Applications of electronic-nose technologies for noninvasive early detection of plant, animal and human diseases

Abstract

The development of electronic-nose (e-nose) technologies for disease diagnostics was initiated in the biomedical field for detection of biotic (microbial) causes of human diseases during the mid-1980s. The use of e-nose devices for disease-diagnostic applications subsequently was extended to plant and animal hosts through the invention of new gas-sensing instrument types and disease-detection methods with sensor arrays developed and adapted for additional host types and chemical classes of volatile organic compounds (VOCs) closely associated with individual diseases. Considerable progress in animal disease detection using e-noses in combination with metabolomics has been accomplished in the field of veterinary medicine with new important discoveries of biomarker metabolites and aroma profiles for major infectious diseases of livestock, wildlife, and fish from both terrestrial and aquaculture pathology research. Progress in the discovery of new e-nose technologies developed for biomedical applications has exploded with new information and methods for diagnostic sampling and disease detection, identification of key chemical disease biomarkers, improvements in sensor designs, algorithms for discriminant analysis, and greater, more widespread testing of efficacy in clinical trials. This review summarizes progressive advancements in utilizing these specialized gas-sensing devices for numerous diagnostic applications involving noninvasive early detections of plant, animal, and human diseases.

  • Citation: Wilson, A.D. 2018. Applications of electronic-nose technologies for noninvasive early detection of plant, animal and human diseases. Chemosensors. 6(10): 45.
  • Keywords: bat white-nose syndrome, diagnostic pathology, disease biomarker metabolites, electronic aroma detection, e-nose, early disease diagnosis, human diseases
  • Posted Date: December 13, 2018
  • Modified Date: February 11, 2019
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