关键词: 脱脂牛乳；风味；顶空固相微萃取-全二维气相色谱-飞行时间质谱；偏最小二乘法判别分析

Abstract: In this study, headspace solid phase microextraction in combination with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (HS-SPME-GC × GC-TOFMS) was used to analyze the volatile compounds in whole (WM), low-fat milk (LFM) and non-fat milk (NFM). Altogether 49 volatile compounds were detected, among which methyl ketones with odd-numbered carbon chain lengths such as 2-nonanone and 2-undecanone constituted the main flavor compounds of WM. Using partial least squares discriminant analysis (PLS-DA), a model which could well differentiate among the 3 milks was developed and it was found to have good variance and cross-validation predictive ability. Nine differential key aroma compounds were identified using variable importance in the projection (VIP) > 1, P ≤ 0.05 and their contents ≥ 1% as criteria, which may be the main factors contributing to the differences in flavor profiles among the 3 milks. The heatmap from clustering analysis indicated that NFM had poor sensory performance due to the presence of off-flavor compounds (e.g., hexadecanal), whereas WM and LFM contained more aroma compounds, having a full and rich sensory aroma profile. The HS-SPME-GC × GC-TOFMS method can provide theoretical guidance for dairy flavor improvement and dairy flavoring formulation.

Key words: non-fat milk; flavor; headspace solid phase microextraction in combination with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry; partial least squares discriminant analysis