Agricultural and Veterinary Sciences

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    The potential distribution of Bacillus anthracis suitability across Uganda using INLA
    (Nature Publishing Group, 2022-11) Ndolo, V A; Redding, D; Deka, M A; Salzer, J S; Vieira, A R; Onyuth, H; Ocaido, M; Tweyongyere, R; Azuba, R; Monje, F; Ario, A R; Kabwama, S; Kisaakye, E; Bulage, L; Kwesiga, B; Ntono, V; Harris, J; Wood, J L N; Conlan, A J K
    Abstract To reduce the veterinary, public health, environmental, and economic burden associated with anthrax outbreaks, it is vital to identify the spatial distribution of areas suitable for Bacillus anthracis, the causative agent of the disease. Bayesian approaches have previously been applied to estimate uncertainty around detected areas of B. anthracis suitability. However, conventional simulation-based techniques are often computationally demanding. To solve this computational problem, we use Integrated Nested Laplace Approximation (INLA) which can adjust for spatially structured random effects, to predict the suitability of B. anthracis across Uganda. We apply a Generalized Additive Model (GAM) within the INLA Bayesian framework to quantify the relationships between B. anthracis occurrence and the environment. We consolidate a national database of wildlife, livestock, and human anthrax case records across Uganda built across multiple sectors bridging human and animal partners using a One Health approach. The INLA framework successfully identified known areas of species suitability in Uganda, as well as suggested unknown hotspots across Northern, Eastern, and Central Uganda, which have not been previously identified by other niche models. The major risk factors for B. anthracis suitability were proximity to water bodies (0–0.3 km), increasing soil calcium (between 10 and 25 cmolc/kg), and elevation of 140–190 m. The sensitivity of the final model against the withheld evaluation dataset was 90% (181 out of 202 = 89.6%; rounded up to 90%). The prediction maps generated using this model can guide future anthrax prevention and surveillance plans by the relevant stakeholders in Uganda.
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    Assessment of Fungal Contamination in Fish Feed from the Lake Victoria Basin, Uganda
    (MDPI AG, 2020-04) Namulawa, Victoria Tibenda; Mutiga, Samuel; Musimbi, Fred; Akello, Sandy; Ngángá, Fredrick; Kago, Leah; Kyallo, Martina; Harvey, Jagger; Ghimire, Sita
    bstract The emergence of commercial fish farming has stimulated the establishment of fish feed factories in Uganda. However, no information is available on the safety of the feed, mainly due to lack of mycotoxin testing facilities and weak regulatory systems. A study was carried out to examine fungal colonization and mycotoxin contamination in fish feed samples (n = 147) of different types collected from nine fish farms (n = 81) and seven fish feed factories (n = 66) in the Lake Victoria Basin (LVB). Fungi were isolated in potato dextrose agar, grouped into morphotypes and representative isolates from each morphotype were identified based on the internal transcribed spacer (ITS) region of ribosomal DNA sequences. Aflatoxin B1 (AFB1) and total fumonisin (combinations of B1, B2 and B3; hereinafter named fumonisin) levels in feed samples were determined by enzyme-linked immunosorbent assay (ELISA). A wide range of fungi, including toxigenic Aspergillus flavus and Fusarium verticillioides, were isolated from the fish feed samples. AFB1 was detected in 48% of the factory samples and in 63% of the farm samples, with toxin levels <40 and >400 µg/kg, respectively. Similarly, 31% of the factory samples and 29% of the farm samples had fumonisin contamination ranging between 0.1 and 4.06 mg/kg. Pellets and powder had higher mycotoxin contamination compared to other commercially available fish feed types. This study shows AFB1 as a potential fish feed safety issue in the LVB and suggests a need for more research on mycotoxin residues in fish fillets.
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    Performance of the Agricultural Credit Facility in Uganda: What are the trends?
    (Budget Monitoring and Accountability Unit, 2019) Budget Monitoring and Accountability Unit
    There is often an assumption that agriculture faces inherent difficulties in mobilizing credit and that this is a binding constraint on expanding agricultural output which justifies government intervention to provide or subsidize agricultural financing.Although the second National Development Plan (NDP II) and the Ministry of Agriculture, Animal Industry and Fisheries (MAAIF) Development and Investment Strategy (DSIP) emphasize increased access to agricultural financing as a fundamental input to the sector transformation, this may not be achieved if the institutional and policy factors are not well streamlined along the credit market chain to solve the demand factors. Since the inception of Agricultural Credit Facility in 2009, various areas in the agriculture value chain have been financed under the scheme. With the introduction of Block Allocation under the current Memorandum of Agreement, 2018, a number of micro borrowers have accessed funding from the scheme which is intended to unlock credit to the smallholder farmers who are unable to access funding due to the stringent loan requirements such as collateral by Participating Financial Institutions (PFIs). This policy brief examines trends in funding, overall physical performance, inclusiveness and investments funded by ACF from FY2011/12 to FY2017/18. The brief uses data from the Budget Monitoring and Accountability Unit (BMAU), Ministry of Finance, Planning and Economic Development (MFPED) and Bank of Uganda (BoU).