A novel chromatographic-sensory-spectral method combined with multivariate algorithms for the identification of...

Trionycis Carapax is a commonly used health food, often consumed after processing. Its quality varies considerably depending on the degree of processing. This study constructed a comprehensive analysis framework combining multiple techniques to accurately distinguish different processing levels. The relationships between dynamic changes in amino acids, the Maillard reaction, and protein hydrolysis during processing were elucidated. Surface color parameters a∗ (back) and b∗ (front/back), and powder color parameters b∗ and L∗, were identified as key differentiation indices. An electronic nose (E-nose) was used to distinguish raw from processed products. Using near-infrared (NIR) spectroscopy combined with a normalization pretreatment method, different processing degrees of Trionycis Carapax were effectively distinguished. Fusion analysis revealed dynamic correlations between color and chemical composition. A backpropagation (BP) neural network model achieved a high discrimination rate of 91.7 %. These findings provide a valuable reference for quality control and digital transformation during food processing.