Dual Bioconversion Strategy: Synergistic Germination and Lactobacillus Fermentation Engineering for a γ-Aminobutyric Acid-Enriched Beverage from Brown Rice

Abstract

Growing demand for plant-based nutraceuticals drives the need for innovative bioprocessing strategies. This study developed an integrated approach combining germination and Lactobacillus-mediated fermentation to produce a γ-aminobutyric acid (GABA)-enriched functional beverage from brown rice. Systematic screening identified an optimal rice cultivar for germination. Sequential enzymatic liquefaction and saccharification were optimized to generate a suitable hydrolysate. Screening of 13 probiotic strains revealed that a 10-strain Lactobacillus-Bifidobacterium consortium maximized GABA synthesis (12.2 mg/100 g). Fermentation parameters were optimized to 0.25% monosodium glutamate, 4% inoculum, 10 μmol/L pyridoxine hydrochloride, 37 °C, and 24 h. The resulting beverage achieved significantly elevated GABA concentrations while exhibiting low fat (0.2 g/100 g), reduced caloric content (233.6 kJ/100 g), and high viable probiotic counts (2 × 10⁸ CFU/g). This strategy demonstrates significant potential for the scalable production of multifunctional, plant-based nutraceuticals with targeted bioactive components.

Keywords: Lactobacillus fermentation; beverage; germinated brown rice (GBR); germination; γ-aminobutyric acid (GABA).

Figure 1

Effects of liquefaction parameters on centrifugal sedimentation rate: (a) enzyme dosage, (b) time, and (c) temperature. Mean values with different letters (a, b, c, d) differ significantly (p < 0.05) by Duncan’s multiple range test. The letter ’a’ represents the group with the highest mean, followed by b, c, and d in decreasing order.

Figure 2

Effects of saccharification parameters on DE value: (a) enzyme dosage, (b) time, and (c) temperature. Mean values with different letters (a, b, c, d) differ significantly (p < 0.05) by Duncan’s multiple range test. The letter ’a’ represents the group with the highest mean, followed by b, c, and d in decreasing order.

Figure 3

GABA production by different multi-strain probiotics (A–M). Mean values with different letters differ significantly (p < 0.05) by Duncan’s multiple range test. The letter ’a’ represents the group with the highest mean, followed by b, c, d, e, f,g and h in decreasing order.

Figure 4

Effect of MSG on GABA content. Mean values with different letters (a, b, c, d) differ significantly (p < 0.05) by Duncan’s multiple range test. The letter ’a’ represents the group with the highest mean, followed by b, c, and d in decreasing order.

Figure 5

Effect of probiotic inoculum size on GABA content. Mean values with different letters differ significantly (p < 0.05) by Duncan’s multiple range test. The letter ’a’ represents the group with the highest mean, followed by b, c, d and e in decreasing order.

Figure 6

Temporal profiles of GABA content and pH during fermentation. Uppercase letters (A–E) and lowercase letters (a–e) indicate significant differences (p < 0.05) among means within their respective data groups by Duncan’s multiple range test. For each letter system, the letter ’A’ (or ’a’) denotes the highest mean value, followed by subsequent letters (B, C, D, E / b, c, d, e) in decreasing order. Letters are not comparable between the two systems.

Figure 7

Effect of pyridoxine hydrochloride concentration on GABA synthesis. Mean values with different letters differ significantly (p < 0.05) by Duncan’s multiple range test. The letter ’a’ represents the group with the highest mean, followed by b, c, d, e and f in decreasing order.