风味
感觉系统
食品科学
发酵
感官分析
钥匙(锁)
化学
气相色谱-质谱法
计算机科学
心理学
色谱法
质谱法
认知心理学
计算机安全
作者
Lina Zong,Hengxian Qu,Wen-Qiong Wang,Dawei Chen,Yunchao Wa,Yujun Huang,Ruixia Gu
标识
DOI:10.1016/j.fochx.2025.102750
摘要
-nose) and HS-SPME-GC-MS with odor activity value (OAV) analysis to characterize flavor profiles of fermented mixed soymilk. The results showed that radar fingerprint profiles of the electronic nose combined with orthogonal partial least squares-discriminant analysis (OPLS-DA) can effectively distinguish the overall flavor profiles among samples. GC-MS identified and quantified 48 volatile compounds, with 35, 32, and 32 detected in samples A, B, and C, respectively. Thirteen key flavor compounds (OAV >1) were screened out, including aroma-enhancing substances such as 1-octanol, 2,3-butanedione, and acetoin (OAV >150), as well as off-flavor contributors like hexanoic acid, 1-hexanol, and decanal. Correlation network analysis indicated that concentration variations of these compounds directly drove the divergence in sensory attributes. The findings highlight the efficacy of GC-MS combined with electronic sensory technologies in evaluating flavor quality and provide valuable insights for characterizing and optimizing fermented soymilk flavor profiles.
科研通智能强力驱动
Strongly Powered by AbleSci AI