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Investigates gamma-PGA production in black soybean waste, suggesting a sustainable approach.
Gamma-Poly Glutamic Acid (γ-PGA) is an eco-friendly biopolymer that is biodegradable and water soluble and has been used in different industries such as foods, pharmaceuticals, agriculture, and environment. Unlike other artificial polymers, γ-PGA is a natural polymer that can be obtained through microbial fermentation. Various strains have been employed to obtain the desired polymer but Bacillus subtilis has been the most common one studied so far. In the current study, the possibility of using soybean extracts to produce γ-PGA in both solid state fermentation and submerged state fermentation was examined. Of all the strains, white and black soybeans yielded the highest amount in SSF and SBF respectively at 347.67 mg (1.390%) and 935 mg (3.116%). To eliminate concerns regarding external glutamate addition, only a trace amount of monosodium glutamate (MSG) was used in the seed culture, and no glutamate was added during fermentation, indicating that γ-PGA was produced predominantly through production without external glutamate supplementation during fermentation. The initial screening showed that black soybean waste could be used as an inexpensive substrate for optimization via SBF. A Central Composite Design (CCD) design with four factors and five levels, with response surface methodology consisting of 30 different experiments, was conducted to determine the influence of the substrate concentration, pH, temperature, and inoculum amount. The optimized parameters for the maximum γ-PGA production, namely 6% substrate, pH of 6.0, 35 °C temperature, and 3% inoculum, resulted in γ-PGA production equaling 7.5 g/L, which is close to the predicted value of 7.48 g/L. The study highlights that substrate selection and statistical optimization are equally critical for enhancing γ-PGA production, positioning black soybean waste as a promising low-cost substrate with potential for future scale-up and sustainable γ-PGA bioprocess development following further pilot-scale and techno-economic validation.
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Rajput et al. (2026) studied this question.
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