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<p>Integrating with microwave-assisted extraction, deep eutectic solvents present a sustainable and efficient alternative to conventional organic solvents for extracting polyphenols from <i>Azadirachta indica</i> leaves. Choline chloride-ethylene glycol at various mole ratios and water contents was evaluated for its effectiveness in extracting polyphenol compounds. The results demonstrated that the interaction between leaves, water, and deep eutectic solvents significantly affected the total phenolic content. A precise optimisation of deep eutectic solvent extraction, employing a 1:3.5 or 1:6 molar ratio, a 12.5 feed-to-solvent ratio, and 17.5% water, yielded maximum phenolic compound extraction, characterised by Folin–Ciocalteu quantification and confirmed via GC–MS identification of key phenolic classes, corroborated by FTIR spectral analysis of relevant functional groups. Deep eutectic solvent-assisted microwave-assisted extraction demonstrates exceptional promise as a sustainable methodology for optimising polyphenol recovery from <i>Azadirachta indica</i> foliage, as evidenced by our comprehensive investigation. Microwave-assisted extraction supports sustainability by enhancing energy efficiency, promoting circular economies, and upcycling waste into polyphenols using water-based solvents. A radial-basis artificial neural network was employed to develop a prediction model for total phenolic content, and it successfully predicted the total phenolic content values with an average error of 4.81%.</p>

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Optimisation studies on polyphenol production from Azadirachta indica leaves—influence of operating conditions

  • 期刊论文

  • 发表日期：

    2025年8月16日

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  • Santosh A. Kadapure,
  • Umesh B. Deshannavar,
  • Amith G. Gadagi,
  • Prasad G. Hegde,
  • Natarajan Rajamohan

摘要

Integrating with microwave-assisted extraction, deep eutectic solvents present a sustainable and efficient alternative to conventional organic solvents for extracting polyphenols from Azadirachta indica leaves. Choline chloride-ethylene glycol at various mole ratios and water contents was evaluated for its effectiveness in extracting polyphenol compounds. The results demonstrated that the interaction between leaves, water, and deep eutectic solvents significantly affected the total phenolic content. A precise optimisation of deep eutectic solvent extraction, employing a 1:3.5 or 1:6 molar ratio, a 12.5 feed-to-solvent ratio, and 17.5% water, yielded maximum phenolic compound extraction, characterised by Folin–Ciocalteu quantification and confirmed via GC–MS identification of key phenolic classes, corroborated by FTIR spectral analysis of relevant functional groups. Deep eutectic solvent-assisted microwave-assisted extraction demonstrates exceptional promise as a sustainable methodology for optimising polyphenol recovery from Azadirachta indica foliage, as evidenced by our comprehensive investigation. Microwave-assisted extraction supports sustainability by enhancing energy efficiency, promoting circular economies, and upcycling waste into polyphenols using water-based solvents. A radial-basis artificial neural network was employed to develop a prediction model for total phenolic content, and it successfully predicted the total phenolic content values with an average error of 4.81%.