GLOBAL JOURNAL OF ANIMAL

SCIENTIFIC RESEARCH

Journal homepage: www.gjasr.com Print ISSN:2345-4377 Online ISSN:2345-4385

Original Article

Assessment of breeding practices on dairy cows in

Samuel Shiferaw1, Zeleke Mekuriaw2, Million Tadesse1 and Dilip Kumar3

1Ethiopian Institute of Agricultural Research (EIAR), 2International Livestock Research Institute, Ethiopia 3Bahir Dar University, College of agriculture and environmental science, Ethiopia

Abstract The study was conducted in Zuria, and Yelmana Densa districts from September 2013 to October 2014, with the objective of assessing breeding practices in dairy cattle in West Gojjam zone. Interviews using pre-tested structured questionnaires administered to 180 households and 9 focus group discussions were used to generate the data on dairy cattle breeding practices in the study area. Data analysis was done using SAS (9.1) and SPSS version 20. One way ANOVA was used for milk production, ranking method and descriptive statistics (means, standard errors and percentages). The most common mating system in all sites was natural control mating. The primary breeding objective of the community was to obtain better milk yield. Milk (Index= 0.169) was the first production preference of the respondent farmers in the study area. About 53.54 % of dairy farmers in the study area preferred AI with synchronization followed by controlled natural mating (30%).Community based breeding program by incorporating indigenous knowledge of farmers is the best option in improving breeding practice of dairy cattle in the study area. Keywords: dairy cattle, breeding practice, breeding objective, West Gojjam

INTRODUCTION Livestock is raised in all of the farming systems of Ethiopia by pastoralists, agro-pastoralists, and crop-livestock farmers. According to Tsehay Redda (2001), milk production systems can be broadly categorized into urban, peri-urban and rural. The dairy sector in Ethiopia can also be categorized as traditional smallholders, privatized state farms and urban and peri urban systems (GebreWold et al., 2000) based on market orientation, scale and production intensity. In dairy cattle breeding, most of the dairy farmers in the highland, midland and the lowland areas of Ethiopia used natural mating by using indigenous breeding bull. But crossbred bull in the highland and midland agro-ecologies were used for service. Some farmers used AI

Corresponding Author: "Samuel Shiferaw Biresaw"

How to Cite this Article: Biresaw, S., Mekuriaw, Z., Tadesse, M., & Kumar, D. (2017). Assessment of breeding practices on dairy cows in west gojjam zone. Global Journal of Animal Scientific Research, 5(1), 14-29. Article History: Received: 2015-09-25 Accepted: 2015-11-29 Copyright © 2017, World Science and Research Publishing. All rights reserved

This work is licensed under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International License. 14 Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

along with natural mating in highland and midland areas. Some of the farmers also preferred seasons for mating for their dairy cattle. They mate their cows in such a way that the calving falls during the wet season to take the advantage of abundant feed supply which promotes better milk production and hence a better chance of survival of calf (Tesfa 2009). In Ethiopia, the human and animal populations are very much affected by nutritional problems; primarily due to lack of food of high nutritional value (Gebrekidan et al 2012). In order to address this problem and upgrade the nutritional status of the population, actions should be taken to improve animal production so as to ensure better supply of animal protein of high nutritive value (Ashebir 1992). Among animal protein milk is the one, whose demand continues to increase and plays a very important role in feeding the rural and urban population of Ethiopia (Asaminew 2007). Therefore, in order to meet this demand, improving the potential milk production status of indigenous dairy cattle through selection and breeding of cows by farmer’s preference traits is a practical approach for a country which lacks appropriate and standard performance recording. The objective of the study was, therefore, to assess breeding practice of dairy cattle in West Gojjam Zone, come up with pertinent and workable recommendations that could call upon decision makers and stakeholders to give the utmost attention to the breeding practices operation in the study area. Materials and Methods Description of Study Area West Gojjam is one of the ten zones in and lies between 36o 30’ to 37o 5’ Longitudes East and 10016’ to 11054’ Latitudes North. Finoteselam, capital of West Gojjam zone, is located 175 Km from Bahir Dar on the way to Addis Ababa. Bahir Dar, Bure, Finoteselam and Adet are some of the major towns in the zone. The total land area of the zone is 13,280km2. Out of these, cultivated land accounts 11.3%, grazing land 8.2%, natural forest 3.4%, plantation forest 16.5%, and woodland 8.5%, shrubs 2.6% and swampy land 33.2%. Zonal elevation difference accounts about 14% of less than 1500 m a.s.l., followed by 76% between 1500 – 2500. The remaining 9% is an altitude between 2500 – 3500 m.a.s.l. Most of the districts (75%) in the zone have ambient temperature ranges of 15 – 20 0C and the remaining (17%) have 20 – 27 0C. West Gojjam zone is one of food secured zones in the region with the least aid dependency ratio. On the other hand, the zone has suffered from high soil erosion and high soil nutrient depletion; as a result some of the areas are becoming more dependent on inorganic fertilizers. The zone is the origin of 9 prominent rivers such as , Gilgel-Abay, Bir, Fetem, Beles, Debohil, Zema, Ayehu and GilgelBeles. There are also many tributaries of Blue Nile (LIVES base line data; 2013). Bahir Dar Zuria, Mecha and Yilmanadensa districts were selected for four commodity intervention by LIVES project (Figure 3.1). Agro-ecologically, these districts have predominantly ‘Moist Weinadega’ and ‘Wet Weinadega’ zones. The annual rainfall ranges from 1,617-1,791mm from the highest areas of and Mecha down to the lowest area of Bahir Dar Zuria district (1,272 – 1,397mm). Of the three LIVES intervention districts, Yilmana Densa is one of undulating topography and mountainous than Mecha and Bahir Dar Zuria. The predominant soil type for Mecha and Bahir Dar Zuria is Chrmic Lumisols. Whereas for Yilmana Densa the major soil type is Eutrivertisols. Eutrivertisols is the least proportion for the two districts. 15 Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Source: LIVES base line data; 2013 Figure 3.1: Map of 3 LIVES intervention districts in West Gojjam Zone

