrences; bacterial infections (10%), fungal infestations (12.5%), myxosporean parasites in the gills (5%), parasitic copepods (10%) and fin rot (2.5%) in the stocks. There were no significant differences between abiotic parameters in the cage locations and the wild (p &gt; 0.05). Additionally, 90% of the respondents had no fish disease training or clue on the treatment action necessary whenever fish diseases struck. Findings from this study put to the fore the significance of fish diseases in a cage culture system in light of commercialization of the industry and the importance of biosecurity and maintenance of optimal environmental conditions within the scope of Blue Economy growth in this region. This study did not detect any disease or parasite of zoonotic importance.