丙酮萃取苹果酒副产品中多酚类化合物的优化预测模型

S. Ibrahim, Regina C D Santos, S. Bowra
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引用次数: 0

摘要

采用响应面法(RSM)对丙酮水溶液提取苹果渣中多酚类化合物的工艺条件进行了优化。采用中心复合旋转式设计(CCRD),考察丙酮浓度% (v/v)、料液比% (w/v)、温度(˚C)、萃取时间(min)等因素对酚类物质含量的影响及其交互作用。对实验数据进行分析,拟合酚类化合物回收率的统计模型。所选模型除绿原酸和槲皮素3-葡萄糖苷显著缺乏拟合外(P R2 > 0.9000,经调整后与预测值合理吻合),其余模型均具有显著性(P 0.05)。在95%置信区间内,每次测定的变异系数< 5%。这些模型可用于在营养保健、制药和化妆品工业中实现多酚化合物的最佳浓度。
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Predictive Models for Optimisation of Acetone Mediated Extraction of Polyphenolic Compounds from By-Product of Cider Production
Response surface methodology (RSM) was applied to provide predictive models for optimisation of extraction of selected polyphenolic compounds from cider apple pomace under aqueous acetone. The design of experiment (DoE) was conducted to evaluate the influence of acetone concentration % (v/v), solid-to solvent ratio % (w/v), temperature (˚C) and extraction time (min) and their interaction on phenolic contents, using the Central Composite Rotatable Design (CCRD). The experimental data were analysed to fit statistical models for recovery of phenolic compounds. The selected models were significant (P 0.05), except for Chlorogenic acid and Quercetin 3-glucoside which had significant lack of fits (P R2 > 0.9000 and adjusted   reasonable agrees with predicted . Coefficient of variation < 5% for each determination at the 95% confidence interval. These models could be relied upon to achieve optimal concentrations of polyphenolic compounds for applications in nutraceutical, pharmaceutical and cosmetic industries.
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