Yang Bing, Wang Heng, Cao Zhenxia, Yan Jing, Dong Zijie, Ren Fazheng, Zhang Wanli, Chen Lishui
Food Laboratory of Zhong Yuan, Luohe 462300, China.
Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100193, China.
Foods. 2025 Mar 27;14(7):1178. doi: 10.3390/foods14071178.
The objective of this study was to assess and compare the characteristics of different soybean pastes by using intelligent sensory analysis. In this study, color, flavor, texture, and taste were regarded as four factors affecting the sensory quality of soybean pastes and the sensory quality of four different soybean pastes was evaluated using fuzzy mathematics. The sensory evaluation scores of samples L, Z, and W were very similar and significantly higher than that of sample Y. Gas chromatography-ion mobility spectrometry (GC-IMS) detected 111 volatile flavor compounds, with acids, alcohol, and ketones having a significantly higher relative content than other compounds, indicating their vital role in the flavor formation process of soybean pastes. Furthermore, partial least squares discriminant analysis (PLS-DA) model analysis identified 41 marker compounds that could differentiate the four types of soybean pastes. The overall odor and flavor profile were detected by the E-nose and E-tongue. These fundamental results lay the groundwork for future research on the similarities and differences between the flavor characteristics of different brands of soybean paste.
本研究的目的是通过智能感官分析评估和比较不同豆酱的特性。在本研究中，颜色、风味、质地和口感被视为影响豆酱感官品质的四个因素，并使用模糊数学对四种不同豆酱的感官品质进行评估。样品L、Z和W的感官评价得分非常相似，且显著高于样品Y。气相色谱-离子迁移谱（GC-IMS）检测到111种挥发性风味化合物，其中酸、醇和酮的相对含量显著高于其他化合物，表明它们在豆酱风味形成过程中起着重要作用。此外，偏最小二乘判别分析（PLS-DA）模型分析确定了41种能够区分四种豆酱的特征化合物。通过电子鼻和电子舌检测了整体气味和风味特征。这些基础结果为未来研究不同品牌豆酱风味特征之间的异同奠定了基础。
