Optimization of a HS-SPME-GC-MS procedure for beer volatile profiling using response surface methodology: Application to follow aroma stability of beers under different storage conditions
The optimization of the main experimental variables, such as extraction temperature, volume of sample and the extraction time of an HS-SPME/GC-MS procedure, for profiling beer volatile analysis was evaluated using response surface methodology. A central composite circumscribed design was employed to study the effect of the experimental variables on the extraction of 28 representative volatile compounds of beer flavour profile. The parameters of the models were estimated by multiple linear regressions. The strongest influence in the volatile extraction yield was the volume of the sample (V) and the extraction temperature (T), with a positive and a negative effect, respectively. The performance characteristics of the optimised method were also determined, showing adequate linear ranges, repeatability, detection and quantification limits. The optimised methodology was applied to the same beer sample stored during 5 months at three different temperature conditions (4, 20 and 40 °C). Sampling was performed monthly, and the results showed that the concentration of most volatile compounds decreased during beer storage, although the rate of decrease was clearly higher at room temperature (20 °C) compared with refrigeration conditions (4 °C). Accelerated ageing conditions (40 °C) showed the most different volatile profile. Sensory analysis also revealed large differences in the overall quality of the samples, showing that even at room temperature the aroma profile of beer is greatly modified during its shelf life. © 2012 Springer Science+Business Media, LLC.
| Main Authors: | , , , |
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| Format: | artículo biblioteca |
| Published: |
Springer
2012
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| Subjects: | HS-SPME-GC-MS, Factorial design response surface methodology, Storage, Aroma, Beer, |
| Online Access: | http://hdl.handle.net/10261/101406 |
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| Summary: | The optimization of the main experimental variables, such as extraction temperature, volume of sample and the extraction time of an HS-SPME/GC-MS procedure, for profiling beer volatile analysis was evaluated using response surface methodology. A central composite circumscribed design was employed to study the effect of the experimental variables on the extraction of 28 representative volatile compounds of beer flavour profile. The parameters of the models were estimated by multiple linear regressions. The strongest influence in the volatile extraction yield was the volume of the sample (V) and the extraction temperature (T), with a positive and a negative effect, respectively. The performance characteristics of the optimised method were also determined, showing adequate linear ranges, repeatability, detection and quantification limits. The optimised methodology was applied to the same beer sample stored during 5 months at three different temperature conditions (4, 20 and 40 °C). Sampling was performed monthly, and the results showed that the concentration of most volatile compounds decreased during beer storage, although the rate of decrease was clearly higher at room temperature (20 °C) compared with refrigeration conditions (4 °C). Accelerated ageing conditions (40 °C) showed the most different volatile profile. Sensory analysis also revealed large differences in the overall quality of the samples, showing that even at room temperature the aroma profile of beer is greatly modified during its shelf life. © 2012 Springer Science+Business Media, LLC. |
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