Source: LIVES base line data; 2013

Figure 3.2: West Gojjam zone cluster Districts Biophysical charters Map Most of the highest (19 – 210C) temperature areas are found in Bahir Dar Zuria following the Blue Nile River down to TisAbay, whereas, the lowest temperature areas are around the other edge of Yilmanadensa district that ranges from 10 -140C. Most of the areas in Mecha district have temperatures ranging from 17-180C (Figure 3.2) (LIVES base line data; 2013) The study sites were selected as per the potential of dairy and which were the focus areas of

the LIVES Project 16 Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Survey Sampling and Methods of Data Collection Based on their milk shed potentiality and AI practice, 9 rural kebeles were purposively selected from each of the three districts and twenty household per rural kebeles for questionnaire administration. A total of 180 respondents (60 from each district) were randomly sampled for the interview from the selected rural kebeles. Data were generated by administrating a structured questionnaire, group discussions and from secondary sources. Questionnaire Administration A structured questionnaire was prepared and pre-tested before administration and some re- arrangement, reframing and correction in accordance with respondents’ perception were made. The check list was administered to key informants, AI technicians, professionals and group discussions and to the randomly selected household heads by a team of enumerators recruited and trained for data collection purpose with close supervision of the researcher. The relevant information from AI technician data sheet was collected. Information on the farm, management practices, and inseminated cow and AI related services were recorded. Information on the socio-economic characteristics of the farmers, breeding practice (selection criteria, routine husbandry practices), factors like cattle breed, production system, parity, heat detection techniques, milk production, state of lactation, time of AI, distances from the AI center and status of AI technician was assessed A group discussion was held in each of three selected rural kebeles i.e. three rural kebeles in each district and totally 9 rural kebeles. The group was composed of youngsters (3), women (3), village leaders (4) and socially respected individuals (3) who are known to have better knowledge on the present and past social and economic status of the area. Group discussions were focused on the history of the breeding practices of dairy cows, utility pattern of the dairy cows and AI services, current status and major constraints of the AI services, major reproductive problems of dairy cows after AI, production system, indigenous knowledge on management of breeding and husbandry practices.

Methods of Data Analysis All the data were fed to Ms-Excel (2010). Analysis was done by using SPSS version 20 and SAS (9.1). The result was summarized and presented by using descriptive statistics (means, standard errors and percentages). Qualitative data obtained from survey was analyzed using SPSS, and one way ANOVA for milk production. Production preference was by ranking method. The following formula was used to compute index as employed by Musa et al (2006):

Index = Rn × C1 + Rn-1 × C2 ... + R1 × Cn/ ( Rn × C1 + Rn-1× C2 + ... + R1 × Cn)

th Where, Rn = the last rank (example if the last rank is 8 , then Rn = 8, Rn-1 = 7, R1 = 1). Cn = the % of respondents in the last rank, C1 = the % of respondents ranked first Result and Discussion Household Resources Household Characteristics

One hundred eighty households (sixty households per district) were considered in this household survey study. The family size, educational status and age group per household in the study areas are shown in Table 3.1, Table 3.2 and Table 3.3, respectively. The average 17 Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

family size per household in Bahir Dar Zuria, Mecha and Yelmana Densa districts were 6.3, 5.9 and 6.0 persons, respectively, with the overall mean of 6.1 persons per family. Table3. 1: Household size in Bahir Dar Zuria, Mecha and Yelmana Densa districts Districts N Mean S.D Bahir Dar Zuria 60 6.30 1.925 Mecha 60 5.90 1.504 Yelmana Densa 60 5.98 1.692 Total 180 6.06 1.715

The average household size observed in this study is smaller than that reported by Asaminew (2006) who found that the overall mean household size in Bahir Dar Zuria and Mecha districts was 7.71 persons. However, it is larger than that of Getachew (2002) who found an average household size of 5.6 persons in Ginchi highlands. The proportion of children and young persons (below 25 years of age) in the study area was 3.5 Percent, while that of older people (over 66 years of age) was 8.6 percent. The proportion of the middle age group in the area (25-45 years of age) was 65 percent. In this study, higher proportion of the population was in working age, which is important to undertake agricultural activities. The educational status of the respondent family members in the study site is indicated in Table 3.2. The proportion of literate family members (who are able to read and write and attending formal education) exceeds the proportion of those who are illiterate (not able to read and write and attending formal education). So, the relatively higher literacy level observed per household in the study area can provide a better opportunity to implement agricultural practices and efficient resource use. Females were more illiterate than males in all three study districts.

