Kinetic and thermodynamic characterization of thermosonication-assisted extraction of bioactives from lapsi fruit juice optimized by ANN-GA

Puja Das, Prakash Kumar Nayak and Radha krishnan Kesavan
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Abstract

The present study focuses on an extensive investigation into thermosonication as a novel process for enhancing the extraction of bioactive functional compounds from lapsi fruit juice. Process optimization was achieved by using artificial neural networks (ANN) coupled with a genetic algorithm (GA), finding optimum conditions to be 75% amplitude, 40 °C, and 60 minutes. The release performance of principal functional compounds, such as total phenolic content, total flavonoid content, antioxidant activity, and ascorbic acid, was also investigated under these optimized conditions. Among all the kinetic models used, the pseudo-second-order model demonstrated the best correlation (R2 = 0.99, χ2 = 0.09), which indicated that compound release occurred by chemisorption processes. The process also revealed an initial rapid extraction phase, which was then followed by a steady plateau at 60 minutes. The activation energies were in the range of 29.45 to 35.23 kJ mol−1, and this indicated the temperature dependence of the process. Thermodynamic studies revealed that the extraction was spontaneous under all tested temperatures (ΔG: −5.45 to −18.46 kJ mol−1), endothermic in nature (ΔH: 5.44 to 15.64 kJ mol−1), entropy-guided (ΔS: 18.03 to 57.23 J mol−1 K−1) and, therefore, capable of efficiently breaking down the cell walls and facilitating mass transfer. Optimal extraction efficiency was achieved at 40 °C, beyond which heat-induced degradation of labile compounds was observed. Kinetic and thermodynamic studies confirm that thermosonication enables efficient, spontaneous, and temperature-dependent extraction of bioactives from Lapsi juice. The findings support its feasibility for energy-efficient, scalable industrial applications.

Abstract Image

ANN-GA优化热超声辅助提取lapsi果汁中生物活性物质的动力学和热力学表征
本研究的重点是广泛研究热超声作为一种新的工艺,以提高从lapsi果汁中提取生物活性功能化合物。采用人工神经网络(ANN)和遗传算法(GA)对工艺进行优化,优化条件为75%振幅、40°C、60分钟。并考察了在优化条件下,总酚含量、总黄酮含量、抗氧化活性和抗坏血酸等主要功能化合物的释放性能。其中拟二阶动力学模型相关性最好(R2 = 0.99, χ2 = 0.09),说明化合物的释放是通过化学吸附过程进行的。该工艺还揭示了最初的快速提取阶段,然后在60分钟后进入稳定的平台期。反应的活化能在29.45 ~ 35.23 kJ mol−1之间,表明了反应的温度依赖性。热力学研究表明,在所有测试温度下(ΔG:−5.45至−18.46 kJ mol−1),萃取是自发的,本质上是吸热的(ΔH: 5.44至15.64 kJ mol−1),熵引导的(ΔS: 18.03至57.23 jmol−1 K−1),因此能够有效地破坏细胞壁并促进传质。在40°C时,萃取效率最高,超过40°C时,观察到不稳定化合物的热诱导降解。动力学和热力学研究证实,热超声能够有效地、自发地、依赖温度地从拉普西果汁中提取生物活性物质。研究结果支持其在节能、可扩展的工业应用中的可行性。
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