TY - GEN
T1 - Algorithm for Automatic Peak Detection and Quantification for GC-IMS Spectra
AU - Fernandes, Jorge M.
AU - Vassilenko, Valentina
AU - Santos, Paulo H.
N1 - The authors would like to thank the Funda??o para a Ci?ncia e Tecnologia (FCT, Portugal) and NMT, S.A. for co-financing the PhD grants PD/BDE/114550/2016 and PD/BDE/130204/2017 of the Doctoral NOVA I4H Program.
PY - 2020
Y1 - 2020
N2 - Ion Mobility Spectrometry with a coupled Gas Chromatography (GC-IMS) pre-separation is an analytical technique suitable for detection of volatile organic compounds (VOCs) in complex sample matrices (indoor & outdoor air, breath samples, food, beverages, microbial cultures, etc.). Its outstanding sensitivity allows in-situ analysis of a very large range of organic compounds at low concentrations with detection limits typically in the low ppb or even ppt level. Automatic detection and quantification of VOCs through GC-IMS spectra is challenging and the lack of computational methodologies able to detect, quantify and deconvolute overlapped peaks are still scarce and diminished. In this work we present a preliminary algorithm and still in development for automatically identify and quantify VOC peaks directly from the spectra matrix with an established threshold, a noise filter, Reactive Ion Peak (RIP) measurements. Herein, proposed tools may be very useful for quick automatic detection and quantification of compounds in GC-IMS spectra.
AB - Ion Mobility Spectrometry with a coupled Gas Chromatography (GC-IMS) pre-separation is an analytical technique suitable for detection of volatile organic compounds (VOCs) in complex sample matrices (indoor & outdoor air, breath samples, food, beverages, microbial cultures, etc.). Its outstanding sensitivity allows in-situ analysis of a very large range of organic compounds at low concentrations with detection limits typically in the low ppb or even ppt level. Automatic detection and quantification of VOCs through GC-IMS spectra is challenging and the lack of computational methodologies able to detect, quantify and deconvolute overlapped peaks are still scarce and diminished. In this work we present a preliminary algorithm and still in development for automatically identify and quantify VOC peaks directly from the spectra matrix with an established threshold, a noise filter, Reactive Ion Peak (RIP) measurements. Herein, proposed tools may be very useful for quick automatic detection and quantification of compounds in GC-IMS spectra.
KW - Algorithm
KW - Automation
KW - Gas Chromatography (GC)
KW - Ion Mobility Spectrometry (IMS)
KW - Peak detection
KW - Quantification
KW - Volatile Organic Compounds (VOCs)
UR - http://www.scopus.com/inward/record.url?scp=85084839442&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-45124-0_35
DO - 10.1007/978-3-030-45124-0_35
M3 - Conference contribution
AN - SCOPUS:85084839442
SN - 978-3-030-45123-3
T3 - IFIP Advances in Information and Communication Technology
SP - 369
EP - 377
BT - Technological Innovation for Life Improvement - 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, Proceedings
A2 - Camarinha-Matos, Luis M.
A2 - Farhadi, Nastaran
A2 - Lopes, Fábio
A2 - Pereira, Helena
PB - Springer
CY - Cham
T2 - 11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020
Y2 - 1 July 2020 through 3 July 2020
ER -