Evaluation of Artificial Insemination Services Provided through Africa Asia Dairy Genetic Gain Programme in Regions of Tanzania: Demographic Details and Herd Reproductive Performance
K.T. Kabuni *
Department of Cattle Research, Tanzania Livestock Research Institute (TALIRI), P.O. Box 202, Mpwapwa, Tanzania.
E.V.G. Komba
Department of Cattle Research, Tanzania Livestock Research Institute (TALIRI), P.O. Box 202, Mpwapwa, Tanzania.
A.C. Chota
Department of Cattle Research, Tanzania Livestock Research Institute (TALIRI), P.O. Box 202, Mpwapwa, Tanzania.
D.M. Komwihangilo
Department of Cattle Research, Tanzania Livestock Research Institute (TALIRI), P.O. Box 202, Mpwapwa, Tanzania.
G. Msuta
Department of Cattle Research, Tanzania Livestock Research Institute (TALIRI), P.O. Box 202, Mpwapwa, Tanzania.
D.F. Masao
Department of Cattle Research, Tanzania Livestock Research Institute (TALIRI), P.O. Box 202, Mpwapwa, Tanzania.
E. Lyatuu
International Livestock Research Institute (ILRI), P.O. Box 34441, Dar es Salaam, Tanzania.
N. Kelya
International Livestock Research Institute (ILRI), P.O. Box 34441, Dar es Salaam, Tanzania.
R. Mrode
International Livestock Research Institute (ILRI), P.O. Box 30709, Nairobi, Kenya.
D.B. Bura
Tanzania National Artificial Insemination Centre (NAIC), P.O. Box 557, Arusha, Tanzania.
R. Laven
School of Veterinary Science, Massey University (MU), Private bag 11 222, Palmerston North, New Zealand.
T.J. Parkinson
School of Veterinary Science, Massey University (MU), Private bag 11 222, Palmerston North, New Zealand.
A. Peters
The University of Edinburgh, Royal Dick School of Veterinary Studies, Roslin Institute, Easter Bush Campus, Midlothian EH25 9RG, UK.
*Author to whom correspondence should be addressed.
Abstract
The Africa Asia Dairy Genetics Gain (AADGG) program has been supporting smallholder farmers in Tanzania's key dairy regions—Kilimanjaro, Arusha, and Tanga—by providing long-term breeding services. This evaluation comprises a two-part study; the first part focuses on herd composition and breeding practices, while the second will examine farmers' attitudes toward artificial insemination (AI). A total of 82 farms were enrolled, with 82% participating in the AADGG program. The majority of farmers (82%) were male, with a median age of 58.5 years and median farm size of 1 acre (ranging from 0.25 to 6 acres). Most farmers relied on natural breeding, with 80% of those using AI selecting Friesian sires. In total, one hundred and twenty-four dams and their offspring were analyzed, revealing a median dam Parity of 3.0; 13% of cows were at Parity 1, and 48% at Parity 4-8. Among the offspring, 64% were calves, and 13% were yearlings, with only 16 male offspring, 69% of which were calves. The median lactation yield was 3,900 liters over a 10-month period. The mean age at first breeding and calving were 25.1 and 34.3 months, respectively. Inter-calving intervals averaged 14.6 months for dams and 12.0 months for parous offspring. Only 34% of dams had ≤90 days open, indicating poor reproductive efficiency, particularly for dams. The study highlights an aging farmer population and suggests future research to assess farm characteristics' impact on productivity and management practices affecting reproductive efficiency and herd dynamics.
Keywords: Farm characteristics, herd composition, reproductive efficiency, smallholder farmers, Tanzania