Characterization of physico-chemical properties of cervical mucus in relation to parity and conception rate in Murrah buffaloes

Autor: K. K. Verma, Shiv Prasad, A. Kumaresan, T. K. Mohanty, S. S. Layek, T. K. Patbandha, S. Chand
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Zdroj: Veterinary World, Vol 7, Iss 7, Pp 467-471 (2014)
Druh dokumentu: article
ISSN: 0972-8988
2231-0916
DOI: 10.14202/vetworld.2014.467-471
Popis: Aim: To characterize the physico-chemical properties of estrual cervical mucus among different parities and analyse their association with conception rate in Murrah buffaloes. Materials and Methods: Cervical mucus was collected from the mid-cervix using sterile blue sheath before artificial insemination (AI) in Murrah buffaloes (n=94) and examined for appearance (transparent/ translucent), consistency (thin/ moderate/ thick), Spinnbarkeit value, arborisation pattern (typical/ atypical/ nil), pH and electrical conductivity. Artificial insemination was carried out using frozen-thawed semen by recto-vaginal method and pregnancy was confirmed by per-rectal examination after 60 days of insemination. Furthermore, the conception rates were calculated and their relationship with physico-chemical properties of cervical mucus was studied. Results: Cervical mucus was clear and thin in 85.10% and 15.96 % of estrus periods, respectively. Typical arborisation pattern of cervical mucus was observed in 54.25% of the estruses. The Mean ± SEM of pH, electrical conductivity and Spinnbarkeit value of mucus were 7.82 ± 0.02, 14.00 ± 0.10 mS/cm and 14.18 ± 0.59 cm, respectively. Significantly (P< 0.05) higher conception rate (54.90%) was observed in buffaloes inseminated with typical arborisation pattern of cervical mucus as compared to atypical arborisation pattern (20.00%) and no conception was recorded in the estruses with nil arborisation pattern. Conclusion: The results of present investigation concluded that arborisation pattern has significant relationship with conception rate thus can be used as an important criteria to predict the right time of AI for improving conception rate in Murrah buffaloes.
Databáze: Directory of Open Access Journals