Assessing climate-induced agricultural vulnerable coastal communities of Bangladesh using machine learning techniques.

The agricultural arena in the coastal regions of South-East Asian countries is experiencing the mounting pressures of the adverse effects of climate change. Controlling and predicting climatic factors are difficult and require expensive solutions. The study focuses on identifying issues other than climatic factors using the Livelihood Vulnerability Index (LVI) to measure agricultural vulnerability. Factors such as monthly savings of the farmers, income opportunities, damage to cultivable lands, and water availability had significant impacts on increasing community vulnerability with regards to agricultural practice. The study also identified the need for assessing vulnerability after certain intervals, specifically owing to the dynamic nature of the coastal region where the factors were found to vary among the different study areas. The development of a climate-resilient livelihood vulnerability assessment tool to detect the most significant factors to assess agricultural vulnerability was done using machine learning (ML) techniques. The ML techniques identified nine significant factors out of 21 based on the minimum level of standard deviation (0.03). A practical application of the outcome of the study was the development of a mobile application. Custom REST APIs (application programming interface) were developed on the backend to seamlessly sync the app to a server, thus ensuring the acquisition of future data without much effort and resources. The paper provides a methodology for a unique vulnerability assessment technique using a mobile application, which can be used for the planning and management of resources by different stakeholders in a sustainable way.

The emergence of foot-and-mouth disease virus serotype O PanAsia-02 sub-lineage of Middle East-South Asian topotype in Bangladesh.

OBJECTIVE: This research work was conducted for the molecular characterization of the circulating foot-and-mouth disease (FMD) virus in Bangladesh and revealed out their serotype. MATERIALS AND METHODS: The VP1 gene of six field isolates of FMD virus (FMDV) serotypes (two serotypes O, two serotypes A, and two serotypes Asia 1) was subjected for sequencing and phylogenetic analysis. Neighbor-joining trees were constructed by using the Molecular Evolutionary Genetics Analysis 6, having the field nucleotide sequences of FMDV and related sequences available in the GenBank. RESULTS: The nucleotide sequences of the VP1 genes of serotypes O, A, and Asia-1 of the isolates revealed that overall isolates were 91%-100% similar to the isolates reported from Bangladesh and other neighboring countries. Among the isolates reported from Bangladesh, serotype O had 98%-100% identity, serotype A had 91%-100% identity, and serotype Asia-1 had 94%-100% identity. A phylogenetic analysis revealed that the FMDV serotype O PanAsia-02 sub-lineage was confirmed in Bangladesh under the Middle East-South Asian (ME-SA) topotype. On the other hand, we identified genotype VII (18) of Asia topotype (serotype A) and lineage C (serotype Asia-1). CONCLUSION: The FMDV serotype O PanAsia-02 sub-lineage was confirmed in Bangladesh under the ME-SA topotype for the first time. The extensive cross-border animal movement from neighboring countries may act as the source of diversified FMDV serotypes in Bangladesh.

Microbial risk assessment of ready-to-eat mixed vegetable salads from different restaurants of Bangladesh Agricultural University campus.

OBJECTIVE: The study was aimed to analyze the microbiological quality of mixed vegetable salads and to understand the risk related with its consumption from different restaurants around Bangladesh Agricultural University campus in Mymensingh. MATERIALS AND METHODS: Sixty (60) samples of mixed vegetable salads were taken from twelve (12) different restaurants in five different time points from each restaurant. In parallel, restaurant workers were asked for handling practices while the consumers were interviewed about their salad consumption pattern and whether they had experienced any health-related problems. Microbial risk assessment of Staphylococcus spp., Salmonella spp., and Escherichia coli was estimated by Monte Carlo simulation (10,000 iterations), an exponential model. RESULTS: Aerobic plate count was ranged from 7.73 ± 0.61 to 9.04 ± 0.26 log cfu/gm, Staphylococcus spp. from 4.64 ± 0.61 to 6.42 ± 0.53 log cfu/gm, Salmonella spp. from 4.75 ± 0.08 to 5.27 ± 0.53 log cfu/gm, and E. coli from 4.98 ± 0.20 to 6.66 ± 0.80 log cfu/gm. From the survey, it was found that total consumers had 18% chances where the male had 13% and the female had 30% chances of being infected with salads. Again frequent, average, and occasional consumers had 31%, 13%, and 0% chances, respectively, of being infected with those salads. From the Monte Carlo simulation, the calculated mean annual risks of Staphylococcus spp., Salmonella spp., and E. coli infection for the three exposure scenarios were found to be about 100%. CONCLUSION: The study actually revealed the potential microbial contamination in mixed vegetable salads which may impact on food safety and human health. So, the findings suggest that following hygienic measures during processing and handling the microbiological quality of mixed vegetables salads can be improved.