Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractInhibition of plant pathogenic fungi by endophytic Trichoderma spp. through mycoparasitism and volatile organic compounds    Next AbstractAn environmental air sampler to evaluate personal exposure to volatile organic compounds »

Anal Methods


Title:Automated chemical identification and library building using dispersion plots for differential mobility spectrometry
Author(s):Rajapakse MY; Borras E; Yeap D; Peirano DJ; Kenyon NJ; Davis CE;
Address:"Mechanical and Aerospace Engineering, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA. Department of Internal Medicine, 4150 V Street, Suite 3400, University of California, Davis, Sacramento, CA 95817, USA. Center for Comparative Respiratory Biology and Medicine, University of California, Davis, CA 95616, USA"
Journal Title:Anal Methods
Year:2018
Volume:20180814
Issue:35
Page Number:4339 - 4349
DOI: 10.1039/C8AY00846A
ISSN/ISBN:1759-9660 (Print) 1759-9679 (Electronic) 1759-9660 (Linking)
Abstract:"Differential mobility spectrometry (DMS) based detectors require rapid data analysis capabilities, embedded into the devices to achieve the optimum detection capabiites as portable trace chemical detectors. Automated algorithm-based DMS dispersion plot data analysis method was applied for the first time to pre-process and separate 3-dimentional (3-D) DMS dispersion data. We previously demonstrated our AnalyzeIMS (AIMS) software was capable of analyzing complex gas chromatography differential mobility spectrometry (GC-DMS) data sets. In our present work, the AIMS software was able to easliy separate DMS dispersion data sets of five chemicals that are important in detection of volatile organic compounds (VOCs): 2-butanone, 2-propanone, ethyl acetate, methanol and ethanol. Identification of chemicals from mixtures, separation of chemicals from a mixture and prediction capability of the software were all tested. These automated algorithms may have potential applications in separation of chemicals (or ion peaks) from other 3-D data obtained by hybrid analytical devices such as mass spectrometry (MS). New algorithm developments are included as future considerations to improve the current numerical approaches to fingerprint chemicals (ions) from a significantly complicated dispersion plot. Comprehensive peak identifcation by DMS-MS, variations of the DMS data due to chemical concentration, gas phase ion chemistry, temperature and pressure of the drift gas are considered in future algorithm improvements"
Keywords:
Notes:"PubMed-not-MEDLINERajapakse, Maneeshin Y Borras, Eva Yeap, Danny Peirano, Daniel J Kenyon, Nicholas J Davis, Cristina E eng U01 EB022003/EB/NIBIB NIH HHS/ UG3 OD023365/OD/NIH HHS/ UL1 TR000002/TR/NCATS NIH HHS/ UH3 OD023365/OD/NIH HHS/ UL1 TR001860/TR/NCATS NIH HHS/ P30 ES023513/ES/NIEHS NIH HHS/ England 2019/04/16 Anal Methods. 2018 Sep 21; 10(35):4339-4349. doi: 10.1039/C8AY00846A. Epub 2018 Aug 14"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 21-09-2024