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
고영진 (경상대학교 수의과대학 수의학과) 강은주 (경상대학교 수의과대학 수의학과) 이성림 (경상대학교 수의과대학 수의학과)
저널정보
한국동물번식학회 한국수정란이식학회지 한국수정란이식학회지 제24권 제3호
발행연도
2009.1
수록면
131 - 137 (7page)

이용수

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

초록· 키워드

오류제보하기
In dogs, correct diagnosis of estrus is important and the exact time of ovulation can be determined by variouse methods. Vaginal cytology has commonly used in conjunction with the physical examination, clinical history, vaginoscopy, and hormonal assays to determine the stage of the reproductive cycle. This study was therefore investigated the effectiveness of direct ovulation detector designed by changes of electrical resistance in vaginal mucus following different estrus cycles with several methods; vaginal cytology, concentration of plasma estrogen and progesterone, and direct examination by laparotomy. A total of 12 bitches was selected for the study and observed estrus signs. The bitches were evaluated clinical sign (vulvar swelling and bleeding), cytological examination (keratocyte and RBC), electrical resistance, plasma estrogen and progesterone concentration for estrus assessment. Accuracy of ovulation detection by vaginal cytology was significantly (p<0.05) lower than those by electrical resistance and plasma progesterone concentration, based on the confirmation by laparotomy. Vaginal smear is not confidential method compared to detection of electrical resistance and plasma progesterone concentration at ovulation. Although the value of electrical resistance was varied at the same points of estrus in individuals, ovulation was occurred at the first day which shown the peak of electrical resistance and mating time was third day after peak. In conclusion, ovulation detector designed by changes of electrical resistance is an effective and economic instrument for predicting estrus and ovulation in bitches.

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