Fish Oil Recovery From Gilthead Sea Bream (Sparus aurata L.) Waste Using Ultrasound-Assisted Enzymatic Extraction: Process Optimization and Oil Characterization

IF 2.4 4区 农林科学 Q3 CHEMISTRY, APPLIED
Hasene Keskin Çavdar, Hakkı Bilgin, Sibel Fadıloğlu
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引用次数: 0

Abstract

This study investigates the optimization of fish oil extraction from gilthead sea bream (Sparus aurata L.) waste using ultrasound-assisted enzymatic extraction (UAEE), which is a sustainable and effective technique for extraction. Addressing the problems of fish processing waste, which accounts for 20%–80% of the total fish mass, ultrasonic waves and enzymatic hydrolysis in UAEE improve extraction efficiency while minimizing environmental effects. The fish oil extraction process was optimized by following a response surface methodology. The optimum conditions for the highest yield (31.0%, g/g) included an ultrasound time of 10.3 min, an enzyme concentration of 0.60% (g/g), and a hydrolysis time of 5 h, obtaining 72.0% extraction efficiency compared to classic Soxhlet extraction. The oil quality and stability were assessed by analyzing its physicochemical properties, fatty acid analysis with GC-FID, and analyzing the oxidation induction temperature using DSC. The extracted oil was characterized by its favorable fatty acid profile, including its high levels of docosahexaenoic (22:6n-3, 4.40%, g/g) and eicosapentaenoic acid (20:5n-3, 2.20%, g/g). The saponification and iodine values of the extracted oils fall within an acceptable range reported for fish oils. Despite a slightly lower oxidation stability compared to Soxhlet extraction, UAEE demonstrates significant potential for producing high-quality fish oil while using less energy and no hazardous solvents. This study promotes sustainable practices by using underutilized fish waste and reduces dependence on dangerous chemicals, which is in line with the worldwide effort to adopt environmentally friendly technologies.

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从金头鲷(Sparus aurata L.)中提取鱼油利用超声波辅助酶法提取废物:工艺优化和油脂表征
研究了超声辅助酶提法(UAEE)对鳙鱼鱼油的提取工艺优化,该工艺是一种可持续、高效的提取工艺。UAEE的鱼加工废弃物占鱼总质量的20%-80%,通过超声波和酶解技术提高了提取效率,同时减少了对环境的影响。采用响应面法对鱼油提取工艺进行优化。超声时间为10.3 min,酶浓度为0.60% (g/g),水解时间为5 h,提取率为72.0% (g/g)。通过理化性质分析、GC-FID脂肪酸分析和DSC氧化诱导温度分析,评价了油的品质和稳定性。提取的油具有良好的脂肪酸谱,包括高含量的二十二碳六烯酸(22:6n-3, 4.40%, g/g)和二十碳五烯酸(20:5n-3, 2.20%, g/g)。萃取油的皂化和碘值在鱼油可接受范围内。尽管与索氏萃取相比,UAEE的氧化稳定性略低,但在使用更少的能源和无有害溶剂的情况下,UAEE显示出生产高质量鱼油的巨大潜力。这项研究通过利用未充分利用的鱼类废物和减少对危险化学品的依赖来促进可持续做法,这符合世界范围内采用环境友好技术的努力。
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来源期刊
CiteScore
4.10
自引率
5.00%
发文量
95
审稿时长
2.4 months
期刊介绍: The Journal of the American Oil Chemists’ Society (JAOCS) is an international peer-reviewed journal that publishes significant original scientific research and technological advances on fats, oils, oilseed proteins, and related materials through original research articles, invited reviews, short communications, and letters to the editor. We seek to publish reports that will significantly advance scientific understanding through hypothesis driven research, innovations, and important new information pertaining to analysis, properties, processing, products, and applications of these food and industrial resources. Breakthroughs in food science and technology, biotechnology (including genomics, biomechanisms, biocatalysis and bioprocessing), and industrial products and applications are particularly appropriate. JAOCS also considers reports on the lipid composition of new, unique, and traditional sources of lipids that definitively address a research hypothesis and advances scientific understanding. However, the genus and species of the source must be verified by appropriate means of classification. In addition, the GPS location of the harvested materials and seed or vegetative samples should be deposited in an accredited germplasm repository. Compositional data suitable for Original Research Articles must embody replicated estimate of tissue constituents, such as oil, protein, carbohydrate, fatty acid, phospholipid, tocopherol, sterol, and carotenoid compositions. Other components unique to the specific plant or animal source may be reported. Furthermore, lipid composition papers should incorporate elements of year­to­year, environmental, and/ or cultivar variations through use of appropriate statistical analyses.
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