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

Area of Science:

• Food Science
• Analytical Chemistry
• Sensory Science

Background:

• Soy sauce quality is significantly influenced by saltiness.
• Current saltiness evaluation relies on subjective sensory methods.
• A scientific, objective model for quantifying soy sauce saltiness is needed.

Purpose of the Study:

• To develop and validate a scientific model for quantifying soy sauce saltiness intensity.
• To identify key taste compounds contributing to soy sauce saltiness.
• To provide a method for objective saltiness evaluation and potential salt reduction.

Main Methods:

• Analysis of 10 soy sauce samples using Liquid Chromatography-Mass Spectrometry (LC-MS) and Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES).
• Sensory evaluation and taste addition experiments to correlate chemical composition with perceived saltiness.
• Spearman's correlation analysis to identify key taste compounds.
• Construction of a multiple linear regression prediction model for saltiness intensity.

Main Results:

• Umami amino acids (aspartic acid, glutamic acid) and nucleotides (5'-inosinic acid, 5'-guanylic acid) contribute to saltiness via umami synergy.
• Pyroglutamic acid and lactic acid act as primary organic acids balancing soy sauce taste.
• High concentrations of sodium (Na+) and potassium (K+) directly impact saltiness.
• A predictive model using 11 key taste compounds demonstrated excellent performance.

Conclusions:

• A robust, scientifically validated model for soy sauce saltiness intensity has been established.
• The model identifies key chemical contributors to saltiness, including amino acids, nucleotides, and ions.
• This research offers a theoretical basis and practical method for objective soy sauce saltiness assessment and salt reduction efforts.