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Phenolics extraction from sweet potato peels: modelling and optimization by response surface modelling and artificial neural network.

ABSTRACT: Sweet potato peels (SPP) are a major waste generated during root processing and currently have little commercial value. Phenolics with free radical scavenging activity from SPP may represent a possible added-value product for the food industry. The aqueous extraction of phenolics from SPP was studied using a Central Composite Design with solvent to solid ratio (30-60 mL g^-1), time (30-90 min) and temperature (25-75 °C) as independent variables. The comparison of response surface methodology (RSM) and artificial neural network (ANN) analysis on extraction modelling and optimising was performed. Temperature and solvent to solid ratio, alone and in interaction, presented a positive effect in TPC, ABTS and DPPH assays. Time was only significant for ABTS assay with a negative influence both as main effect and in interaction with other independent variables. RSM and ANN models predicted the same optimal extraction conditions as 60 mL g^-1 for solvent to solid ratio, 30 min for time and 75 °C for temperature. The obtained responses in the optimized conditions were as follow: 11.87 ± 0.69 mg GAE g^-1 DM for TPC, 12.91 ± 0.42 mg TE g^-1 DM for ABTS assay and 46.35 ± 3.08 mg TE g^-1 DM for DPPH assay. SPP presented similar optimum extraction conditions and phenolic content than peels of potato, tea fruit and bambangan. Predictive models and the optimized extraction conditions offers an opportunity for food processors to generate products with high potential health benefits.

SUBMITTER: Anastacio A

PROVIDER: S-EPMC5223245 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Phenolics extraction from sweet potato peels: modelling and optimization by response surface modelling and artificial neural network.

Anastácio Ana A Silva Rúben R Carvalho Isabel S IS

Journal of food science and technology 20161208 12

Sweet potato peels (SPP) are a major waste generated during root processing and currently have little commercial value. Phenolics with free radical scavenging activity from SPP may represent a possible added-value product for the food industry. The aqueous extraction of phenolics from SPP was studied using a Central Composite Design with solvent to solid ratio (30-60 mL g<sup>-1</sup>), time (30-90 min) and temperature (25-75 °C) as independent variables. The comparison of response surface metho ...[more]

PMID: 28115751

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Project description:The purple sweet potato, Ipomoea batatas, belongs to the family Convolvulaceae. It is one of the most widely consumed tubers in Asia and is found in many dishes. Many people with diabetes eat purple sweet potato tubers to help reduce blood glucose in China.To predict the ultrasonic conditions for getting the optimal in vitro antioxidant and antiglycated activity of ultrasonic extracted polysaccharides from purple sweet potato (I. batatas) tubers, the artificial neural network (ANN) regression models was used in this study.The antioxidant activity of polysaccharides was quantified by evaluating the hydroxyl radical scavenging effect after ultrasonic extraction, and the data were used in conjunction with optimized extraction conditions to train the predictive ANN models.The following conditions were predicted to yield optimal hydroxyl scavenging activity: 200 W, 22°C, and 40 min. In contrast, conditions of 230 W, 22°C, and 50 min yielded the greatest inhibitory effect on albumin nonenzymatic glycosylation. The accuracy and predictive ability of the models ranged from good to excellent, as indicated by R2 values ranging from 0.953 to 0.998.The results of the present study showed that ANN predictive models are useful in ultrasonic processing, which can rapidly and accurately predict the optimum extraction conditions for polysaccharides based on their antioxidant and antiglycated activities. In addition, the results of the present study suggest that the consumption of sweet potatoes may help reduce free radicals in the body and prevent or treat diabetes.Ultrasonic extraction conditions were simulated and optimized using artificial neural networkBioactivities showed nonlinear relationship with ultrasonic conditionsThe optimal extraction conditions were 200 W, 22°C, and 40 min for the highest antioxidant capacityThe optimal extraction conditions were 230 W, 22°C, and 50 min for the highest antiglycated effect. Abbreviations used: IBP: Polysaccharide of Ipomoea batatas; RSM: response surface methodology; ANN: Artificial neural network; BSA: Bovine serum albumin.

Dataset Information

Phenolics extraction from sweet potato peels: modelling and optimization by response surface modelling and artificial neural network.

Publications

Phenolics extraction from sweet potato peels: modelling and optimization by response surface modelling and artificial neural network.

Similar Datasets

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