GC/IR computer-aided identification of anaerobic bacteria

Hunian Ye; Feng Sheng Zhang; Hua Yang; Zhu Li; Song Ye

doi:10.1117/12.156498

22 September 1993 GC/IR computer-aided identification of anaerobic bacteria

Hunian Ye, Feng Sheng Zhang, Hua Yang, Zhu Li, Song Ye

Proceedings Volume 2101, Measurement Technology and Intelligent Instruments; (1993) https://doi.org/10.1117/12.156498
Event: Measurement Technology and Intelligent Instruments, 1993, Wuhan, China

Abstract

A new method was developed to identify anaerobic bacteria by using pattern recognition. The method is depended on GC / JR data. The system is intended for use as a precise rapid and reproduceable aid in the identification of unknown isolates. Key Words: Anaerobic bacteria Pattern recognition Computeraided identification GC / JR 1 . TNTRODUCTTON A major problem in the field of anaerobic bacteriology is the difficulty in accurately precisely and rapidly identifying unknown isolates. Tn the proceedings of the Third International Symposium on Rapid Methods and Automation in Microbiology C. M. Moss said: " Chromatographic analysis is a new future for clinical microbiology" . 12 years past and so far it seems that this is an idea whose time has not get come but it close. Now two major advances that have brought the technology forword in terms ofmaking it appropriate for use in the clinical laboratory can aldo be cited. One is the development and implementation of fused silica capillary columns. In contrast to packed columns and those of'' greater width these columns allow reproducible recovery of hydroxey fatty acids with the same carbon chain length. The second advance is the efficient data processing afforded by modern microcomputer systems. On the other hand the practical steps for sample preparation also are an advance in the clinical laboratory. Chromatographic Analysis means mainly of analysis of fatty acids. The most common

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Hunian Ye, Feng Sheng Zhang, Hua Yang, Zhu Li, and Song Ye "GC/IR computer-aided identification of anaerobic bacteria", Proc. SPIE 2101, Measurement Technology and Intelligent Instruments, (22 September 1993); https://doi.org/10.1117/12.156498

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KEYWORDS

Infrared radiation

Absorbance

Biological research

Bacteria

Absorption

Pattern recognition

Statistical analysis

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