肉类研究2025，Vol.39Issue(5)：1-9,9.DOI:10.7506/rlyj1001-8123-20241021-275
基于人工神经网络耦联遗传算法优化肉葡萄球菌高密度培养基配方
Optimization of High-density Culture Medium for Staphylococcus carnosus Based on Artificial Neural Network-Genetic Algorithm
摘要
Abstract
This study aimed to achieve high-density culture of Staphylococcus carnosus for the purpose of preparing highly active starter cultures.Tryptic soy broth was used as the basal culture medium.Optimization of medium components was carried out using one-factor-at-a-time method and Box-Behnken design combined with response surface methodology(RSM).Meanwhile,an artificial neural network-genetic algorithm(ANN-GA)model was developed.The results indicated that the nitrogen source was the most significant factor influencing the viable count of S.carnosus.Compared with the RSM model,the ANN-GA model provided more accurate predictions with smaller prediction errors and superior optimization results.The optimal medium determined by the ANN-GA method was composed of 3.21 g/L glucose,20.17 g/L soy protein peptone,20.17 g/L beef extract powder,5.63 g/L dipotassium phosphate,5.0 g/L sodium chloride,and 0.2 g/L magnesium sulfate heptahydrate.In a 5 L fermentor,the maximum viable bacterial count reached 1.67×1010 CFU/mL.关键词
肉葡萄球菌/高密度培养基/响应面法/人工神经网络/遗传算法/优化Key words
Staphylococcus carnosus/high-density culture medium/response surface methodology/artificial neural network/genetic algorithm/optimization分类
轻工业引用本文复制引用
王仪,祝超智,白雪原,郑飏衣,张新军,仝林,赵改名..基于人工神经网络耦联遗传算法优化肉葡萄球菌高密度培养基配方[J].肉类研究,2025,39(5):1-9,9.基金项目
国家现代农业(肉牛牦牛)产业技术体系建设专项(CARS-37) （肉牛牦牛）
河北省现代农业产业技术体系肉牛产业创新团队建设项目(HBCT2023190204) （HBCT2023190204）
青海高海拔地区特色养殖业提质增效关键技术集成与示范项目(2022YFD1602300) （2022YFD1602300）
