Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology

Li, Huizhen; Zhang, Zhijun; Hou, Tianyu; Li, Xiaojun; Chen, Tie

doi:10.1016/j.indcrop.2015.06.021

Cited by 92 publications

(62 citation statements)

References 36 publications

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“…The first effect may be attributed to the fact that many bubbles created by ultrasonic significantly and a fragmentation of the matrix occurred in ultrasound process accelerate the release of components from cells into the distilled water and the penetration of distilled water into cells 5,24,25 . This result was consistent with findings obtained with perilla oil 26 . In addition, at ultrasonic power level higher 400 W, oil color deepened, which indicate a decrease in oil quality.…”

Section: Discussionsupporting

confidence: 93%

Ultrasonic-assisted Aqueous Extraction and Physicochemical Characterization of Oil from <i>Clanis bilineata</i>

Sun

Zhang

et al. 2018

J. Oleo Sci.

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Section: Discussionsupporting

confidence: 93%

Ultrasonic-assisted Aqueous Extraction and Physicochemical Characterization of Oil from <i>Clanis bilineata</i>

Sun

Zhang

et al. 2018

J. Oleo Sci.

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“…The saponification values (196.48 -198.26 mg KDH/g oil) of UAAEE oil, SE oil and CPE oil were not significantly different (p > 0.05). The values were, however, higher than those of other vegetable oils (Cerchiara et al, 2010;Li et al, 2015), indicating very high levels of low molecular weight triacylglycerols, which means that perilla oil is very suitable for the production of liquid soaps and shampoos.…”

Section: Physicochemical Characteristics and Fatty Acid Composition Omentioning

confidence: 73%

“…The fatty acid composition of the perilla seed oils was analyzed using an HP-7900 gas chromatograph (Tianmei Scientific Instrument Co., Ltd., Shanghai, China), according to the method of Li et al (2015).…”

Section: Fatty Acid Compositionmentioning

confidence: 99%

Ultrasound-assisted aqueous enzymatic extraction of oil from perilla seeds and determination of its physicochemical properties, fatty acid composition and antioxidant activity

Zhang

et al. 2017

Food Sci. Technol

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Response surface methodology (RSM) was used to optimize ultrasound-assisted aqueous enzymatic extraction (UAAEE) conditions for perilla seed oil. Under the optimum conditions-which were a liquid-to-solid ratio of 4.4:1, a hydrolysis time of 2.66 h, a hydrolysis temperature of 50.87 °C and an ultrasound treatment time of 24.74 min-an oil yield of 31.34% was obtained. Comparisons of the physicochemical characteristics of oil obtained using UAAEE with those of oil obtained by solvent extraction (SE oil) and cold pressing extraction (CPE oil) revealed similar refractive indices and saponification values, but UAAEE oil had a higher iodine value and better stability against oxidation, with a low peroxide value. UAAEE oil contained higher levels of beneficial α-linolenic acid and phenolics than SE oil or CPE oil, and it also had superior efficiency in scavenging 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals.Keywords: perilla seed oil; ultrasound-assisted aqueous enzymatic extraction; physical and chemical characteristics; fatty acid composition; antioxidant activities.Practical Application: Based on its physical and chemical properties, perilla oil obtained using UAAEE would be suitable as high quality edible oil and could also have applications in the cosmetic and pharmaceutical industries.

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“…Perilla (Perilla frutescens), an aromatic vegetable, has been cultivated worldwide and used extensively for cooking and medicinal purposes in several Asian countries (Igarashi & Miyazaki, 2013;Li et al, 2015). The leaves of P. frutescens have been shown to have detoxicant, antitussive, antipyretic and antibiotic properties (Liu et al, 2013;Nakamura et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

Optimization of ultrasound-assisted extraction of phenolic compounds, antioxidants and rosmarinic acid from perilla leaves using response surface methodology

Zhang

Xue

et al. 2016

Food Sci. Technol

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Response surface methodology (RSM) was used to optimize ultrasound-assisted extraction (UAE) of functional components from perilla leaves. The factors investigated were ethanol concentration, extraction temperature, and extraction time. The results revealed that ethanol concentration had significant effects on all extraction parameters. Based on the RSM results, the optimal conditions were an ethanol concentration of 56%, a UAE temperature of 54 °C, and a UAE time of 55 min. Under these conditions, the experimental TPC (total phenolic content), RA (rosmarinic acid), FRAP (ferric reducing antioxidant power) and DPPH (1,1-diphenyl-2-picrylhydrazyl) values were 48.85 mg GAE/g DW (mg gallic acid equivalent /g of dry weight), 31.02 mg/g DW, 85.55 μmol Fe 2+ /g DW and 73.35%, respectively. The experimental values were in agreement with those predicted by RSM models, confirming suitability of the model employed and the success of RSM for optimization of the extraction conditions. Keywords: perilla leaves; ultrasound-assisted extraction; phenolic compounds; antioxidants; rosmarinic acid. Practical Application:The study provides valuable information that ultrasound-assisted extraction is an environmentally-friendly, green process for the preparation of extracts from perilla leaves, and will help in the development of functional food resources.

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Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology

Cited by 92 publications

References 36 publications

Ultrasonic-assisted Aqueous Extraction and Physicochemical Characterization of Oil from <i>Clanis bilineata</i>

Ultrasonic-assisted Aqueous Extraction and Physicochemical Characterization of Oil from <i>Clanis bilineata</i>

Ultrasound-assisted aqueous enzymatic extraction of oil from perilla seeds and determination of its physicochemical properties, fatty acid composition and antioxidant activity

Optimization of ultrasound-assisted extraction of phenolic compounds, antioxidants and rosmarinic acid from perilla leaves using response surface methodology

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