Multivariate Analysis of Key Taste Compounds in Soy Sauce and Model Construction for Its Saltiness Intensity

Saltiness is a key characteristic that influences the quality of soy sauce. Currently, the evaluation of saltiness intensity in soy sauce relies on sensory evaluation methods, while a scientific and efficient model to quantify saltiness is lacking. Liquid chromatography-mass spectrometry (LC-MS) and inductively coupled plasma-optical emission spectrometry (ICP-OES) were used to analyze key taste compounds in 10 soy sauce samples. According to sensory evaluation and taste addition experiments, the model for assessing the saltiness intensity of soy sauce was established. The results indicate that the umami amino acid (aspartic acid, 2.44~15.30 mg/mL; glutamic acid, 8.29~67.94 mg/mL) and the nucleotides 5'-inosinic acid (0.44~12.5 mg/mL) and 5'-guanylic acid (0.41~2.51 mg/mL) mainly contributed the saltiness intensity of soy sauce through umami synergy. Pyroglutamic acid (19.6~79.22 mg/mL) and lactic acid (0.77~0.85 mg/mL) are the primary taste-contributing organic acids to balance the taste profile in soy sauce. The Na<sup>+</sup> (54.6 mg/mL) and K<sup>+</sup> (8.13 mg/mL) contents are both relatively high, directly affecting the saltiness of the soy sauce. Through Spearman's correlation analysis, 11 key taste compounds were identified to construct a multiple linear regression prediction model for saltiness intensity. The model demonstrates excellent predictive performance, providing a theoretical basis and methodological support for objectively evaluating soy sauce saltiness and reducing salt content through a scientific approach.

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Publication Details

Journal
Foods
Published
2025-12-05
DOI
https://doi.org/10.3390/foods14244182
Primary Topic
Fermentation and Sensory Analysis
Type
article
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article

Multivariate Analysis of Key Taste Compounds in Soy Sauce and Model Construction for Its Saltiness Intensity

Shiyu Li, Lili Zhang, Li Liang, Yuyu Zhang et al.
Foods
Fermentation and Sensory Analysis
article

Multivariate Analysis of Key Taste Compounds in Soy Sauce and Model Construction for Its Saltiness Intensity

Shiyu Li, Lili Zhang, Li Liang, Yuyu Zhang, Jiacong Yin
article en

Abstract

Saltiness is a key characteristic that influences the quality of soy sauce. Currently, the evaluation of saltiness intensity in soy sauce relies on sensory evaluation methods, while a scientific and efficient model to quantify saltiness is lacking. Liquid chromatography-mass spectrometry (LC-MS) and inductively coupled plasma-optical emission spectrometry (ICP-OES) were used to analyze key taste compounds in 10 soy sauce samples. According to sensory evaluation and taste addition experiments, the model for assessing the saltiness intensity of soy sauce was established. The results indicate that the umami amino acid (aspartic acid, 2.44~15.30 mg/mL; glutamic acid, 8.29~67.94 mg/mL) and the nucleotides 5'-inosinic acid (0.44~12.5 mg/mL) and 5'-guanylic acid (0.41~2.51 mg/mL) mainly contributed the saltiness intensity of soy sauce through umami synergy. Pyroglutamic acid (19.6~79.22 mg/mL) and lactic acid (0.77~0.85 mg/mL) are the primary taste-contributing organic acids to balance the taste profile in soy sauce. The Na<sup>+</sup> (54.6 mg/mL) and K<sup>+</sup> (8.13 mg/mL) contents are both relatively high, directly affecting the saltiness of the soy sauce. Through Spearman's correlation analysis, 11 key taste compounds were identified to construct a multiple linear regression prediction model for saltiness intensity. The model demonstrates excellent predictive performance, providing a theoretical basis and methodological support for objectively evaluating soy sauce saltiness and reducing salt content through a scientific approach.

FoodsVol. 14(24)
Beijing Technology and Business University (CN)
Openalex Percentile: Top 56%
Fermentation and Sensory Analysis
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Multivariate Analysis of Key Taste Compounds in Soy Sauce and Model Construction for Its Saltiness Intensity — Shiyu Li, Lili Zhang, et al. · Foods (2025) | TGRS Research Map | TGRS