Department of Industrial Engineering, Faculty of Engineering and Natural Sciences, Osmaniye Korkut Ata University, Osmaniye, 80000, Turkey.
Department of Biology, Faculty of Engineering and Natural Sciences, Osmaniye Korkut Ata University, Osmaniye, 8000, Turkey.
BMC Biotechnol. 2024 Oct 29;24(1):83. doi: 10.1186/s12896-024-00914-w.
Optimizing extraction conditions can help maximize the efficiency and yield of the extraction process while minimizing negative impacts on the environment and human health. For the purpose of the current study, an artificial neural network (ANN) combined with a genetic algorithm (GA) was utilized for that the extraction conditions of Hypericum spectabile were optimized. In this particular investigation, the main objective was to get the highest possible levels of total antioxidant status (TAS) for the extracts that were obtained. In addition to this, conditions of the extract that exhibited the maximum activity have been determined and the biological activity of the extract that was obtained under these conditions was analyzed. TAS values were obtained from extracts obtained using extraction temperatures of 30-60 °C, extraction times of 4-10 h, and extract concentrations of 0.25-2 mg/mL. The best model selected from the established ANN models had a mean absolute percentage error (MAPE) value of 0.643%, a mean squared error (MSE) value of 0.004, and a correlation coefficient (R) value of 0.996, respectively. The genetic algorithm proposed optimal extraction conditions of an extraction temperature of 59.391 °C, an extraction time of 8.841 h, and an extraction concentration of 1.951 mg/mL. It was concluded that the integration of ANN-GA can successfully be used to optimize extraction parameters of Hypericum spectabile. The total antioxidant value of the extract obtained under optimum conditions was determined as 9.306 ± 0.080 mmol/L, total oxidant value as 13.065 ± 0.112 µmol/L, oxidative stress index as 0.140 ± 0.001. Total phenolic content (TPC) was 109.34 ± 1.29 mg/g, total flavonoid content (TFC) was measured as 148.34 ± 1.48 mg/g. Anti-AChE value was determined as 30.68 ± 0.77 µg/mL, anti-BChE value was determined as 41.30 ± 0.48 µg/mL. It was also observed that the extract exhibited strong antiproliferative activities depending on the increase in concentration. As a result of LC-MS/MS analysis of the extract produced under optimum conditions in terms of phenolic content. The presence of fumaric, gallic, protocatechuic, 4-hydroxybenzoic, caffeic, 2-hydoxycinamic acids, quercetin and kaempferol was detected. As a result, it was determined that the H. spectabile extract produced under optimum conditions had significant effects in terms of biological activity.
优化提取条件可以提高提取效率和产量,同时最大限度地减少对环境和人类健康的负面影响。本研究采用人工神经网络(ANN)结合遗传算法(GA)优化了贯叶连翘的提取条件。在本研究中,主要目的是获得提取物中总抗氧化状态(TAS)的最高水平。此外,还确定了提取物的最大活性条件,并分析了在此条件下获得的提取物的生物活性。TAS 值是从提取温度为 30-60°C、提取时间为 4-10 小时、提取浓度为 0.25-2mg/mL 的提取物中获得的。从建立的 ANN 模型中选择的最佳模型的平均绝对百分比误差(MAPE)值为 0.643%,均方误差(MSE)值为 0.004,相关系数(R)值为 0.996。遗传算法提出的最佳提取条件为提取温度 59.391°C、提取时间 8.841 小时和提取浓度 1.951mg/mL。结果表明,ANN-GA 的集成可以成功用于优化贯叶连翘的提取参数。最佳条件下提取物的总抗氧化值为 9.306±0.080mmol/L,总氧化剂值为 13.065±0.112µmol/L,氧化应激指数为 0.140±0.001。总酚含量(TPC)为 109.34±1.29mg/g,总黄酮含量(TFC)为 148.34±1.48mg/g。AChE 抑制值为 30.68±0.77µg/mL,BChE 抑制值为 41.30±0.48µg/mL。还观察到提取物的增殖活性随浓度的增加而增强。根据最佳条件下提取的酚含量进行 LC-MS/MS 分析,检测到富马酸、没食子酸、原儿茶酸、4-羟基苯甲酸、咖啡酸、2-羟基肉桂酸、槲皮素和山奈酚。因此,确定最佳条件下生产的贯叶连翘提取物在生物活性方面具有显著的作用。