Table3. 2: Education Status of the Bahir Dar Zuria, Mecha and Yelmana Densa districts

Education level BDZ(N=280) ME(N=275) YD (N=309) Total(N=864) Male illiterate 2.10% 0.72% 3.20% 2.10% Male1-7education level 17.1% 18.0% 19.4% 18.3% Male8-12education level 14.3% 16.3% 18.4% 16.4% Male >12 education level 20.0% 19.6% 16.5% 18.6% Female illiterate 9.30% 11.3% 11.3% 10.6% Female 1-7 education level 13.6% 12.0% 11.3% 12.3% Female 8-12 education level 13.6% 11.3% 14.2% 13.1% Female >12 education level 10.0% 10.5% 5.50% 8.50% Total illiterate 11.4% 12.0% 14.6% 12.7% Total 1-7 education level 30.7% 30.2% 30.7% 30.6% Total 8-12 education level 27.9% 27.6% 32.7% 29.5% Total >12 education level 30.0% 30.2% 22.0% 27.2% BDZ=Bahir dar Zuria; ME=Mecha; YD=Yelmana Densa; N=number of sampled population

18

Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Table3. 3: Age group classification in Bahir Dar Zuria, Mecha and Yelmana Densa districts Age (year) Frequency (N=180) Percent Cumulative below 25 7 3.88 3.88 25 to 35 55 30.56 34.44 36 to 45 62 34.44 68.88 46 to 65 39 21.67 90.56 over 66 17 9.44 100.00

Land Holding, Land Use Pattern and Land Holding Trend Table4.4, Shows the land holding, land use pattern per household in the study area. Overall average land holding of respondents for own land, rented land and communal land were 0.8, 0.21 and 2.08 hectares, respectively. Average land holding per household in Bahir Dar Zuria, Mecha and Yelmana Densa districts were (0.75, 0.27, 2.19), (0.79, 0.13, 1.95), and (0.88, 0.13 and 2.04) hectares per household for own land, rented land and communal land, respectively. The overall land holding per household observed in the study area is smaller than that reported by Getachew (2002) in Ginchi highlands of Ethiopia, which was 2.5 hectare. The land holding and land use pattern in the present study was not significantly different among districts. Table3. 4: Land holding pattern of the Bahir Dar Zuria, Mecha and Yelmana Densa districts in hectare Crop Crop Grazing Grazing Irrigated Irrigated Total Total Total Districts Own Rented Own Communal Owned Rented Own Rented Communal N 60 16 20 56 29 31 60 35 57 BDZ Mean 0.56 0.13 0.13 2.21 0.13 0.24 0.75 0.27 2.19 S.D 0.12 0 0 0.67 0.00 0.03 0.21 0.08 1 N 60 19 47 44 31 - 60 19 44 Mecha Mean 0.63 0.13 0.13 1.95 0.13 - 0.79 0.12 1.95 S.D 0.13 0 0 0.68 0 - 0.17 0 1 N 32 10 24 28 4 - 30 10 28 YD Mean 0.75 0.13 0.13 2.04 0.13 - 0.88 0.12 2.04 S.D 0.17 0 0 0.88 0 - 0.17 0 1 N 152 45 91 128 64 31 150 64 129 Total Mean 0.63 125 0.13 2.08 0.13 0.24 0.80 0.21 2.08 S.D 0.15 0 0 0.72 0 0.03 0.19 0.09 1 N=number of households; S.D= Standard deviation; DBZ=Bahir Dar Zuria; YD=Yelmana Densa

Most of the respondents in Bahir Dar Zuria (60%), Mecha (60%) and Yelmana Densa (66.7%) districts revealed that the land holding trend was significantly decreasing since the past five years (Table3.5). Especially in Yelmana Densa district, larger proportion of the respondents perceived that land holding is decreasing more than in Bahir Dar Zuria (60%) and Mecha (60%) districts. But the remaining respondents in both districts perceived that the land holding trend is as it was before, even though they expressed fear of decreasing

landholding size at unexpected period of time due to alarmingly increasing human population in the area. This finding is the same as reported by IUCN (1990), which predicted that per

capita land holdings in Ethiopia will decline from an average of 1.76 ha in 1985 to 0.66 ha in 19 the year 2015. Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Table3. 5: Land holding trend for the last five years in Bahir Dar Zuria, Mecha and Yelmana Densa districts Land holding trend BDZ (N=60) Mecha (N=60) Y D (N=60)

No change (%) 40 40 33.3 Decreasing (%0 60 60 66.7 Total (%) 100 100 100 BDZ=Bahir Dar Zuria;YD=Yelmana Densa;N=number of households

