Abstract

AbstractThe objective of this study was to conduct comprehensive aroma analyses of fermented soybean paste (doenjang) using descriptive sensory analysis and μ‐CTE–TD–GC–MS. Four doenjang samples were analyzed for its aroma using μ‐CTE–TD–GC–MS. Descriptive analysis was carried out with a highly trained panel (n = 6). A total of 38 volatile compounds were identified and significant differences in concentrations were noted especially between traditionally manufactured doenjang (S1) and commercially manufactured doenjang (S2–S4) samples. Authentically produced traditional doenjang samples (S1) characterized with meju, fish sauce, and roasted bean aromatics and these are previously reported as typical aromatics associated with traditional doenjang. Higher concentrations of Streker aldehydes and 3‐hydroxy‐2‐butanone, 2‐hydroxy‐3‐pentanone, and butanoic acid were exclusively found in S1. Commercially manufactured doenjang samples were characterized with high alcohol and fruity aromatics and volatile compounds in alcohol and ester compounds were found in higher concentration than S1. Addition of different flavor enhancer also influenced the aroma characteristics of commercially manufactured doenjang, which seems irrelevant to soybean fermentation.Practical applicationsThis study provides the most abundant list of sensory descriptors for traditional doenjang, which can be used as a baseline for doenjang aroma wheel. In addition, this study confirms the use of μ‐CTE–TD–GC–MS for volatile aroma analysis to provide same or superior extraction efficiency for volatile aroma analysis. Overall, this study confirms the aroma differences between “traditionally made” doenjang and “commercially made” doenjang. Interestingly commercial doenjang advertised as “traditionally made doenjang” had different aroma characteristics than authentic, traditionally made doenjang. Finding from current study can assist the doenjang industry to strategically designing the traditional doenjang aroma development targeting for different consumer segments.

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