从刺蒺藜中超声辅助提取富含原薯蓣皂甙提取物的 ANN 建模和 RSM 优化研究

IF 8.7 1区化学 Q1 ACOUSTICS

Ultrasonics Sonochemistry Pub Date : 2024-11-07 DOI:10.1016/j.ultsonch.2024.107141

Stefan Kuvendziev, Isidora Dimitrievska, Martin Stojchevski, Mirko Marinkovski

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引用次数: 0

摘要

刺蒺藜是一种草本植物，以其丰富的皂苷、黄酮和生物碱而闻名，可用于治疗各种健康问题。原薯蓣皂苷能促进睾酮转化为强效的双氢睾酮，刺激性欲增强、骨髓红细胞生成和肌肉发育。我们选择了采用绿色萃取溶剂的现代超声辅助萃取（UAE）工艺来设计所需的分离系统。实验计划是根据独立的操作变量--萃取时间、操作温度和溶剂系统成分--制定的，目的是确定确定的参数及其相互作用对萃取率和原薯蓣皂苷存在的影响。采用 3D-RSM 方法确定了所研究的自变量在最大萃取率范围内的最佳值。在最佳操作条件下进行的 UAE 过程产生了最高提取率（31%，w/w）和 5.9 mg/g 干植物基质的原薯蓣皂苷含量。实验数据被用来为确定的提取系统开发一个 ANN，将操作变量值作为输入矩阵，将观察到的产量作为目标矩阵。成功设计和训练的 ANN 在观测数据和预测模型输出之间产生了较高的相关性（r = 0.9992），MSE 值为 0.29107。

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ANN modeling and RSM optimization of ultrasound-assisted extraction of protodioscin-rich extracts from Tribulus terrestris L.

Tribulus terrestris L. is a herb renowned for its abundance of saponins, flavonoids, and alkaloids, which are utilized in treating various health conditions. Protodioscin functions by enhancing the conversion of testosterone into potent dihydrotestosterone, stimulating an increase in libido, red blood cell production from the bone marrow, and muscle development. Contemporary ultrasound-assisted-extraction (UAE) process employing green extraction solvents was selected to design the required separation system. The experimental plan was developed based on the independent operating variables – extraction time, operating temperature and solvent system composition in order to determine the influence of defined parameters and their interactions on the extraction yield and the presence of protodioscin. The 3D-RSM approach was introduced to determine the optimal values of studied independent variables in the area of maximal extraction yield. UAE process performed at optimal operating conditions generated maximal extraction yield (31 %, w/w) and protodioscin content of 5.9 mg/g dry plant matrix. Experimental data was used to develop an ANN for the defined extraction system using the operating variables values as the input matrix and observed yield as target matrix. Successfully designed and trained ANN generated high correlation (r = 0.9992) between observed data and predictive model’ outputs, and MSE value of 0.29107.

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来源期刊

Ultrasonics Sonochemistry 化学-化学综合

CiteScore

15.80

自引率

11.90%

发文量

361

审稿时长

59 days

期刊介绍： Ultrasonics Sonochemistry stands as a premier international journal dedicated to the publication of high-quality research articles primarily focusing on chemical reactions and reactors induced by ultrasonic waves, known as sonochemistry. Beyond chemical reactions, the journal also welcomes contributions related to cavitation-induced events and processing, including sonoluminescence, and the transformation of materials on chemical, physical, and biological levels. Since its inception in 1994, Ultrasonics Sonochemistry has consistently maintained a top ranking in the "Acoustics" category, reflecting its esteemed reputation in the field. The journal publishes exceptional papers covering various areas of ultrasonics and sonochemistry. Its contributions are highly regarded by both academia and industry stakeholders, demonstrating its relevance and impact in advancing research and innovation.