Optimization of Sesame oil Extraction from Sesame cake using Supercritical Fluid $CO_{2}$

초임계유체 $CO_{2}$를 이용한 참깨박 중 참기름 추출의 최적화

  • Kim, Seong-Ju (Department of Food Science and Technology, Chungnam National University) ;
  • Kim, Young-Jong (Department of Food Science and Technology, Chungnam National University) ;
  • Chang, Kyu-Seob (Department of Food Science and Technology, Chungnam National University)
  • 김성주 (충남대학교 식품공학과) ;
  • 김영종 (충남대학교 식품공학과) ;
  • 장규섭 (충남대학교 식품공학과)
  • Published : 2005.06.30


Overall experiments were planned by central composite design, and results were analyzed by response surface methodology (RSM) to determine effects of three independent variables, temperature ($X_{1}$), extraction time ($X_{3}$), and pressure ($X_{3}$), on yield of sesame oil extract (Y). Regression equation model optimized by response surface analysis was: Y (sesame oil) = $-3.89+0.07X_{1}+0.03X_{2}+0.0006X_{3}-0.0007X_{1}^{2}-0.0002X_{2}X_{1}-0.00008X_{2}^{2}+0.000004X_{3}X_{1}+0.0000009X_{3}X_{2}-0.00000009X_{3}^{2}$. According to RSM analysis, optimum extracting conditions of temperature, time, and pressure were $45.89^{\circ}C$, 131.89 min, and 34228.41 kPa, respectively, and statistical maximum yield of sesame oil was 96.27%. Fatty acid composition of sesame oil showed sesame oil extracted by Supereritical Fluid $CO_{2}$ contained lower levels of palmitic, stcaric, and oleic acids and higher levels or palmitoleic and linoleic acids than commercial sesame oil. Commercial and extracted sesame oils were analyzed by electronic nose composed of 12 different metal oxide sensors. Obtained data were interpreted by statistical method of MANOVA. Sensitivities of sensors from electronic nose were analysed by principal component analysis. Proportion of first principal component was 99.92%. All sesame oils showed different odors (p < 0.05).


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