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首页> 外文期刊>Innovative Food Science & Emerging Technologies >Green ultrasound and microwave extraction of carotenoids from passion fruit peel using vegetable oils as a solvent: Optimization, comparison, kinetics, and thermodynamic studies
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Green ultrasound and microwave extraction of carotenoids from passion fruit peel using vegetable oils as a solvent: Optimization, comparison, kinetics, and thermodynamic studies

机译:使用植物油作为溶剂的热情果皮的绿色超声和微波提取类胡萝卜素:优化,比较,动力学和热力学研究

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摘要

The aim of this study was to examine the effect of green processes like ultrasonication assisted extraction (UAE) and microwave assisted extraction (MAE) using olive oil (OO) and sunflower oil (SO) as solvents on the extractability of carotenoids from passion fruit peel (PEP) that is discarded as waste. Using optimized conditions of UAE, 91.4% (OO) and 86.7% (SO) of the carotenoids present were extracted while MAE extracted 86.9% in OO. Comparison of energy density revealed that UAE is more efficient than MAE. UAE treated OO was acceptable for different quality parameters and the oil was enriched with carotenoids by more than three times and phenolic content by fifteen times. The extraction kinetics and thermodynamic studies for carotenoids extracted from PEP using UAE and CE (conventional extraction) processes with OO as solvent were performed at different combinations of extraction time and temperature. The extraction rate constant (ks) for UAE and CE was in the range of 0.0022?0.0048 100 g/?g carotenoids min and 4.02 x 10-5 - 6.85 x 10-5 100 g d.w./?g carotenoids min, respectively. The effective diffusion coefficient of UAE and CE for the extraction of carotenoids varied between 2.3740 x10-13 and 2.8260 x10-13 m2/s and 0.997x10- 14and 2.336 x10-14 m2/s, respectively and corresponding mass transfer rate ranged from 1.625 x10-7 ? 1.8731 x10-7 m/s and 0.0728 x10-8 ? 0.1714 x10-8 m/s. The kinetics information mainly rate constant, effective diffusivity and mass transfer coefficient obtained from the green extraction process using ultrasonication would allow the prediction of operation conditions for industrial implementation.
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