메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Song-Yi Gu (Kyungpook National University) Yunhee Jo (Institute of Health and Environment in Daegu Metropolitan City) Kashif Ameer (Chonnam National University) Joong-Ho Kwon (Kyungpook National University)
저널정보
한국식품저장유통학회 Food Science and Preservation 한국식품저장유통학회지 제26권 제4호
발행연도
2019.7
수록면
405 - 415 (11page)
DOI
10.11002/kjfp.2019.26.4.405

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
Eggplant is consumed worldwide as a valuable source of phytochemicals, especially anthocyanin and antioxidants. Here, microwave-assisted extraction (MAE) was applied to optimize the total yield (TY), total anthocyanin content (TAC), total phenolic content (TPC), and radical scavenging activities (DPPH, ABTS, and FRAP) of eggplant. A response surface methodology (RSM) was employed based on a five-factor, three-level central composite design with the ethanol concentration (X₁) 55-95% , microwave power (X₂: 0-200 W), and extraction time (X₃: 30-150 s) as independent process variables. Furthermore, the efficiency of MAE was compared to that of conventional reflux extraction (CRE) in terms of target responses, energy consumption, and CO₂ emissions. The highest TY (1.72%), TAC (9.55 ㎎ CE/L), TPC (48.75 ㎎ GAE/100 mL), and antioxidant activities (DPPH: 45.95, ABTS: 46.74, and FRAP: 69.22 ㎎ TE/100 mL) were obtained under the optimum MAE parameters of X₁: 70%, X₂: 160 W, and X₃: 100 s. Moreover, MAE yielded higher target responses than CRE in a faster time with lower energy consumption and CO2 emissions. In conclusion, the application of RSM to evaluate the extraction characteristics of individual components by MAE and CRE revealed MAE as an effective method for the green extraction of target compounds from eggplant.

목차

Abstract
Introduction
Materials and methods
Results and discussion
Conclusion
References

참고문헌 (32)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2019-059-000954216