Husbandry Practices Production Objectives of Cattle Keeping In this study, it was found that the first and second priority functions of cattle were milk production and draft power, respectively (Table 3.6). The use of cattle for meat production and as a source of income ranked third and fourth, respectively. On the other hand, functions of cattle such as manure production and use for threshing cereal grains ranked fifth. The result obtained in this study is comparable with the results of other authors (Alganesh, 2002; Solomon, 2004; Zewdu, 2004). Despite the fact that draft power stood second next to milk production as a priority, draft power is an important function of cattle, since draft power from other livestock species was not used in the study area. This result is not in conformity with that of Asaminew (2007). The first important breeding objective stated by the sampled farmers in each study site was obtaining better milk yield (Table 3.7, 3.8 and 3.9). This is similar to the results of a previous study by Zewdu (2004). Milk was mentioned as one of the most important functions of the local cattle and one of the primary reasons for keeping indigenous cattle. An increase in milk yield will bring additional income from the sale of butter. More milk production also means better-fed calves that will have better pre- and post-weaning survival rates. These calves will also grow faster and hence reach puberty earlier thus reducing age at first calving (Zewdu et al., 2006). Similarly, Piotr et al (2004) also reported that recently the cattle breeding objective are focused on the increase of milk yield, under the assumption that profit would increase with increased yield per cow. Production circumstances have given rise to interest in directly reducing cost of production, and breeding objectives are moving from increasing yield to increasing economic efficiency.

Table3. 6: Aggregate Production objectives rank in the study area Production objectives Most imp Imp Least imp Not imp Index Rank Milk 56 101 22 1 0.169 1 Meat 14 121 35 10 0.148 3 Drought power 40 80 40 20 0.148 3 Income 0 77 91 17 0.1597 2 Asset accumulation 9 89 64 18 0.122 7 Socio-cultural value 2 73 83 22 0.123 6 Manure 35 113 26 6 0.12 5

20

Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Table3. 7: Bahir Dar Zuria, production objective of keeping livestock Production objectives Most Imp. Imp. Least imp. Not imp. Index Rank

Milk 16 39 5 0 0.174 1 Meat 0 49 5 6 0.149 3 Drought power 24 4 18 14 0.144 4 Income 0 27 32 1 0.170 2 Asset accumulation 11 27 19 3 0.111 7 Socio-cultural value 0 12 43 5 0.116 6 Manure 13 41 5 1 0.133 5 Imp. Important Milk (Index=0.174) was the first preference in all of Bahir Dar Zuria, Mecha and Yelmana Densa districts, and it was the primary preference of keeping livestock as the same as the aggregate rank indicated on Table 8. Income (index= 0.170) was also the second production preference in Bahir Dar Zuria and Yelmana Densa (index= 0.157) districts. Whereas in Mecha district income (index= 0.153) was the third rank and drought power (index= 0.154) was the second. The fourth rank of production preferences was meat (Index= 0.149) and drought power (Index= 0.147) in Bahir Dar Zuria and Yelmana Densa districts, respectively. Drought power, meat and meat were the fourth rank of production preference in Bahir Dar Zuria, Mecha and Yelmana Densa districts, respectively. Production preference varied from district to district which may be due to the living style of the respondents and the need of products by the consumers. For example, in Bahir Dar Zuria, meat is the second preference next to milk production. This indicates that more meat is consumed by urban dwellers in Bahir Dar city and around than in small town like Adet and Merawi. Table3. 8: Mecha production objective of keeping livestock Most Least Not Production objectives Important Index Rank important important important Milk 10 40 9 1 0.155 1 Meat 3 51 4 2 0.152 4 Drought power 14 30 16 0 0.154 2 Income 0 34 26 0 0.153 3 Asset accumulation 0 21 35 4 0.119 7 Socio-cultural value 0 33 24 3 0.130 6 Manure 0 56 4 0 0.134 5

Table3. 9: Yelmana Densa production objective of keeping livestock Production objectives Most important Important Least important Not important Index Rank Milk 30 22 8 0 0.181 1 Meat 0 43 12 5 0.142 4 Drought power 2 46 6 6 0.147 3 Income 0 16 33 11 0.157 2

Asset accumulation 9 19 24 8 0.134 5 Socio-cultural value 2 28 16 14 0.124 6

Manure 22 16 17 5 0.112 7 21

Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Milk Production Performance The daily milk yield, lactation length and milking frequency of local and crossbred cows in the study area are shown in Table 3.10. Average daily milk yield of local cows was 2.62, 2.02 and 1.86 liters for Bahir Dar Zuria, Mecha and Yelmana Densa districts, respectively, with an overall average of 2.26 liters. The average daily milk yield of 50% Jersey crossbred cows was 8.34, 7.85 and 8.42 liters for Bahir Dar Zuria, Mecha and Yelmana Densa districts, respectively with an overall average of 8.2 liters. The average daily milk yield of 50% Frisian crossbred cows was 13.63, 12.12 and 12.30 liters for Bahir Dar Zuria, Mecha and Yelmana Densa districts, respectively with an overall average of 12.68 liters. There is significance difference (P-value<0.05) both in genotype and within districts except for the local breeds. The reported average daily milk yield of local cows in the present study is consistent with the value reported by ILDP (2004), which was 4 liters and CSA (2013) which was 1.32 liters for the country. Similarly, Zewdu (2004) indicated that the overall average daily milk yield of local cows in the first and second lactations in North Gonder Zone was 1.69 and 1.86 liters, respectively. The overall average lactation length of local, 50% Jersey crossbred, and 50% Frisian crossbred cows were 5.12, 6.68 and 6.61 months, respectively in the study area (Table3.10). The lactation length of the indigenous (local) cows, 50% Jersey crossbred, and 50% Frisian crossbred cows observed in this study is lower than the national average of 6 months (CSA, 2013). The lactation length in crossbred cows observed in this study is significantly shorter than the lactation length of 11.7 months reported for crossbred cows in the central highlands of Ethiopia (Zelalem and Ledin, 2001). In general, the lower average daily milk yield per cow and the variation in lactation length in the present study may be attributed to disease problem, feed shortage and poor genetic potential of the sample population.

