The Feasibility of Using Pyrolysis-Mass Spectrometry and Pyrolysis-MS/MS with Pattern Recognition for the Identification of Biological Materials.

Abstract

A series of experiments are reported which examined the susceptibility of the pyrolysis-mass spectroscopy (Py-MS) method in identifying bacteria which had been subjected to changes in growing time, killing method and diversity in the data set. In spite of these complications, Py-MS with pattern recognition techniques was successful where the number of bacteria in the data set was less than 16. The results from a large data set, containing 47 bacteria indicated that the number of samples exceeded the capabilities of the pattern recognition technique. Experiments using Py-MS/MS showed that this technique could provide enough selectivity to overcome the pattern recognition problems in large sample groups. Analyses were conducted on mixtures containing bacteria in a background which might be found on a battlefield. The complexity of the mixture and the level of the bacteria seriously affected the ability to identify the bacteria. Py-MS/MS with pattern recognition techniques will probably be necessary for future development of the technique.

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Document Details

Document Type
Technical Report
Publication Date
Jan 07, 1987
Accession Number
ADA176672

Entities

People

  • Kent J. Voorhees
  • Steven L. Durfee

Organizations

  • Colorado School of Mines

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Alcohols
  • Bacteria
  • Chemistry
  • Curie Temperature
  • Data Analysis
  • Data Sets
  • Fungi
  • Identification
  • Jet Propulsion
  • Mass Spectra
  • Mass Spectrometers
  • Mass Spectrometry
  • Materials
  • Microorganisms
  • Pattern Recognition
  • Recognition
  • Spectrometry

Readers

  • Computer Vision.
  • Gulf War Illness and Chronic Multisymptom Illness in Veterans.
  • Systems Analysis and Design

Technology Areas

  • AI & ML