International Journal of Advances in Scientific Research and Engineering-IJASRE

Pathogenic Microbes Growth Pattern Analysis in Staple Suya Meat Consumption Using the Bayesian Networks

Article Category: Computer Science and Information Engineering

DOI: 10.31695/IJASRE.2019.33146

Pages: 125-132

Author: Joe Essien

Abstract: Suya is a spicy meat skewer popular as a food item in the sub-Sahara regions. It is traditionally prepared by the Hausa people of northern Cameroon, Nigeria, Niger, Ghana, and some parts of Sudan. Suya is generally made with skewered beef, ram, chicken and innards such as kidney, liver and tripe. Being stable meat caviar for people of this region, prepared for consumption and in almost all cases, very unhygienic and sanitary conditions, the beef regalement is exposed massively to microbiome especially Escherichia coli (E. coli). Though most E.coli strains are harmless, some can cause serious food poisoning and severe disease. This paper aims to adopt the generality of Bayesian networks to represent and solve decision problems under uncertainty using influence diagrams from Bayesian taxonomies. It also investigates the application of Bayesian networks principles in making reliable predictions about the reoccurrence of microbe growths. Based on the analytical categorization, the research work builds on extant historical trends which establish referential patterns for microbiome growth in suya meat using Bayesian Networks as a formal model for characterizing and reasoning with uncertain information. Bayesian network models have proven useful in Decision Support Systems (DSS) and in many fields of Artificial Intelligence (AI) including medical domain diagnosis and weather forecasting. This research extends

Keyword: Bayesian Network, Microbiome, Decision Support Systems, Microbiology, Influence taxonomies

This work is licensed under a Creative Commons Attribution 4.0 (International) Licence. (CC BY-NC 4.0)
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