Characterization of Pigmented Microbial Isolates for Use in Material Applications

Abstract

Organisms (i.e., plants and microorganisms) contain pigments that allow them to adapt and thrive under stressful conditions, such as elevated ultraviolet radiation. The pigments elicit characteristic spectral responses when measured by active and passive sensors. This research study focused on characterizing the spectral response of three organisms and how they compared to background spectral signatures of a complex environment. Specifically, spectra were collected from a fungus, a plant, and two pigmented bacteria, one of which is an extremophile bacterium. The samples were measured using Fourier transform infrared spectroscopy and dis-criminated using chemometric means. A top-down examination of the spectral data revealed that organisms could be discriminated from one an-other through principal component analysis (PCA). Furthermore, there was a strong distinction between the plant and the pigmented microorganisms. Spectral differences resulting in samples with the highest variance from the natural background were identified using PCA loading plots. The outcome of this work is a spectral library of pigmented biological candidates for coatings applications.

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Document Details

Document Type
Technical Report
Publication Date
Mar 21, 2023
Accession Number
AD1196470

Entities

People

  • Alison K. Thurston
  • Dane N. Wedgeworth
  • Elizabeth J. Corriveau
  • Hayden A. Hanna
  • Mine G. Ucak-astarlioglu
  • Robert M. Jones
  • Robyn A. Barbato
  • Travis L. Thornell

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Biomedical
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Antifreeze Proteins
  • Bacteria
  • Chemical Elements
  • Chemical Synthesis
  • Chemistry
  • Cold Regions
  • Detectors
  • Electromagnetic Radiation
  • Engineering
  • Engineers
  • Environment
  • Infrared Spectroscopy
  • Microorganisms
  • Passive Sensors
  • Remote Sensing
  • Spectra
  • Spectroscopy
  • Statistical Analysis

Readers

  • Microbial Pathology
  • Regression Analysis.
  • Spectroscopy.

Technology Areas

  • Biotechnology