Bacterial contamination of Nigerian currency notes: A comparative analysis of different denominations recovered from local food vendors

Microbial transmission, on the surface of any currency note, can either be through direct (hand-to-hand contact) or indirect (food or other inanimate objects) means. To ascertain the degree of bacterial load enumerated during the handling of money and food items, particularly on currency note by denominations, should be of public health importance. Despite the available literature regarding microbial contamination of Nigerian currency notes, there is still paucity of information about how microbial contamination/load differ across the denominations specific to different food vendors. In this context, therefore, the current study investigated bacterial contamination of Nigerian currency notes via a comparative study of different denominations (₦1,000, ₦500, ₦200, ₦100, ₦50, ₦20, and 10, and ₦5) recovered from local food vendors. Specifically, the different food handlers/vendors included fruit, meat, vegetable, fish, and grain/cereal sellers. All emergent data from 8 × 5 factorial design of experiment were of duplicate measurements. To consider the currency denominations and food vendor type, a one-factor-at-a-time analysis of variance (ANOVA) was conducted. Results showed that about 81.7% of currency notes were contaminated with either Escherichia coli, Klebsiella spp. or Staphylococcus spp. in varying degrees. The higher denominations of ₦500, ₦200, and ₦100 note, with the exception of ₦1,000 note, recorded increased degree of contamination over the lower denominations of ₦50, ₦20, ₦10, and ₦5 note. Based on the total viable count (TVC), the ₦100 currency note appeared the most contaminated (1.32 × 10⁵ cfu/ml) whereas ₦5 note appeared the least contaminated (1.46 × 10⁴ cfu/ml). The frequency of isolated bacteria on currency notes from vegetable, meat, and fish sellers were significantly higher (p < 0.05) compared to other food vendors. The degree of bacterial contamination of the current work appears chiefly dependent on the food vendor type and currency denomination(s). This work calls for increased awareness and education among food vendors and ready-to-eat food sellers. Doing this would help mitigate the possible cross-contamination between currency notes and foodstuff. Through this, consumers would know more about the potential health risks such simultaneous activities (of handling currency notes and foodstuff) do pose on food safety.

Banknote recognition: investigating processing and cognition framework using competitive neural network

Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded. In a similar analogy, the robustness of intelligent systems to perform the task of banknote recognition should not collapse under some minimum level of partial occlusion. Artificial neural networks are intelligent systems which from inception have taken many important cues related to structure and learning rules from the human nervous/cognition processing system. Likewise, it has been shown that advances in artificial neural network simulations can help us understand the human nervous/cognition system even furthermore. In this paper, we investigate three cognition hypothetical frameworks to vision-based recognition of banknote denominations using competitive neural networks. In order to make the task more challenging and stress-test the investigated hypotheses, we also consider the recognition of occluded banknotes. The implemented hypothetical systems are tasked to perform fast recognition of banknotes with up to 75 % occlusion. The investigated hypothetical systems are trained on Nigeria's Naira banknotes and several experiments are performed to demonstrate the findings presented within this work.