Cattle Housing and Cleaning Practices All of the farmers in the study areas used separate house for their cows. Abebe Belay (2012) reported contrary results that 90.8% of the households shared the same house with their animals, while 9.2% of the households used separate houses for their cows in Ezha district of Gurage zone in southern Ethiopia. Clean, dry and comfortable bedding materials are important to reduce the growth of microorganisms. About 62.8 % of smallholder households used grass or cereal straw as bedding material, while 37.2 % didn’t use any bedding material. Maintaining the sanitary condition of milking area is important for clean milk production. In the study area, 83.8 % of the farmers clean dairy house daily while 16.2 % of farmers clean three times in a week. Zelalem Yelma (2010) reported comparable result that 87% of the respondents cleaned their barn daily, 9 % clean once or twice in a weekend 4% did not clean at all in central highland of Ethiopia. Breeding Practices and Breeding Programs Breeding practice The breeding practice in this finding, the farmers preferred was AI with synchronization followed by natural mating. But as Godadaw Misganaw et al. (2013), in North Gondar area was mostly natural mating but AI also rarely practiced. Bulls can be used for two main types of natural mating, either free mating in the range or controlled mating. In the former system,

heat detection is carried out by the bull and cows in heat are usually mated several times during each heat period. In controlled mating systems, heat detection is carried out by the farmer and each cow is mated once or twice during each heat period. 22 Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Table3. 10: Milk production of dairy cattle in Bahir Dar Zuria, Mecha and Yelmana Densa districts Districts MYL MYJ MYF LLLC LLJC LLFC MFLC MFJC MFFC (L/day) (L/day) (L/day) (months) (months) (months) BDZ Mean 2.62a 8.34a 13.63a 5.43a 6.62a 6.82a 2 2 2 (N=60) S.E 1.21 0.62 0.92 0.45 0.49 0.38 0.00 0.00 0.00 Mecha Mean 2.02a 7.85b 12.12b 4.69b 7.03b 6.24b 2 2 2 (N=60) S.E 0.86 0.69 1.44 0.47 0.24 0.69 0.00 0.00 0.00 YD(N=60) Mean 1.86a 8.42a 12.30b 5.25a 6.39a 6.77a 2 2 2 S.E 0.89 0.62 0.89 0.49 0.49 0.43 0.00 0.00 0.00 Overall Mean 2.26 8.20 12.68 5.12 6.68 6.61 2 2 2 (N=180) S.E 1.00 0.69 1.29 0.57 0.49 0.58 0.00 0.00 0.00 P-value 0.13 < 0.001 0.001 0.01 0.001 0.001 - - - MYL=milk yield of local breed cow; MYJ= milk yield of 50% Jersey crossbred cow; MYF= milk yield of 50% Frisian crossbred cow; LLLC= lactation length of local bred cow; LLJC= lactation length of 50% Jersey crossbred cow; LLFC= lactation length of 50% Frisian crossbred cow; MFLC= milking frequency of local cow; MFJC= milking frequency of 50% Jersey crossbred cow; MFFC=milking frequency of 50% Frisian crossbred cow and L/day=liters per day. The same superscript letters with a column are not significant (P>0.05) Source; 2014 survey result; the milk production was taken by asking the dairy farmers not by monitoring

Table3. 11: Types of housing in the study area Variables BDZ Mecha Y.D Total N % N % N % N % Types of housing Housed 60 100 60 100 60 100 180 100 Fenced ------Bedding materials used grass and/or cereal straw 43 71.7 31 51.7 39 65 113 62.8 no bedding material 17 28.8 29 48.3 21 35 67 37.2 Barn cleaning Frequency Daily 46 76.7 54 90 51 85 151 83.8 Three times a week 14 23.3 6 10 9 15 29 16.2

Majority of the respondents (95 %, 97% and 94.6 % from Bahir Dar Zuria, Mecha and Yelmana Densa districts, respectively) reported that castration is common breeding management practice for male animals (Table 3.12). The farmers report from Bahir Dar Zuria (BDZ) district also indicates that, there were different reasons for castration activity. The first major reason (62.8%) was to make bulls tame for different farming activities; second reason (22.8%) was to avoid the difficulty with breeding bulls running around for mating. The third reason (14.4%) was to remove unwanted bulls from mating (Table 4.12). In mating type, three alternatives were presented to the sampled households. In BDZ district 62.8 % of the respondents practice natural controlled mating, which means bulls were selected and allowed to mate cows; around 22.8% of them reported the use of free mating, which means there was no selection of breeding bulls. This result is similar to the trend reported by Azage et al. (2009) in highland zebu cattle in Metema district. The remaining 14.4% of the sampled households in BDZ district reported use of AI technology through AI

technicians (Table 3. 12). However, in Mecha district natural mating was reported by 80% of

sampled households especially natural controlled breeding takes place. In Yelmana Densa 23 Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29 district, 61.5 %, 27 % and 11.5 % of respondents reported practice of natural controlled mating, natural free mating and AI technologies, respectively (Table3. 12).

