16 Evaluation of Factors Influencing Timed Artificial Insemination in South African Communal Cows
Z. C. Raphalalani A B , T. L. Nedambale A , M. L. Mphaphathi B , M. M. Seshoka B , M. Nkadimeng B , M. A. Bopape B , F. L. Seolwana B , M. H. Mapeka B , F. V. Ramukhithi B and K. A. Nephawe AA Faculty of Science, Department of Animal Science, Tshwane University of Technology, Pretoria, Republic of South Africa;
B Agricultural Research Council, Animal Production Institute, Germplasm Conservation and Reproductive Biotechnologies, Irene, Pretoria, Republic of South Africa
Reproduction, Fertility and Development 30(1) 147-148 https://doi.org/10.1071/RDv30n1Ab16
Published: 4 December 2017
Abstract
In South Africa, assisted reproductive technologies (ART) such as oestrus synchronization and AI in cattle have traditionally been applied in commercial production systems but not communal production systems because of several challenges such as infrastructure and cost. The study was designed to assess factors affecting response to oestrus synchronization, conception, and calving rate of organised communal cows following timed AI in Limpopo province, South Africa. A total of 140 cows were selected from organised communal villages and categorized according to body condition score (BCS), parity, age, frame size (small to medium) and breed type (Nguni, Bonsmara, and Brahman). A 9-day CIDR® (Pfizer Laboratories, New York, NY, USA) protocol was used to synchronize the selected cows. Heat mount detectors (Karma®; Four Lakes) were used to assess oestrous synchronisation responce. The AI was done twice at 36 and 48 h post-CIDR® removal using Nguni frozen–thawed semen. Pregnancy diagnosis was performed 90 days following AI using ultrasound scanner and trans-rectal palpation. Data on influence of factors such as BCS, parity, age, district, breed type, and frame size on oestrus response, conception and calving rate were analysed using logistic regression procedure of SAS. Of 140 cows synchronized, 75% (105/140) had tripped patches and underwent AI, 41% (43/105) conceived, and 36% (38/105) calved. Parity, age, breed type, and frame size did not significantly affect oestrous synchronisation response, conception, and calving rate. However, BCS significantly (P = 0.0042) affected calving rate, whereby cows in BCS of >3 had a greater probability of success than those with BCS ≤3. Small-framed Nguni and Bonsmara type cows in their first parity with a BCS ≥3 had greater odds of conceiving following timed AI. Noteworthy, calving rate in the current study was comparable to other studies under communal areas (South African Vet. Assoc. 2004 75, 30-36; Appl. Anim. Husb. Rural Develop. 2013 6, 48-54). Therefore, the current study demonstrated an opportunity to improve the production of organised communal cattle using superior sire germplasm though assisted reproductive technologies. Cows in organised communal areas have greater probability of conceiving and calving when their condition score is >3, regardless of their age, parity, size, or breed type. It is concluded, therefore, that AI technology should be applied in cows of organised communal farmers to facilitate dissemination and propagation of superior germplasm.