title: Automated analysis of food-borne pathogens using a novel microbial cell culture, sensing and classification system.
abstract: We hereby report the design and implementation of an Autonomous Microbial Cell Culture and Classification (AMC(3)) system for rapid detection of food pathogens. Traditional food testing methods require multistep procedures and long incubation period, and are thus prone to human error. AMC(3) introduces a "one click approach" to the detection and classification of pathogenic bacteria. Once the cultured materials are prepared, all operations are automatic. AMC(3) is an integrated sensor array platform in a microbial fuel cell system composed of a multi-potentiostat, an automated data collection system (Python program, Yocto Maxi-coupler electromechanical relay module) and a powerful classification program. The classification scheme consists of Probabilistic Neural Network (PNN), Support Vector Machines (SVM) and General Regression Neural Network (GRNN) oracle-based system. Differential Pulse Voltammetry (DPV) is performed on standard samples or unknown samples. Then, using preset feature extractions and quality control, accepted data are analyzed by the intelligent classification system. In a typical use, thirty-two extracted features were analyzed to correctly classify the following pathogens: Escherichia coli ATCC#25922, Escherichia coli ATCC#11775, and Staphylococcus epidermidis ATCC#12228. 85.4% accuracy range was recorded for unknown samples, and within a shorter time period than the industry standard of 24 hours.
authors.affiliation: Center for Advanced Sensors & Environmental Systems (CASE), Department of Chemistry, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA. osadik@binghamton.edu.
authors.forename: Kun
authors.initials: K
authors.lastname: Xiang
authors.affiliation: Department of Biomedical Engineering, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA.
authors.forename: Yinglei
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Biomedical Engineering, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA.
authors.forename: William
authors.initials: W
authors.lastname: Ford
authors.affiliation: Department of Biomedical Engineering, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA.
authors.forename: Walker
authors.initials: W
authors.lastname: Land
authors.affiliation: Department of Biomedical Engineering, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA.
authors.forename: J David
authors.initials: JD
authors.lastname: Schaffer
authors.affiliation: Center for Advanced Sensors & Environmental Systems (CASE), Department of Chemistry, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA. osadik@binghamton.edu.
authors.forename: Robert
authors.initials: R
authors.lastname: Congdon
authors.affiliation: Center for Advanced Sensors & Environmental Systems (CASE), Department of Chemistry, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA. osadik@binghamton.edu.
authors.forename: Jing
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Center for Advanced Sensors & Environmental Systems (CASE), Department of Chemistry, State University of New York at Binghamton, P.O Box 6000, Binghamton, NY 13902, USA. osadik@binghamton.edu.
authors.forename: Omowunmi
authors.initials: O
authors.lastname: Sadik
mesh_terms: D001185:Artificial Intelligence; D001331:Automation; D018929:Cell Culture Techniques / Q000379:methods*; D004563:Electrochemistry; D004926:Escherichia coli / Q000166:cytology* / Q000302:isolation & purification*; D005516:Food Microbiology; D006801:Humans; D016571:Neural Networks, Computer; D011786:Quality Control; D013212:Staphylococcus epidermidis / Q000166:cytology* / Q000302:isolation & purification*; D060388:Support Vector Machine