Methodology for the bacteria detection in drinking water through an e-nose and e-tongue

Introduction— The evaluation of water quality remains a challenge for public health institutions today. One of the most abundant bacteria and the one that is mainly related with the sanitary risk of water is Escherichia coli (E. coli). The incidence of this bacteria shows that there is an increased risk of the presence of other bacteria and viruses of fecal origin, many of which are pathogenic. Nowadays, standardized and regulated conventional techniques are used for the detection of E. coli in water. These techniques require at least 24-28 hours of incubation for detection; in addition to require reagents and qualified personnel, among other requirements. Objective— This article presents an analysis of the ability of the sensory perception systems (e-nose and e-tongue) to determine and discriminate E. coli from other related bacteria in water samples. Methodology— To verify discrimination between bacteria, water samples contaminated with three bacteria were prepared: E. coli, Klebsiella oxytoca and Pseudomonas aeruginosa. Sterilized drinking water was used as a negative control. On the other hand, to evaluate the potential of the systems under study for the detection of E. coli in drinking water, water samples from the drinking water treatment plant (DWTP) of the municipality of Toledo (N. S) were analyzed. For this, the microbiological membrane filtration method was used as reference in this study. Results— The water samples discrimination was carried out through the Principal Components Analysis (PCA), reaching 97.6% of variance captured through the electronic nose. On the other hand, with the electronic tongue, the discrimination of the bacteria was 99.4% variation in the data set, obtaining a similar response with both methods. Conclusions— The results confirmed that the methodology allowed an effective evaluation between the contaminated samples and control samples. It is obtained a good discrimination of the categories for the samples acquired from the water treatment plant.

• Autores: Carrillo Gómez, Jeniffer Katerine; DURÁN ACEVEDO, CRISTHIAN MANUEL; Garcia-Rico, Ramon Ovidio
• Tipo de recurso: Article of journal
• Fecha de publicación: 2021
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/10300
• Acceso en línea: https://hdl.handle.net/11323/10300; https://repositorio.cuc.edu.co/
• Palabra clave: E. coli; Drinking water; Electronic nose; Electronic tongue; Data processing; Lengua electrónica; Procesamiento de datos; Agua potable; Nariz electrónica
• Rights: openAccess
• License: Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)