Zong Lina, Qu Hengxian, Wang Wenqiong, Chen Dawei, Wa Yunchao, Huang Yujun, Gu Ruixia
College of Food Science and Engineering, Yangzhou University, Yangzhou 225127, China.
Key Laboratory of Probiotics and Deep Processing of Dairy Products, Yangzhou 225127, China.
Food Chem X. 2025 Jul 7;29:102750. doi: 10.1016/j.fochx.2025.102750. eCollection 2025 Jul.
This study integrated electronic nose (-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.
本研究将电子鼻与顶空固相微萃取-气相色谱-质谱联用,并结合气味活性值(OAV)分析,以表征发酵混合豆浆的风味特征。结果表明,电子鼻的雷达指纹图谱结合正交偏最小二乘判别分析(OPLS-DA)能够有效区分样品间的整体风味特征。气相色谱-质谱联用鉴定并定量了48种挥发性化合物,样品A、B和C中分别检测到35种、32种和32种。筛选出13种关键风味化合物(OAV>1),包括增香物质如1-辛醇、2,3-丁二酮和乙偶姻(OAV>150),以及异味贡献物质如己酸、1-己醇和癸醛。相关性网络分析表明,这些化合物的浓度变化直接导致了感官属性的差异。研究结果突出了气相色谱-质谱联用与电子感官技术在评估风味品质方面的有效性,并为表征和优化发酵豆浆风味特征提供了有价值的见解。