Effect of Corynebacterium glutamicum Fermentation on the Volatile Flavors of the Enzymatic Hydrolysate of Soybean Protein Isolate

Abstract

This study focused on improving the flavor quality of seasonings, and enzymatic hydrolysis of soybean protein isolate (SPI) seasoning via traditional technology may lead to undesirable flavors. Herein, we aimed to develop a new type of SPI seasoning through microbial fermentation to improve its flavor quality. The effect of Corynebacterium glutamicum fermentation on the flavoring compounds of seasonings in SPI enzymatic hydrolysate was examined. Sensory evaluation showed that the SPI seasoning had mainly aromatic and roasted flavor, and the response signals of S18 (aromatic compounds), S24 (alcohols and aldehydes), and S25 (esters and ketones) sensors of the electronic nose differed significantly. Overall, 91 volatile compounds were identified via gas chromatography-mass spectrometry. SPI seasonings contained a higher number of alcohols, ketones, aromatics, and heterocyclic compounds than traditional seasonings, which had stronger cheese, fatty, and roasted aromas. According to the relative odor activity value (ROAV) analysis, n-pentylpyrzine, 2,6-dimethylpyrazine, and tetramethylpyrazine are the key flavoring compounds (ROAV ≥ 1) of SPI seasoning, which may impart a unique roasted and meaty aroma. Therefore, the fermentation of SPI enzymatic hydrolysate with C. glutamicum may improve the flavor quality of its products, providing a new method for the development and production of new seasoning products.

Keywords: Corynebacterium glutamicum; fermentation; seasoning; soybean protein isolate; volatile flavoring compound.

Figure 1

Sensory evaluation and electronic nose analysis of seasoning samples (different letters indicate significant differences [p < 0.05]). (a) Sensory scoring radar map, (b) odor radar map of the response of the electronic nose sensor, and (c) correlation of odor with the electronic nose sensor response data (PC1 and PC2 were the directions with the largest and smallest differences, respectively).

Figure 2

(a) Types of volatile compounds in three seasoning samples. (b) Relative levels of volatile compounds in three seasoning samples.

Figure 3

(a) PCA-X diagram of different flavoring samples (red, blue, and green dots represent samples S, F, and SF, respectively). (b) Biplots of different flavor samples (green and orange dots represent volatile flavor substances and flavor samples, respectively). (c) Heatmap based on the relative content distribution of volatile flavor substances in different flavor samples (red and blue colors represent the high and low concentrations of volatile flavor substances, respectively; the higher the concentration of volatile flavor substances, the darker the color).

Figure 3

(a) PCA-X diagram of different flavoring samples (red, blue, and green dots represent samples S, F, and SF, respectively). (b) Biplots of different flavor samples (green and orange dots represent volatile flavor substances and flavor samples, respectively). (c) Heatmap based on the relative content distribution of volatile flavor substances in different flavor samples (red and blue colors represent the high and low concentrations of volatile flavor substances, respectively; the higher the concentration of volatile flavor substances, the darker the color).

Figure 4

(a) OPLS-DA regression projection of volatile compounds. (b) Validation via the permutation test. (c) VIP value calculated based on the OPLS-DA regression model.

Figure 5

(a) ROAV values of eight important volatile compounds. (b) Correlation graph between the electronic nose sensor and eight important volatile flavoring compounds.