2.1 Description of working sites
Andassa Livestock Research Center (ALRC): is found at 587 km Northwest of Addis Ababa, and 22 km South of Bahir Dar city (capital of Amhara region), on the way to Blue Nile fall. The total area of the center is about 360 hectares out of which 310 are covered by pasture land and the rest 50 hectares is covered with bushes and different constructions. The center was established to conserve Fogera breed both in-situ and ex-situ approach. The center had above 600 nucleus herd animals for conservation and improvement strategy. Community based breed improvement program was implementing at two districts; those are known to have true-to-type Fogera cattle breed. These are:
Gondar Zuria district: the district is found in North Gondar of Amhara regional state. It is located 12° 39' N latitude and 37° 19' E longitude. The altitude of the district is 1982 masl and the average annual rainfall range between 950 to1035mm. The annual temperature ranges from 27oc to 33oc. The total area coverage of the district is 114,983ha. The cattle population was estimated to be 212,164 [18].
Fogera district: the district is found in South Gondar of Amhara regional state. It locates 11°46’ to 11°59’ latitude and 37°33’ to 37°52’ longitudes. The altitude ranges from 1774 to 2410 masl, and receives mean annual rainfall of 1216.3 mm (ranging from 1103 to 1336 mm). The average minimum and maximum temperature of the district vary between 10.3°C to 27.2°C. It has an estimated cattle population of 182729. The land, about 44.2% is arable and 20% is irrigated, 22.9% for pasture, 1.8% forest or shrub land, 3.7% is water, and the remaining 7.4% is considered degraded land [19]. Figure 1 (right) indicates the working districts.
2.2 Description of Fogera breed
With its distinctive combination of a black muzzle, black inner ears, a black, white and grey coat colour, and its long legs and tail, the Fogera are one of the most iconic cattle breeds of Ethiopia. Found in the district bordering Lake Tana (Fig. 1 left), Ethiopia’s largest lake and the source of the Blue Nile, the breed is particularly well adapted to wet soils and swampy areas and cop adapted to wet soils and swampy areas and copes well with the heavy fly, parasite and disease well with the heavy fly, parasite and disease infestations, as well as low quality of feed, that characterizes this challenging environment [1]. The breed (Fig. 2) is also characterized with short, stumpy, pointed horns; hump ranges from thoracic to cervico-thoracic; dewlap is folded and moderate to large in size; docile temperament; used for draught, milk and meat [20, 21].
2.3 Breeding strategy
The center follows open nucleus breeding scheme (Fig. 3), to improve milk yield of Fogera cattle. In the strategy, improved bulls from the nucleus had transported to community (village) herd and selected heifers to the nucleus herd. In the nucleus herd, animals are grouped based on their milk yield and pedigree. A single herd had 40 to 50 cows with one bull and mating is natural.Calves had free access to suckle their dams for the first four days to ensure that they consume enough colostrum; they were then separated from their dams and allowed to partially suckle (two teats) at milking times until weaning.
2.4 Community Based Breed Productivity Improvement (CBBPI)
As a part of open nucleus breeding strategy, community-based breed productivity improvement is the implementation program of the strategy at the village herd. For the implementation, through participation of researchers and experts, two districts based on presence of true to type Fogera cattle (50%), Accessibility and presence of knowledgeable farmers (25%) and others like willingness of farmers, communal grazing land and enough land for feed development (25%) was selected. After selection, community discussion was done on points like the importance and productivity of the breed, its value for them and the need of the conservation and improvement strategy. After the consensus built with the community, farmers were selected to hold the breeding bull and serve the community. Those farmers were selected based on wealth status, cattle management ability, and presence of better educational background. And the bull was given based on written contractual agreement for four years’ service and after to make him own property.
2.5 Data analysis
The collected data was analysed by general linear model (GLM) procedure of SAS [22] software. Milk yield performance was separately analysed by using period (Period 1, 2, 3, 4, and 5), category (10 and 25 percent of the herd), and breeding group (group I, II, III, and IV) as a fixed factor. Pre-weaning growth (birth weight and weaning weight) was analysed using sex and year for nucleus herd; and district, year, sex, and season of birth for CBBPI data as a fixed factor. The following GLM models was used for birth and weaning weight for both sites.
Yijkl = µ + Bi + Dj + Xk + Sl + eijkl
Where, Yijklm = mth record of ith year, jth season, kth sex and lth parity
µ = overall mean
Bi = effect of ith year of birth
Dj = effect of jth district
Xk = effect of kth sex
Sl = effect of lth season
eijklm = random error associated with each observation
ASREML [23] a statistical package that fits linear mixed models using Residual Maximum Likelihood (REML), was used to estimate the selected genetic parameters. To fit the models based on the data (Table 1), the data was arranged in to performance data (birth weight and weaning weight) and pedigree data (animal, sire and dam ID) based on the guidance of the software. Genetic parameters were estimated for heritability and correlation for birth and weaning weight. The fixed effects (sex, season and year) were included in the mixed model after they are checked for their significance effect via GLM procedure of SAS. The variance components and heritability were estimated using a uni-variate animal model, indicated below.
Y = X b + Z1a + Z2m + Z3c + e
Where, Y is the vector of records; b is vector of fixed effects; X is incidence matrix of fixed effects; a is vector of direct additive genetic effect; m is vector of maternal additive genetic effect; c is vector of permanent environmental effect; Z1 is incidence matrix for direct additive genetic effect; Z2 is incidence matrix for maternal additive genetic effect; Z3 is incidence matrix for permanent environmental effect and e is vector of random errors
Table 1
Number of observation used for genetic parameter estimation
Type of data
|
Genetic parameter estimation
|
Birth weight
|
Weaning weight
|
Animals used
|
1497
|
1315
|
Progeny with unknown sires
|
164
|
141
|
Sire
|
55
|
53
|
Dam
|
742
|
742
|