On Farm Evaluation of Milk Production and Composition Performance of Horro Cattle Breed in Western Oromia, Ethiopia
DOI:
https://doi.org/10.20372/star.v10i3.01Keywords:
Horro cattle, Horro district, Milk composition, Milk yield, Non-genetic factorsAbstract
The current study was conducted in Horro district of Horro Guduru Wallaga zone, Oromia, Ethiopia, to evaluate the milk production performance and milk composition of Horro cattle herds managed under farmers’ management conditions. Data on milk production and composition were collected from 220 Horro cows owned by 64 households for two years. The data were analysed using the General Linear Model (GLM) Procedures of the Statistical Analysis System (SAS, 2004). The overall means (LSM±SE) for daily milk yield (DMY), lactation milk yield (LMY), 305 days’ milk yield (305DMY), and lactation length (LL) were 1.5±0.01liters, 419.8±4.45liters, 474.5±3.50liters, and 284.1±0.15days, respectively. The overall mean (LSM±SE) for protein, fat, solid, not fat, and total solid percentages were 3.5%, 6.0%, 8.8%, and 14.0%, respectively. The year of calving, season of calving, parity, and stage of lactation significantly influenced all milk production performances. Parity, stage of lactation, and season had significant (P<0.01) effects on fat, solids, not fat (SNF), and total solids (TS). The highest average daily milk yield was recorded during the first 3 months of lactation, whereas the highest percentage composition of fat and total solids (TS) was recorded after six months of lactation. The highest milk yield was recorded from cows from third parties and cows that calved during the short rainy season. The traits measured in the current study were significantly affected by non-genetic factors, indicating a remarkable improvement can be achieved through improved management. The existence of huge variations among individuals within the herds involved in the current study was observed in milk production performance, which indicates improvements in the trait could be achieved through selection.
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