Abstract
A novel disposable all-printed electronic biosensor is proposed for a fast detection and classification of bacteria. This biosensor is applied to classify three types of popular pathogens: Salmonella typhimurium, and the Escherichia coli strains JM109 and DH5-α. The proposed sensor consists of inter-digital silver electrodes fabricated through an inkjet material printer and silver nanowires uniformly decorated on the electrodes through the electrohydrodynamic technique on a polyamide based polyethylene terephthalate substrate. The best sensitivity of the proposed sensor is achieved at 200 µm teeth spaces of the inter-digital electrodes along the density of the silver nanowires at 30 × 103/mm2. The biosensor operates on ±2.5 V and gives the impedance value against each bacteria type in 8 min after sample injection. The sample data are measured through an impedance analyzer and analyzed through pattern recognition methods such as linear discriminate analysis, maximum likelihood, and back propagation artificial neural network to classify each type of bacteria. A perfect classification and cross-validation is achieved by using the unique fingerprints extracted from the proposed biosensor through all the applied classifiers. The overall experimental results demonstrate that the proposed disposable all-printed biosensor is applicable for the rapid detection and classification of pathogens.
Highlights
A rapid and low-cost detection and classification of bacterial contamination is important information in many practical applications such as food industry[1,2]
We propose a novel impedance based biosensor that can detect three different types of bacteria, including Escherichia colistrains JM 109 and DH5-α, and Salmonella typhimurium
The pattern classification algorithms were used as linear maximum likelihood estimation (MLE), linear discrimination analysis (LDA), and non-linear back propagation neural network (BPNN) methods
Summary
A rapid and low-cost detection and classification of bacterial contamination is important information in many practical applications such as food industry[1,2]. We propose a novel impedance based biosensor that can detect three different types of bacteria, including Escherichia colistrains JM 109 and DH5-α, and Salmonella typhimurium We verify this biosensor’s capability by using the various machine learning algorithms to classify them. Salmonella usually can cause self-limiting gastrointestinal diseases, and can be transmitted through the ingestion of contaminated food or water These three bacteria organisms are quantitatively measured based on their impedance variation under the same conditions. In order to classify these bacteria, unique fingerprints, including the power, I-V curve, first, and second derivative of the I-V characteristics, were utilized to achieve 100% classification These results show that the proposed low cost and disposable all printed biosensor can be a good candidate for the rapid detection and classification of food pathogens
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