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Predictive Models for Optimisation of Acetone Mediated Extraction of Polyphenolic Compounds from By-Product of Cider Production

Predictive Models for Optimisation of Acetone Mediated Extraction of Polyphenolic Compounds from By-Product of Cider Production
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摘要 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 (&#730C) 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. 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 (&#730C) 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.
出处 《Advances in Chemical Engineering and Science》 2020年第2期81-98,共18页 化学工程与科学期刊(英文)
关键词 CIDER APPLE POMACE PREDICTIVE Models Optimisation Polyphenolic Compounds Cider Apple Pomace Predictive Models Optimisation Polyphenolic Compounds
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