Optimization of ultrasound-assisted extraction of anthocyanins and bioactive compounds from butterfly pea petals using Taguchi method and Grey relational analysis

Ultrasound-assisted extraction (UAE) was used to extract anthocyanins, antioxidants and phenolic compounds from butterfly pea petals, as an alternative to traditional methods. Taguchi method with three factors: extraction time (30, 45, 60 min), temperature (40, 60, 80 °C) and liquid–solid ratio (5,...

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Veröffentlicht in:Journal of food science and technology 2020-10, Vol.57 (10), p.3720-3730
Hauptverfasser: Salacheep, Supanat, Kasemsiri, Pornnapa, Pongsa, Uraiwan, Okhawilai, Manunya, Chindaprasirt, Prinya, Hiziroglu, Salim
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Sprache:eng
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Zusammenfassung:Ultrasound-assisted extraction (UAE) was used to extract anthocyanins, antioxidants and phenolic compounds from butterfly pea petals, as an alternative to traditional methods. Taguchi method with three factors: extraction time (30, 45, 60 min), temperature (40, 60, 80 °C) and liquid–solid ratio (5, 7.5, 10 mL distilled water/mg butterfly pea) was used to obtain the high extraction yield. Grey relational analysis was employed to convert multi-response problem into single response optimization. The high extraction efficiency could be achieved at optimal parameter condition using 45 min of extraction time, 40 °C and 10 ml distilled water/mg butterfly pea. Liquid–solid ratio exhibited the highest contribution for anthocyanin and total phenolic content. A high temperature of ultrasonication resulted in a negative effect on antioxidant capacity and total phenolic content. The findings from this study indicated that the UAE process optimization would be an efficient and sustainable method for the preparation of bioactive compounds from medical plants with saving of reaction time and cost in which extraction yields of antioxidant capacity and total phenolic content were also increased. The color response analysis results suggested that the gelatin film incorporated with butterfly pea extract can be potentially used as pH-indicator for detecting food spoilage for intelligent packaging.
ISSN:0022-1155
0975-8402
DOI:10.1007/s13197-020-04404-7