为提高具有益生特性植物乳杆菌的产量,基于发酵动力学模拟,对其培养基组成、发酵条件和补料方式进行了优化。在该研究中,通过建立人工神经网络(artificial neural network,ANN)和遗传算法(genetic algorithm,GA)结合的智能模型对培养基成分进行优化,结果为碳源36.64 g/L(葡萄糖-麦芽糖质量比2∶3)、氮源47.83 g/L(酵母粉-蛋白胨质量比1∶1)、柠檬酸二铵33.27 g/L。发酵动力学采用Logistic和Luedeking-Piret模型,对植物乳杆菌的发酵过程进行拟合,菌体生长、底物消耗和产物生成动力学模型相关系数R2分别为0.995,0.998,0.993,表明这些模型能够精确的模拟植物乳杆菌的发酵过程。此外,对培养条件和分批补料进行了优化,最佳培养条件为温度35 ℃,初始pH值5.0,接种量4%。在分批添加中和剂NH3·H2O和葡萄糖30 g/L的情况下,菌体产量可达12.64 g/L。
To improve the production of Lactobacillus plantarum with probiotic properties, the medium composition, fermentation conditions and fed-batch method were optimized based on fermentation kinetic simulations. Firstly, the medium composition was optimized through single-factor experiments. Among the carbon sources studied, the results showed that maltose had the most significant effect in promoting the growth of the bacteria. Compared to glucose, maltose was more effective in promoting the growth of L. plantarum, probably due to the rapidly consumed of glucose by the bacteria to produce acid, lowering the pH of the medium and inhibiting its own growth. Considering the high cost of using maltose alone, glucose and maltose(mass ratio 2∶3) were chosen as the optimal carbon source. Among the nitrogen sources studied, organic nitrogen sources were significantly better than inorganic nitrogen sources, while the highest production of bacteria was achieved when yeast powder and peptone (mass ratio1∶1) was chosen as the nitrogen source. Compared with single nitrogen source, the peptone which had macromolecular peptide combined with the yeast powder significantly promoted the growth of L. plantarum.Different concentrations of hybrid carbon source and nitrogen source had an important effect on the growth of bacteria. The maximum production of bacteria was achieved when the concentration of hybrid carbon source and nitrogen source were 30 g/L and 25 g/L, respectively.The addition of buffer salts to the medium could balance the pH and reduce the inhibitory effect on the bacteria. In this study, different concentrations of the buffer salt system were investigated and the amount of bacteria initially increased with increasing buffer salt concentration but then decreased. When the concentration of diammonium citrate was 25 g/L, the medium buffer effect was the best.Subsequently, an intelligent model combining artificial neural network (ANN) and genetic algorithm (GA) was established to optimize the medium composition. By optimizing the artificial neural network structure, the results showed that the minimum mean square error was 0.009 1 when the number of neurons in the single hidden layer was nine. The minimum mean square error was 0.024 2 when the number of neurons in the double hidden layer was seven and nine. The single hidden layer model fitted the biomass better than the double hidden layer model, so the single hidden layer structure was used in this study. The neural network model was used as the fitness function of the genetic algorithm, and after 369 iterations,the results of medium optimization was obtained as follows (g/L): carbon source 36.64 (glucose-maltose mass ratio 2∶3), nitrogen source 47.83 (yeast powder-peptone mass ratio 1∶1) and ammonium citrate 33.27 . Meanwhile, the experimental value of biomass under the optimal conditions was 10.86 g/L, with an error value of less than 2%. The experimental values were in good agreement with the predicted values, indicating that the generated ANN-GA model has good predictive and optimization capabilities.Furthermore,Logistic and Luedeking-Piret models were used to fit the fermentation process of L. plantarum,the correlation coefficients R2 for the kinetic models of bacterial growth, substrate consumption and product generation were 0.995, 0.998 and 0.993 respectively, indicating that these models were able to accurately simulate the fermentation process of L. plantarum. Finally, the culture conditions and fed-batch were optimized.Under the optimized medium condition, the growth effect of L. plantarum was the best at 35 ℃.The bacteria had the highest biomass at pH 5.0 and growth was inhibited as the initial pH of the medium increased. The best growth was achieved at 4% inoculum. When the inoculum was 5%, the amount of biomass decreases, probably because the inoculum was too large and the nutrients in the medium were not sufficient for the simultaneous growth . Therefore, the optimum culture conditions were 35 ℃, initial pH 5.0, inoculum 4%. Fed-batch was one of the most commonly used methods to increase production efficiency in the fermentation industry. In the late exponential growth phase,the bacteria had a high demand for carbon sources, meanwhile provided additional carbon source to meet the growth needs of the bacteria and thus increase production. Neutralisers were usually used to prevent pH drops during fermentation, and NH3·H2O can significantly increase the density of bacteria in the culture broth. In this experiment, the effect of supplement with different concentrations of glucose on the biomass of lactic acid bacteria was investigated. Excessive glucose decreased the production of the bacteria, and the maximum biomass was achieved when glucose was supplemented to 30 g/L. The number of supplements was also optimized, with the increased in the number of supplements, the bacteria production gradually decreased and the maximum biomass was achieved with a single supplement. Thus, through supplied with glucose and NH3·H2O ,the biomass could reach 12.64 g/L, which was 19% higher than without supplement.
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