There have been many attempts to develop sensitive and accurate techniques for the detection and diagnosis of pathogenic bacteria using nucleic acid-based technology. To achieve efficient multiple detection of seven selected food-borne pathogens, we assessed the respective 16S rDNA pathogen specific sequences using an oligonucleotide-based signature array. Strategic optimal design of specific capture probes was achieved by using the characteristic first variable region. To assess the specificity of this pathogen detection system, we employed a two-step experimental strategy. Under conditions established through experiments with chemically synthesized model targets comprising both conserved and variable regions of 16S rDNA, we confirmed the validity of this system using real 16S rDNA targets. Detection with real targets was successfully performed using our system, and better specificity was obtained compared to experiments with model targets. Moreover, the subtypes of Vibrio pathogens were successfully classified. We developed a two-dimensional visualization plot tool for positive control and specific spots, which allowed facile and minute differentiation between spot intensities. Repeated array formats were employed to ensure experimental uniformity, and included the statistical p-value criterion for pathogen discrimination. The present results thus indicate that our novel oligonucleotide-based signature chip detection system can be employed for the effective detection of multiple pathogens.