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

논문 기본 정보

자료유형
학술저널
저자정보
이창성 (강릉대학교 식품과학과) 이근택 (강릉대학교 식품과학과) 이광호 (식품의약품안전본부 용기포장과)
저널정보
한국식품위생안전성학회 한국식품위생안전성학회지 한국식품위생안전성학회지 제12권 제2호
발행연도
1997.1
수록면
132 - 140 (9page)

이용수

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

초록· 키워드

오류제보하기
Additives in plastics are capable of migrating from the packaging materials into the foodstuffs, thereby presenting a source of contamination and a potential health risk to the consumer. The migration from packaging materials into foodstuffs is first of all regulated by examining the amounts of global and specific migrated components. Besides, there is worldwide still a need for practical methods for measuring and monitoring migration from polymers, especially for the testing of migration into fatty foodstuffs. Therefore, these studies were undertaken to investigate the safety status of domestic plastic packaging materials with respect to migration. Another objective of this study was to examine the applicability of ethanol as an alternative fatty food simulant substituting for olive oil and n-heptane. The evaporation residues for various dometic plastic samples determined as described in Korean food laws were in the level from 4.3 to 14.5 mg/$\ell$, which were much lower than the limit value of 150 mg/$\ell$. The global migration values into 95 % ethanol showed to be comparable to those into n-heptane, while the olive oil migration values were comparably higher than those into ethanol or n-heptane and moreover they were not reproducible. The kinetic migration begavior of additives in polyolefin samples into 95% ethanol showed a Fickian diffusion process. The results of these studies on global migration and kinetic testings demonstrate that the ethanol could be successfully substitute for the olive oil and n-heptane as an alternative fatty food simulant, at least in contact with polyoefins.

목차

등록된 정보가 없습니다.

참고문헌 (0)

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