4.6 Article

Optimization of Ultrasonic-Assisted Enzymatic Extraction of Freeze-Dried Sea Buckthorn (Hippophae rhamnoides L.) Berry Oil Using Response Surface Methodology

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SUSTAINABILITY
卷 14, 期 17, 页码 -

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MDPI
DOI: 10.3390/su141710849

关键词

fatty acid composition; FAME; physicochemical characteristics; predictive model; Soxhlet extraction; ultrasonication

资金

  1. Deanship of Scientific Research at Umm Al-Qura University [22UQU4290372DSR04]

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The optimal conditions for ultrasound-assisted enzymatic extraction of sea buckthorn oil were determined to be a solvent to sample ratio of 5.08 mL/g, an ultrasonication time of 14.65 minutes, and an enzyme unit of 3.13 U/g. The oil extracted using this method had better physicochemical properties and higher levels of fatty acids compared to the oil extracted using the Soxhlet method.
The ultrasound-assisted extraction (UAE) of oil has received immense importance nowadays because of the enormous benefits the process offers. However, the literature evaluating this process is scarce for sea buckthorn oil. Furthermore, to date, to the best of our knowledge, a study evaluating the combined use of enzymes and UAE for this oil is lacking. In this study, oil from freeze-dried sea buckthorn berries was extracted using ultrasound-assisted enzymatic extraction (UAEE) and the effect of variables (time, enzyme concentration, and solvent to sample ratio) was evaluated on oil yield and its physiochemical properties (acid value, peroxide value, iodine value, density, and color). The optimum conditions were determined using the response surface methodology. The optimum conditions established were 5.08 mL/g, 14.65 min, and 3.13 U/g for a solvent to sample ratio, ultra-sonication time, and enzyme units, respectively. The oil yield was 18.32%. Physicochemical parameters were found better in UAEE oil than in the Soxhlet-extracted oil. Gas chromatography detected relatively higher levels of fatty acids, including palmitic, palmitoleic, and oleic acids in UAEE oil. The optimum conditions were also verified for adequacy by validation and results were matched with predicted values with 0.8 to 1.5 error %, which states that the model can be utilized to predict oil yield percentage.

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