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SIFT-MS Application Note: Rapid Classification of Beer using Untargeted SIFT-MS Headspace Analysis

Anatune

16th March 2022

Automated SIFT-MS, Beer, Beer Analysis, SIFT-MS,


beer, types, volatiles, analysis

SIFT-MS Application Note – Rapid Classification of Beer using Untargeted SIFT-MS Headspace Analysis PART ONE

Authors: Vaughn S Langford (Principal Scientist, Syft Technologies), Diandree Padayachee (Product Manager, Syft Technologies), Mark J Perkins (Senior Applications Chemist, Anatune)

 

Automated headspace analysis using selected ion flow tube mass spectrometry (SIFT- MS) provides rapid and economic screening of food products, ingredients, and packaging materials.

This application note describes how SIFT-MS coupled with multivariate statistical analysis rapidly classifies beer products via an untargeted “fingerprinting” approach (i.e. utilising SIFT-MS SCAN mode).

Automated headspace SIFT-MS analysis can classify beer at throughputs of 12 samples per hour, offering great potential for rapid product screening.

Selected ion flow tube mass spectrometry (SIFT-MS) has been shown to provide powerful classification using an untargeted analytical approach coupled with multivariate statistical analysis for Argan and olive oils, strawberry flavour mixes, and Parmesan cheese. Therefore, in this application note a similar approach is utilised for classification of a variety of beer products – a more challenging matrix for direct mass spectrometry techniques because of the alcohol content (ca. 5%).

 

Part One Conclusions

This study demonstrates that untargeted automated SIFT- MS analysis, coupled with multivariate statistical analysis, can rapidly analyse and classify various beer products both individually and by type of beer.

The combined instrumental and statistical approach utilised here facilitates enhanced quality screening of beer with throughputs of 12 samples/hr achievable using currently available automation technology.

The untargeted approach to beer classification proves very effective when utilising automated SIFT-MS.

 

 

DOWNLOAD the SIFT-MS Application Note

SIFT-MS Headspace Beer Analysis Part One

 

 

beer, analysis, sift-ms

 

SIFT-MS Application Note – Rapid Classification of Beer with Automated Headspace Analysis using SIFT-MS PART TWO

Authors: Vaughn S Langford (Principal Scientist, Syft Technologies), Diandree Padayachee (Product Manager, Syft Technologies), Mark J Perkins (Senior Applications Chemist, Anatune)

 

Automated headspace analysis using selected ion flow tube mass spectrometry (SIFT- MS) provides rapid and economic screening of food products, ingredients, and packaging materials.

This application note describes how SIFT-MS coupled with multivariate statistical analysis rapidly classifies beer products by targeting well-known beer aroma compounds. Automated headspace-SIFT-MS analysis can classify beer at throughputs of 12 samples per hour, offering great potential for rapid product screening.

Coupled with multivariate statistical analysis, targeted analysis using selected ion flow tube mass spectrometry (SIFT- MS) has been demonstrated to effectively classify various food products, including Parmesan cheese, vanilla extracts of different origins, honey, beef, and milk powders. Therefore, this application note utilises a similar approach for classification of a variety of beer products according to type and product.

Beer is a moderately challenging matrix for direct mass spectrometry techniques because of the alcohol content (ca. 5%), but recently it has been demonstrated that headspace- SIFT-MS analysis of beer is feasible using an untargeted approach. Here, the approach employed is one that targets common beer aroma volatiles, yielding very effective classification of beer samples.

 

Part Two Conclusions

This study demonstrates that automated SIFT-MS analysis targeting important beer volatiles, coupled with multivariate statistical analysis, can rapidly classify various beer products both individually and by beer type.

The combined instrumental and statistical approach utilised here facilitates enhanced quality screening of beer with throughputs of 12 samples/hr achievable using currently available automation technology.

 

 

mark, perkins, anatune, vaughn, langford, syft,

Application Note Authors: Vaughn Langford of Syft Technologies & Anatune’s Mark Perkins

 

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