Table4. 12: Reported percentage of weaning, castration and mating practices by district Management practice BDR Mecha YD

Weaning practice Yes 26.6 96.6 62.9 No 73.4 3.42 37.1 Castration practice Yes 95 97 94.6 No 5 3 5.4 Reason for castration Tame bulls for farming activity 62.8 - - Avoid running around mating 22.8 - - Remove unwanted bull from mating 14.4 - - Mating type Natural control (%) 62.8 82 61.5 Natural uncontrolled (%) 22.8 - 27.0 AI (%) 14.4 18 11.5 Is mating seasonally restricted Yes 70.0 30.0 87.5 No 30.0 70.0 12.5 BDR=Bahir Dar Zuria;YD=Yelmana Densa Most of the farmers in Yelmana Densa districts also report that mating was seasonal. It occurs from September to January. There are several reasons that emerged from the focus group discussion and individual farmer interviews as to why mating tends to be seasonal in these two districts: 1) availability of good pasture grass; 2) less fly and insect burden during this period, and 3) breeding bulls have less work burden and have more time to stay with breeding cows. Farmers also mentioned that cows also manifest more signs of heat during this time. But reported frequencies of seasonality of mating vary between districts, from 30% in Mecha to 87.5% in Yelmana Densa (Table3.12). This may be due to the districts availability of feed and water, agro ecology and other factors. It was also noted from the individual farmer interviews and the focus group discussions that obtaining the desired type of breeding bulls has become increasingly difficult in the study area. The farmers reported to use a mix of three sources of breeding bulls – their own herd, bought and neighbors – at different proportions between the districts. This agrees well with the earlier report by Zewdu Wuletaw et al. (2006), who found out that the majority of farmers in north western Ethiopia obtain their replacement breeding animals from their own farm and from their relatives and neighbors. Own bull means a bull obtained or produced within their own herd. Neighbor’s bull is obtained in their surrounding and available in communal grazing lands. Bought (market) bulls are obtained from the market, which is used either by bringing estrous cow to the market where bulls on sale are available, or buy the bull and bring it to the herd. In BDZ and YD districts, farmers primarily use their own bull. In Mecha, farmers primarily rely on bulls from neighbors as well as their own home-bred bulls.

Cause for Reduced Outcomes from Artificial Insemination 24 The second reason for artificial insemination failure in the study area was distance of AI center (Table3.13) from the respondent’s village and because of the time taking process to Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29 arrive the AI site while cows/heifers are still in heat. The first reason was heat detection problem. During focus group discussion, respondents had critical problem of observing the cow in heat status and then no one could see the cow/heifer in estrus. And the third one was the AI technician inefficiency, as reported from BDZ and Mecha districts (Table 4.13)

Table3. 13: Reasons of AI Failure and Breeding Practice according to respondents View Districts Reasons of AI failure Over all(N=180) BDZ(N=60) Mecha (N=60) YD (N=60) Heat detection problem (%) 25 55.56 42.86 37.38 AI technician efficiency (%) 23 0.00 6.12 11.21 Distance of AI center (%) 25 44.44 44.89 24.20 Absence of AI technician (%) 10 6.12 0.00 6.54 Disease problem (%) 18 0.00 0.00 9.35 Breeding practice

AI with synchronization (%) 60 46.67 55 53.54 AI only (%) 32 11.11 6.67 16.11 Natural mating (%) 8 43.33 25.55 30 BDR=Bahir Dar Zuria; YD=Yelmana Densa;N= number of households

Breeding Objective Breeding objective is defined as the reason (s) for which animals are specifically bred for, assuming that farmers have made a deliberate choice to genetically improve the next generation of animals in terms of their performance in relation to their parent generation. The focus is therefore on one or more traits. The objectives are likely to be affected by the cost of production and the revenue from product sales related to a genetic change in the target trait. Cattle in the northern Amhara have multipurpose functions. These include traction, milk production, income generation, manure, reproduction and meat production (Zewdu Wuletaw et al., 2006). The current study also tried to explore the expressed and perceived breeding objectives of the community by emphasizing on milk production. The first important breeding objective stated by the sampled farmers in each study site was obtaining better milk yield (Table3.14). This is similar to the results of a previous study by Zewdu Wuletaw (2004). Milk was mentioned as one of the most important functions of the local cattle and one of the primary reasons for keeping indigenous cattle. An increase in milk yield will bring additional income from the sale of butter. More milk production also means better-fed calves that will have better pre- and post-weaning survival rates. These calves will also grow faster and hence reach puberty earlier thus reducing age at first calving (Zewdu Wuletaw et al., 2006). Similarly, Piotr et al (2004) also reported that recently the cattle breeding objective are focused on the increase of milk yield, under the assumption that profit would increase with increased yield per cow. Production circumstances have given rise to interest in directly reducing cost of production, and breeding objectives are moving from

