The files are attached below. It's 6 questions based off the article.
You must save this file as Lastname_ Firstname_ JAA. For example: Smith_John_JAA 1. In your own words, describe what problems or limitations you see in the authors’ methodology (8pts). 2. In your own words, describe how the authors analyzed their data. What test/s did they use? 8pts. How reliable are the results? Found in the discussion section 3. Explain what the authors suggest as problems with the study that could lead to unreliable results. Include quotation marks around the exact wording, and indicate page number(s) (8pts). 4. In your own words, describe what problems you see in the study that could lead to unreliable results (8pts). 5. In your own words, describe if the conclusions made (about the results) by the author make sense to you? Are the conclusions too broad or too narrow based on what was done in the study? (8pts) The importance of this scientific work Found in the discussion section 6. Write (in your own words) the significant contributions of the experimental work in this journal article as reported by the authors. This is called broader implications. This is usually found at the end of the discussion/conclusions section (8pts). 2 ~ 295 ~ International Journal of Fisheries and Aquatic Studies 2019; 7(2): 295-301 E-ISSN: 2347-5129 P-ISSN: 2394-0506 (ICV-Poland) Impact Value: 5.62 (GIF) Impact Factor: 0.549 IJFAS 2019; 7(2): 295-301 © 2019 IJFAS www.fisheriesjournal.com Received: 20-01-2019 Accepted: 24-02-2019 DW Wanja 1. Department of Veterinary Pathology, University of Nairobi, College of Agriculture and Veterinary Sciences, Microbiology and Parasitology, Kangemi, Nairobi, Kenya 2. Sokoine University of Agriculture, College of Veterinary and Medical Sciences, Chuo KIKUU, Morogoro, Tanzania PG Mbuthia Department of Veterinary Pathology, University of Nairobi, College of Agriculture and Veterinary Sciences, Microbiology and Parasitology, Kangemi, Nairobi, Kenya RM Waruiru Department of Veterinary Pathology, University of Nairobi, College of Agriculture and Veterinary Sciences, Microbiology and Parasitology, Kangemi, Nairobi, Kenya JM Mwadime 1. Department of Veterinary Pathology, University of Nairobi, College of Agriculture and Veterinary Sciences, Microbiology and Parasitology, Kangemi, Nairobi, Kenya 2. Sokoine University of Agriculture, College of Veterinary and Medical Sciences, Chuo KIKUU, Morogoro, Tanzania LC Bebora Department of Veterinary Pathology, University of Nairobi, College of Agriculture and Veterinary Sciences, Microbiology and Parasitology, Kangemi, Nairobi, Kenya PN Nyaga Sokoine University of Agriculture, College of Veterinary and Medical Sciences, Chuo KIKUU, Morogoro, Tanzania HA Ngowi Sokoine University of Agriculture, College of Veterinary and Medical Sciences, Chuo KIKUU, Morogoro, Tanzania Correspondence DW Wanja 1. Department of Veterinary Pathology, University of Nairobi, College of Agriculture and Veterinary Sciences, Microbiology and Parasitology, Kangemi, Nairobi, Kenya 2. Sokoine University of Agriculture, College of Veterinary and Medical Sciences, Chuo KIKUU, Morogoro, Tanzania Bacterial pathogens isolated from farmed fish and source pond water in Kirinyaga County, Kenya DW Wanja, PG Mbuthia, RM Waruiru, JM Mwadime, LC Bebora, PN Nyaga and HA Ngowi Abstract Bacterial infections cause low to high mortality in fish, affecting the productivity of aquaculture. This study aimed at determining the occurrence of bacterial pathogens in farmed tilapia, catfish, goldfish and koi carp and source pond water in Kirinyaga County. A total of 181 healthy-appearing fish and 27 water samples from randomly selected fish farms in the county were processed. Bacteriological isolation was done on aseptically collected skin and kidney swabs; gills and a portion of intestines from each fish and water samples. Isolated bacteria were identified by colony morphology, Gram stain and biochemical characteristics, and some further characterized using API-20E kit. A total of 329 bacterial isolates were recovered from fish organs and 39 from pond water samples. They belonged to 17 genera with 18 different identified bacterial species. The most prevalent species found on the skin, gills, intestines, kidney, and water samples belonged to five genera: Proteus spp. (14.9%), Aeromonas hydrophila (8.2%), Aeromonas caviae (6.3%), Plesiomonas (5.2%), Flavobacterium spp. (5.2%), Aeromonas sobria (4.3%) and Micrococcus spp. (4.3%). Some isolates (11%, n=42) could not be identified. Bacterial species recovered from fish samples were also found in the water samples except: Streptococcus spp., Pseudomonas luteola, Serratia plymuthica and Klebsiella oxytoca. Raoultella terrigena was recovered from water samples only. The study has shown that farmed fish and aquatic environments harbor potentially pathogenic and zoonotic bacteria which may cause significant fish diseases and public health risks. Therefore, there is need to implement stringent management and biosecurity programs. Keywords: Bacterial infections, aquaculture, fish diseases, public health, biosecurity 1. Introduction Kenya has fast growing fish species (Oreochromis