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The cooked meat-like aroma compound, 2-methyl-3-furanthiol (2M3F), was detected in fermented soy sauce (FSS) by GC-olfactometry and GC-MS. 2M3F was present in FSS at a concentration considerably greater than the perception threshold, and the 2M3F concentration increased with heating temperature. Sensory analysis indicated that with the addition of only 0.2 μg/L of 2M3F to the soy sauce sample, the cooked meat-like aroma is significantly stronger than that of sample without the addition of 2M3F. Hence, 2M3F contributes to the cooked meat-like aroma of FSS, which constitutes the key aroma component of FSS. In addition, 2M3F was generated from the addition of ribose and cysteine in FSS by heating at 120 °C, but it was not detected in a phosphate buffer under the same condition. Furthermore, 2M3F was not detected in acid-hydrolyzed vegetable-protein-mixed soy sauce (ASS) and heated ASS. These results indicated that fermentation by micro-organisms facilitates the generation of 2M3F in FSS.

In order to clarify the aroma characteristics of raw soy sauce (RS), the application of gas chromatography−olfactometry analysis to the aroma concentrate from a RS revealed 76 aroma peaks, of which 25 peaks showed fruit-like aromas. Furthermore, the head space aromatic compounds of RS were analyzed with 32 peaks detected. Ethyl 2-methylpropanoate, ethyl butanoate, ethyl 2-methylbutanoate, ethyl 3-methylbutanoate, and ethyl 4-methylpentanoate were detected with higher flavor dilution factor (FD factor) than other aroma compounds by aroma extract dilution analysis. Quantitative analysis suggested that these compounds were common in all RS samples tested in this study, and were present at higher concentrations than their perception thresholds. The concentrations and the FD factors of these compounds were significantly decreased during the heating of the RS. Fruitiness is one of the key aroma characteristics of RS and the ethyl esters identified in this study are the key components contributing to this distinct aroma.

Characterizing the relationships between the components and taste differences among soy sauces can help evaluate and improve the quality of soy sauces. Although previous studies have reported that certain taste-active dipeptides, the relationships between taste differences and dipeptides of soy sauces are unknown. Therefore, our objective in this study was to investigate the correlations between the dipeptides and the taste differences among soy sauces. To analyze the dipeptides, we constructed an analytical method using liquid chromatography/tandem mass spectrometry (LC/MS/MS) in multiple reaction monitoring mode. Based on this method, we detected 237 dipeptides, the largest number ever detected in soy sauce research. Next, orthogonal projections to latent structures regressions were performed. The data matrix of components, including dipeptides and other low-molecular-weight hydrophilic components obtained from gas chromatography/mass spectrometry (GC/MS), served as explanatory variables (366 in total), whereas a sensory data matrix obtained using quantitative descriptive analysis served as the response variable. The accuracy of models for the sweetness and saltiness differences constructed using the LC/MS/MS and GC/MS data matrix were higher than did models constructed using only the GC/MS data matrix. As a result of investigation of the correlation between the dipeptides and taste differences among soy sauces by using variable importance in the projection (VIP) score, many dipeptides showed the high correlation with taste differences. Specifically, Ile-Gln, Pro-Lys, Ile-Glu, Thr-Phe, and Leu-Gln showed the high VIP score on sweet differences. This study is the first report that reveals the correlations between the dipeptides and taste differences among soy sauces.

複雑系（食品中）において，直接的な効果だけでなく，他の成分との相互効果も含めてヒトに認知される変化を誘起するために必要な最少の呈味成分の添加量（複雑系における閾値）を明らかにすることを目的として，醤油をモデルとした試験を行った．その結果，その過程において以下の知見を得た．（1） 醤油原液の評価におけるぶどう糖の閾値は1.8％，MSGの閾値は1.9％である．（2） 豆腐へのつけかけ評価における醤油中の閾値は，ぶどう糖8.9％，果糖ぶどう糖液糖8.3％（v/v），砂糖4.8％，みりん7.1％（v/v），MSG 3.9％，核酸0.03％である．複雑系に対する甘味成分や旨味成分の添加効果は対象となる系が有する成分とは異なると，また，その成分を構成する糖の種類が豊富であるほど大きくなり，閾値が低くなる可能性がある．（3） 醤油中における呈味成分の閾値，すなわち品質の差を認識させるために必要な呈味成分の添加量はその評価系によって異なる（豆腐へのつけかけにおけるぶどう糖の閾値は醤油原液での評価の4.9倍，MSGについては2.1倍）．したがって，呈味成分を添加した食品を開発する際には，その用途を勘案して品質の設計をする必要がある．

醤油および醤油関連調味料の評価を専門とした記述分析型パネルの採用を行った．採用においては，特に醤油に対する評価能力が高いパネルの選抜を目的として一般的な基準液を用いた試験の他に，醤油や醤油と共通する特性を有する食品を用いての評価を行った．その結果，その採用試験を通じて以下の知見を得た．（1）味のテスト : 配偶法によるテストは一般のパネル選抜試験と同様，閾値付近の濃度で行うことが望ましい．また，認知閾，認知閾の1/2，認知閾の1/4濃度に調製したスクロース，酢酸，グルタミン酸ナトリウム溶液を用いた甘味，酸味，旨味強度の識別テストは，パネルの選抜に有効である．醤油を用いた塩味の識別テストは食塩濃度8.2％，11.2％，14.2％が適切である．（2）香りのテスト : メーカーや原材料が異なる醤油を用いた香りの識別テストは，醤油に対する識別能力が高い被験者の選抜に有効である．また，加熱時間（2分，5分）が異なる醤油の識別テストもパネルのスクリーニングに適する．トリメチルアミンを添加して醤油の香りを識別テストにおける試薬の添加量は50ppm程度が妥当である．なお，香りの識別テストを複数回行う場合，評価間の休憩が1分間であれば，繰り返しは2回を上限とするべきである．（3）記述テスト : 醤油と同じ醸造物で数多くの成分を共有するワインを用いた記述力の試験は醤油を専門としたパネルの選抜に有効である．

Soy sauces, produced from different ingredients and brewing processes, have variations in components and quality. Therefore, it is extremely important to comprehend the relationship between components and the sensory attributes of soy sauces. The current study sought to perform metabolite profiling in order to devise a method of assessing the attributes of soy sauces. Quantitative descriptive analysis (QDA) data for 24 soy sauce samples were obtained from well selected sensory panelists. Metabolite profiles primarily concerning low-molecular-weight hydrophilic components were based on gas chromatography with time-of-flightmass spectrometry (GC/TOFMS). QDA data for soy sauces were accurately predicted by projection to latent structure (PLS), with metabolite profiles serving as explanatory variables and QDA data set serving as a response variable. Moreover, analysis of correlation between matrices of metabolite profiles and QDA data indicated contributing compounds that were highly correlated with QDA data. Especially, it was indicated that sugars are important components of the tastes of soy sauces. This new approach which combines metabolite profiling with QDA is applicable to analysis of sensory attributes of food as a result of the complex interaction between its components. This approach is effective to search important compounds that contribute to the attributes.