increasing yield to increasing economic efficiency. Secondly, in addition to increasing milk production, obtaining of good breeding bull, and plough ox, good mothering ability and shortening of calving intervals were aimed at the same time. The farmers believed that good 25 breeding bull brings gross improvement through natural control mating system. Keeping Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

desirable bulls can contribute to improve herd performance over time. Since the farming system of the area is mixed crop-livestock, bulls are needed in different farming activities. Alongside increasing milk production, getting the suitable plough oxen was examined. Mothering ability of the cow is also taken into consideration. Docility of the dairy cow at the time of milking and any management aspect is also considered important. The sampled households were also keen to have more number of calves per cow. This is obtained through shortening of calving interval. They believe that shortening of calving interval is achieved by selecting for ancestors that have short calving interval and applying the tools of genetic improvement with the proper management system. Coat color is also taken in to account at the time of setting the breeding objective. This is not only for eye pleasure but also for higher market value. Table3. 14: Frequency of reported reasons for breeding cattle in the study area by district Traits in Breeding objective BDZ Mecha Yelmana Densa Better milk yield 27.5 34.9 45.3 Shorter calving interval 11.8 12.1 - Getting good breeding bull 17.6 31.3 18.8 Draught power 12.7 8.40 16.98 Coat color 5.9 7.20 - Mothering ability 13.7 2.40 13.2 butter yield 3.90 3.60 - Getting marketable animals 6.90 - 5.60 Achieving breeding objectives Yes 40.0 13.3 27.0 Partially 50.0 13.3 61.5 No 10.0 73.4 11.5

The success of following stated breeding objectives was also assessed. Only 40 % of the respondents stated that they achieved their planned breeding objectives in full and another 50 % said they partially achieved them in BDZ district (Table 3.14). Only 10 % of the respondents in BDZ district said that they have difficulty to realizing breeding objectives, due to scarcity of feeds, presence of disease, parasites, biting insects and lack of proper management. In Mecha district due to a serious feed scarcity, around 73.4 % of the respondents said they have not achieved the stated breeding objectives. However, in Yelmana Densa district 61.5 % of the sampled households indicated partial achievement of the desired breeding objectives (Table 4.14). Record Keeping Record keeping was taken from each districts of the study area during the survey session even though the record keeping was not incorporated all the necessary records; the records seen at the time of survey was Price of purchased cattle, medication cost, milk production. As the Table 4.15 indicated that, 7.6%, 11.2% and 17.5% of dairy farmers practiced the record keeping in Mecha, Yelmana Densa and Bahir Dar Zuria Districts respectively. The better record keeping was found to be in Bahir Dar Zuria district and this might be due to the district’s location nearby Bahir Dar city and Andasa livestock research center which create

farmers awareness of record keeping significance.

26

Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Record keeping among the study districts Districts Record keeping Bahir Dar Zuria Yelmana Densa Mecha Total N=60 N=60 N= 60 N=180 Practiced 17.5% 11.2% 7.6% 12.1% Not practiced 82.5% 88.8% 92.4% 87.9%

Conclusion and Recommendation It can be concluded that farmers in the study area preferred AI with synchronization followed by natural mating. Natural controlled mating was common practice and bulls were selected and allowed to mate cows. Majority of the respondents in the study districts reported that castration was common breeding management practice for male animals. Obtaining the desired type of breeding bulls has become increasingly difficult in the study area. Milk yield is the most important trait preferred and criteria for selecting a dairy breed based on individual performance and pedigree selection. Breeding decisions of smallholder dairy producers in the study area match producers’ multiple objectives. Community based breeding program by incorporating indigenous knowledge of farmers is the best option in improving breeding practice of dairy cattle in West Gojjam Zone. Acknowledgement This study is part of a graduate study at Bahir Dar University, Ethiopia. The Ethiopian Institute of Agricultural Research is acknowledged for providing study leave during the study time. The LIVES project (ILRI) provided finance for the conduct of this thesis research work.

REFERENCES Abebe Belay, Zelalem Yilma and Abjebu N, 2012. Hygienic and microbial quality of raw whole cow’s milkproduced in Ezha district of the Gurage zone, Southern Ethiopia Addis Getu And Godadaw Misganaw, Campus, S. 2014. A review on dairy cattle improvement practices based on conformation. Journal of harmonized research (johr): 2(4), 314–327. Alemu GebreWold, Alemayehu Mengestu, Solomon Demeke.2000. Status of dairy research in Ethiopia. In the role of village dairy co-operatives in dairy development. Smallholder Dairy Development Project (SDDP) Proceeding, Ministry of Agriculture (MOA). Addis Ababa, Ethiopia. Alganesh Tola, 2002. Traditional milk and milk products handling practices and raw milk quality in Eastern Wollega. M.Sc. Thesis, Alemaya University. Dire Dawa, Ethiopia. 108p. Asaminew Tassew. 2007. Production, Handling, Traditional Processing Practices and Quality of Milk in Bahir Dar Milk Shed Area, Ethiopia. M.Sc. Thesis School of graduate studies, Alemaya University. Asheber Sewalem 1992 Evaluation of the reproductive and pre-weaning growth performance of Fogera and their F1 Fresian crosses at Andassa Cattle breeding station, Ethiopia. M.Sc. Thesis, Alemaya University, Ethiopia. Azage Tegegne, Eshete Dejen, Dirk Hoekstra and Worku Teka. 2009. Matching Genotype with the Environment Using Indigenous Cattle Breed: Introduction of Borana Cattle from Southern Ethiopia into the Lowlands of North-Western Ethiopia. A paper presented

