Validation Study on the Simultaneous Quantitation of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry

Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Bahareh Sarmadi ◽  
Paul A. Kilmartin
2021 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Bahareh Sarmadi ◽  
Paul Kilmartin

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.


2020 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Paul Kilmartin

<div>In this paper, we report on the application of the static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS) instrument in the field of wine aroma analysis and its potential in constructing a prediction model for the quality gradings of wines. The easy-to-operate, cost effective SHS-GC-IMS instrument was innovatively used for a non-targeted search for volatile compounds in Sauvignon Blanc wine, with the identification of volatiles seldom before reported. The wine aroma profile acquired by the instrument was organically and innovatively combined with advanced classification models, inspired by the computer science community, to produce high classification accuracy in terms of wine quality gradings. Useful insights were also extracted by using advanced interpretation methods on complex models to learn the important volatiles correlated with wine quality grading.</div>


2021 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Paul Kilmartin

<p>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. A potential pitfall that would cause inaccurate quantification <i>i.e.</i>, competitive ionization, is also discussed. 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.</p>


2020 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Paul Kilmartin

<div>In this paper, we report on the application of the static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS) instrument in the field of wine aroma analysis and its potential in constructing a prediction model for the quality gradings of wines. The easy-to-operate, cost effective SHS-GC-IMS instrument was innovatively used for a non-targeted search for volatile compounds in Sauvignon Blanc wine, with the identification of volatiles seldom before reported. The wine aroma profile acquired by the instrument was organically and innovatively combined with advanced classification models, inspired by the computer science community, to produce high classification accuracy in terms of wine quality gradings. Useful insights were also extracted by using advanced interpretation methods on complex models to learn the important volatiles correlated with wine quality grading.</div>


2020 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Paul Kilmartin

<div>In this paper, we report on the application of the static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS) instrument in the field of wine aroma analysis and its potential in constructing a prediction model for the quality gradings of wines. The easy-to-operate, cost effective SHS-GC-IMS instrument was innovatively used for a non-targeted search for volatile compounds in Sauvignon Blanc wine, with the identification of volatiles seldom before reported. The wine aroma profile acquired by the instrument was organically and innovatively combined with advanced classification models, inspired by the computer science community, to produce high classification accuracy in terms of wine quality gradings. Useful insights were also extracted by using advanced interpretation methods on complex models to learn the important volatiles correlated with wine quality grading.</div>


2021 ◽  
Author(s):  
Wenyao Zhu ◽  
Frank Benkwitz ◽  
Paul Kilmartin

<p>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. A potential pitfall that would cause inaccurate quantification <i>i.e.</i>, competitive ionization, is also discussed. 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.</p>


2017 ◽  
Vol 409 (28) ◽  
pp. 6595-6603 ◽  
Author(s):  
Roman Rodríguez-Maecker ◽  
Eduardo Vyhmeister ◽  
Stefan Meisen ◽  
Antonio Rosales Martinez ◽  
Andriy Kuklya ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document