Static Headspace-Gas Chromatography Theory and Practice By Bruno Kolb (Bodenseewerk Perkin-Elmer GmbH) and Leslie S. Ettre (Yale University). Wiley−VCH:  New York. 1997. xx + 298 pp. $79.95. ISBN 0-471-19238-4.

1997 ◽  
Vol 119 (49) ◽  
pp. 12029-12029
Author(s):  
Richard D. Foust
Keyword(s):  
New York ◽  
Gas Chromatography ◽  
Theory And Practice ◽  
Headspace Gas Chromatography ◽  
Static Headspace ◽  
Yale University ◽  
Static Headspace Gas Chromatography ◽  
Headspace Gas

scholarly journals A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

2021 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Bahareh Sarmadi ◽  
Paul Kilmartin
Keyword(s):  
Gas Chromatography ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Aroma Compounds ◽  
Headspace Gas Chromatography ◽  
Static Headspace ◽  
Simultaneous Quantification ◽  
Static Headspace Gas Chromatography ◽  
Boltzmann Function ◽  
Headspace Gas

A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. Potential pitfalls that would cause inaccurate quantification i.e., effects of ethanol content and competitive ionization, were also discussed. The performance of the SHS-GC-IMS method was subsequently compared against a currently established method, namely, GC-MS, using actual wine samples. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.

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