Harnessing the power of artificial neural networks methodology and multi-objective optimization for enhanced yield and bioactivity of plants polyphenolic compounds
{"title":"Harnessing the power of artificial neural networks methodology and multi-objective optimization for enhanced yield and bioactivity of plants polyphenolic compounds","authors":"Yousra Touami , Rafik Marir","doi":"10.1016/j.jarmap.2024.100551","DOIUrl":null,"url":null,"abstract":"<div><p>The extraction of polyphenolic compounds from plants is crucial in the industrial production of functional nutraceuticals, but traditional methods often yield low and variable results. In this research, an innovative strategy for optimizing polyphenol extraction from two plants <em>Cistus creticus L.</em> and <em>Ephedra alata</em> subsp. <em>alenda</em> (Stapf) Trab., known for their rich composition in polyphenols and their bioactivities, using Ultrasound-Assisted Extraction in conjunction with artificial neural networks (ANNs) and multi-objective optimization is presented. ANNs were trained to model the intricate relationships among UAE parameters, including solvent concentration, temperature, and time, and the outcomes, encompassing polyphenol yield and bioactivity. Multi-objective optimization techniques were subsequently applied to identify extraction conditions that maximize both yield and bioactivity simultaneously. Results validate the accuracy of the ANNs model in predicting polyphenol yields and the significant enhancement in extraction efficiency and bioactivity achieved through multi-objective optimization. The extracts prepared in the optimal conditions have demonstrated superior antioxidant activities, compared to the non-optimized extracts, with the smallest values of IC<sub>50</sub> of 242,378 µg/mL, and 146,736 µg/mL for the plants <em>Ephedra alata</em> subsp <em>alenda</em> (Stapf) Trab. and <em>Cistus creticus</em> L. respectively. This study introduces a promising approach for elevating the extraction of plant-derived polyphenols, augmenting their bioactivity with ANNs and multi-objective optimization. In light of the obtained results, it is recommended that further research explore the scalability and applicability of the presented innovative strategy in larger-scale industrial settings. Considering the demonstrated success in optimizing polyphenol extraction from <em>Cistus creticus</em> L. and <em>Ephedra alata</em> subsp. <em>alenda</em> (Stapf) Trab., extending the application of Ultrasound-Assisted Extraction, coupled with artificial neural networks (ANNs) and multi-objective optimization, to other plant species could offer valuable insights. Additionally, investigating the economic feasibility and environmental impact of implementing this strategy on an industrial scale would contribute to its practical viability.</p></div>","PeriodicalId":15136,"journal":{"name":"Journal of Applied Research on Medicinal and Aromatic Plants","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Research on Medicinal and Aromatic Plants","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S221478612400024X","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The extraction of polyphenolic compounds from plants is crucial in the industrial production of functional nutraceuticals, but traditional methods often yield low and variable results. In this research, an innovative strategy for optimizing polyphenol extraction from two plants Cistus creticus L. and Ephedra alata subsp. alenda (Stapf) Trab., known for their rich composition in polyphenols and their bioactivities, using Ultrasound-Assisted Extraction in conjunction with artificial neural networks (ANNs) and multi-objective optimization is presented. ANNs were trained to model the intricate relationships among UAE parameters, including solvent concentration, temperature, and time, and the outcomes, encompassing polyphenol yield and bioactivity. Multi-objective optimization techniques were subsequently applied to identify extraction conditions that maximize both yield and bioactivity simultaneously. Results validate the accuracy of the ANNs model in predicting polyphenol yields and the significant enhancement in extraction efficiency and bioactivity achieved through multi-objective optimization. The extracts prepared in the optimal conditions have demonstrated superior antioxidant activities, compared to the non-optimized extracts, with the smallest values of IC50 of 242,378 µg/mL, and 146,736 µg/mL for the plants Ephedra alata subsp alenda (Stapf) Trab. and Cistus creticus L. respectively. This study introduces a promising approach for elevating the extraction of plant-derived polyphenols, augmenting their bioactivity with ANNs and multi-objective optimization. In light of the obtained results, it is recommended that further research explore the scalability and applicability of the presented innovative strategy in larger-scale industrial settings. Considering the demonstrated success in optimizing polyphenol extraction from Cistus creticus L. and Ephedra alata subsp. alenda (Stapf) Trab., extending the application of Ultrasound-Assisted Extraction, coupled with artificial neural networks (ANNs) and multi-objective optimization, to other plant species could offer valuable insights. Additionally, investigating the economic feasibility and environmental impact of implementing this strategy on an industrial scale would contribute to its practical viability.
期刊介绍:
JARMAP is a peer reviewed and multidisciplinary communication platform, covering all aspects of the raw material supply chain of medicinal and aromatic plants. JARMAP aims to improve production of tailor made commodities by addressing the various requirements of manufacturers of herbal medicines, herbal teas, seasoning herbs, food and feed supplements and cosmetics. JARMAP covers research on genetic resources, breeding, wild-collection, domestication, propagation, cultivation, phytopathology and plant protection, mechanization, conservation, processing, quality assurance, analytics and economics. JARMAP publishes reviews, original research articles and short communications related to research.