niloticus, Clarias gariepinus and Oncorhynchus mykiss) aquaculture industry. The country is among the major aquaculture producers of sub-saharan Africa, with an industry dominated by tilapines [1]. The capture and wild fisheries contributes 0.8% of the Gross Domestic Product (GDP), providing direct employment opportunities to over 500,000 people and supporting over two million people indirectly [1]. However, fish supply in Africa has been declining for a number of reasons while the demand has increased due to rapidly growing human population. In an effort to reverse these trends, aquaculture projects have been massively promoted across the continent, Kenya included. This is characterized by a record growth extensive small scale to intensive large scale fish farms over the last decade. One significant setback for rapid intensification in aquaculture is risk of diseases, caused by parasites [2-4], viruses [5], fungi [6] and bacteria. Although aquaculture may not be exclusively implicated for the rising disease concern in fisheries, it does provide key insights into: how the diseases may be spread, maintained and whether it is significant enough to elicit action. Of the diseases, bacteriosis remains the most damaging to fish production globally due to economic significance of diseases they cause [7]. There has been a steady increase in the number of species of bacteria implicated in causing fish diseases. An estimated 125 different bacterial species belonging to 34 different bacterial families has been reported to cause various fish diseases globally [8], including: Aeromonas spp., Vibrio spp., Pseudomonas spp., Yersinia spp., Flavobacterium spp., Renibacterium spp., Mycobacterium spp., Edwardsiella spp., Citrobacter spp. and Streptococcus spp. [9]. However, there is growing indication that the pathogenic species spectrum as well as the geographic and host range is widening among fish pathogens [10], leading to the emergence of new pathogens. ~ 296 ~ International Journal of Fisheries and Aquatic Studies Most documented cases of fish diseases in Kenya have narrowed their focus to parasitic infections in capture and wild fish [11], and may thereby miss out on potentially important disease-causing bacterial microbes. Concomitant to this; it is essential to monitor the health of fish stock so as to produce fish that is safe for human consumption There is scarce information available on the occurrence of bacterial pathogens affecting the aquaculture sector in Kenya. While most published studies have focused on isolation of single bacteria species; this study aims to isolate and identify common bacterial pathogens in farmed food and ornamental fish and pond water in Kirinyaga County, Kenya. Studies on aquatic bacterial flora would provide information relevant in developing more stringent biosecurity and sanitary measures. 2. Materials and Methods 2.1 Ethical approval This research work was approved by the Faculty of Veterinary Medicine Biosafety, Animal use and Ethics Committee for Experimentations on live non-human vertebrates, University of Nairobi, Kenya. 2.2 Study area and design A cross sectional study was carried out where fish and water samples were collected from five sub-counties of Kirinyaga County, between December 2017 and April 2018. The sub- counties involved were Mwea East, Mwea West, Ndia, Gichugu, Kirinyaga West and Kirinyaga Central (Figure 1). Bacteria were isolated from the sampled fish and source pond water and identified by colony morphology, Gram stain and biochemical characteristics, while some were further characterized using Analytic Profile Index (API) 20E microorganism identification kit. Fig 1: Kirinyaga County map showing the five sub counties (stars) visited during the study. Map modified from Serede et al. [12]. 2.3. Sampling procedure and sample size Simple random sampling was used to select active and available farms in the study area. The sample size was calculated using the formula given by Naing et al. [13]; , where n is the sample size, Z is the Z statistic for a level of confidence (1.96 for 95%), P is expected prevalence (assumed pathogen prevalence level of 50%) and d is the precision, which is equal to 5% (0.05). This gave a sample size of 384. However, only 208 samples comprising: 88 tilapia, 53 catfish, 30 goldfish and 10 koi carp and 27 source pond water samples were collected, owing to limitations in resources and time. Fifteen grow-out farms and five breeder farms were sampled based on availability and consent of farmers and number of active fish ponds. To obtain a proportional sample, 5-10 fish were purchased per pond from selected farmers. Live fish were transported to Kerugoya County Veterinary Department Laboratory for necropsy in sterile 18 litre buckets. Surface pond water samples were collected from the same ponds where fish sampling was done. The water samples were collected aseptically using a sterile 50ml screw capped universal glass bottles, submerged 15cm to 20 cm below the water surface at every sampling. Bottles with water samples were labeled accordingly. Water samples were placed in a cool box packed with ice, then transported to laboratory