Chemical characterization of aromas in beer and their effect on consumers liking

摘要: Identification of volatiles in beer is important for consumers acceptability. In this study, triplicates 24 beers from three types fermentation (top/bottom/spontaneous) were analyzed using Gas Chromatograph with Mass-Selective Detector (GC-MSD) employing solid-phase microextraction (SPME). Principal components analysis was conducted each type fermentation. Multiple regression analysis, and an artificial neutral network model (ANN) developed the peak-areas 10 to evaluate/predict aroma, flavor overall liking. There no hops-derived bottom-fermentation beers, but they present top spontaneous. Top spontaneous had more than bottom-fermentation. 4-Ethyguaiacol trans-β-ionone positive towards Styrene a negative effect on An ANN high accuracy (R = 0.98) obtained predict The use SPME-GC-MSD effective method detect that contribute