Yang Menglu, Huang Jun, Zhou Rongqing, Qi Qi, Peng Can, Zhang Lin, Jin Yao, Wu Chongde, Tang Qiuxiang
College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China.
College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China; Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu 610065, China.
Food Res Int. 2020 Dec;138(Pt A):109753. doi: 10.1016/j.foodres.2020.109753. Epub 2020 Oct 2.
In the present research, four different samples were investigated by multiple analyzing technology to reveal the common unique flavor and taste of traditional Pixian Doubanjiang (PXDBJ). These samples were manufactured by inheritor according to the intangible skills and ripened for two years in different enterprises. Citric acid, malic acid, Glu and Asp were the dominant non-volatiles, the proportion of both organic acids ranged from 54.78% to 65.61%, while that of both free amino acids ranged from 22.49% to 29.39%. Ethyl palmitate, ethyl laurate, γ-cis-himachalane, (+)-valencene and β-ionone were identified as typical volatile constituents by three kinds of GC techniques combined with three pretreatment approaches. These results suggested that these five volatiles and the proportion of four non-volatiles could be used as indicators of flavor and taste to discriminate with other types of traditional fermented soy pastes (miso, dajiang, gochujiang, etc), and were also proofed by sensory evaluation. It laid a vital foundation for revealing the contribution of the traditional skill to unique quality of PXDBJ and the correlation between microbial community diversity and their metabolic regulation.
在本研究中，通过多种分析技术对四个不同样本进行了研究，以揭示传统郫县豆瓣酱（PXDBJ）独特的风味和口感。这些样本由传承人按照非物质技艺制作，并在不同企业中陈酿两年。柠檬酸、苹果酸、谷氨酸和天冬氨酸是主要的非挥发性成分，两种有机酸的比例在54.78%至65.61%之间，而两种游离氨基酸的比例在22.49%至29.39%之间。通过三种气相色谱技术与三种预处理方法相结合，鉴定出棕榈酸乙酯、月桂酸乙酯、γ-顺式喜马拉雅烷、（+）-瓦伦烯和β-紫罗兰酮为典型挥发性成分。这些结果表明，这五种挥发性成分和四种非挥发性成分的比例可作为风味和口感指标，用于区分其他类型的传统发酵豆酱（味噌、大酱、韩式辣椒酱等），感官评价也证实了这一点。这为揭示传统技艺对郫县豆瓣酱独特品质的贡献以及微生物群落多样性与其代谢调控之间的相关性奠定了重要基础。