at the FAO/IAEA Symposium on Sustainable Improvement of Animal Production and 27 Health 8-11 June 2009, Vienna, Austria. pp. 29-38 Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Charfeddine N.2000. Economic aspects of defining breeding objectives in selection programmes. ciheam-iamz, Options Méditerranéennes : Série A, 43:9-17. CSA. 2013. Federal Democratic Republic of Ethiopia Agricultural Sample Survey. Livestock and Livestock Characteristics Bulletin, Volume II, Central Statistical Authority, Addis Ababa, Ethiopia. Dejene Takele Gebissa. 2014. Assessment of Dairy Cattle Husbandry and Breeding Management Practices of Lowland and Mid-Highland Agro-Ecologies of Borana Zone. Animal and Veterinary Science 2(3); 62-69. Desalegn Gebremedhin, 2008. Assessment of Problems / Constraints Associated with Artificial insemination service in Ethiopia. M.Sc. Thesis. Addis Ababa University Faculty of veterinary medicine, Debre Zeit, Ethiopia. Gebrekidan Tesfay, Zeleke Mekuriaw, Gangwar S K and Aklilu Hailemichael 2012 Socio- economic characteristics and purpose of keeping dairy cattle in central zone of Tigray, northern Ethiopia. International Journal of Advanced Biological Research, Volume 2(2) 2012: 256-265p GebreWold Amha, Alemayehu Mengistu, Demeke Solomon and Tadesse Amare. 2000. Status of dairy research in Ethiopia. In The role of village dairy co-operatives in dairy develop ment.Smallholder Dairy Development Project (SDDP) Proceeding,Ministry of Agriculture (MOA). Addis Ababa, Ethiopia. Getachew Eshete .2002. An assessment of feed resources, their management and impact on livestock productivity in the Ginchi watershed Area. M.Sc. Thesis. Alemaya University, Alemaya. 172p. Godadaw Misganaw, Zewdu Wuletaw and Workneh Ayalew, 2014. Breeding practices in indigenous dairy cattle breeds in Northern Amhara, Ethiopia. Livestock Research for Rural Development 26(4). 53-55. ILDP (Integrated Livestock Development Project).2004. Study report on dairy marketing and mini-dairy in Gonder (Draft Report), North Gonder. 35p. IUCN.1990. Ethiopian National Conservation Strategy. Phase I Report.18 International Union for the Conservation of Nature, Addis Ababa, Ethiopia. Laval, G. and Assegid Workalemahu, 2002. Traditional Horro cattle production in Boji district, west Wolloga, Ethiopia. Ethiopian Journal of Animal Production. 2(2)-97-114. LIVES. 2013. Zonal diagnosis and intervention plan West Gojjam, Amhara. Mukasa-Mugerwa, E., 1989. A review of reproductive performance of Bos indicus cattle. ILCA Monograph No. 6, International Livestock Center for Africa (ILCA), Addis Ababa, Ethiopia. Piotr G, Krzysztof M, Zygmunt H and Ewa D. 2004. Heritability’s of and genetic and phenotypic correlations between condition score and production and conformation traits in Black-and-White cows. Pp89. Rege, J.E.O., 1998. Utilization of exotic germplasm for milk production in the tropics Proc. 6th World Cong. On Genetics Applied to Livest. Prod. 25:193-200. SAS, 2003. SAS User’s Guide: Statistics. Ver.9.1. Cary, NC: Statistical Analysis System Inc. Solomon Bogale .2004. Assessment of livestock production systems and feed resources base in Sinana and Dinsho districts of Bale highlands, southeast Oromia. M. Sc. Thesis. Alemaya University Alemaya. Dire Dawa, Ethiopia. 141p. SPSS (Statistical Package for Social Sciences). SPSS ver.20.0 Application Guide. SPSS Inc.

Tadesse Amare, Zeleke Mekuriaw, and Birhanu Belay. 2014. Status and constraints

evaluation of artificial insemination in cattle in the three selected districts of Western 28 Page Samuel Shiferaw, Zeleke Mekuriaw, Million Tadesse and Dilip Kumar

GLOBAL JOURNAL OF ANIMAL SCIENTIFIC RESEARCH, 5(1), 14-29

Gojjam Zone; Amhara Region, Ethiopia. African Journal of Animal Production and Husbandry 1 (2), 020-028. Tesfa Gebremicheal 2009 Reproductive performance of indigenous dairy cattle in south Wollo. MSc Thesis, Mekelle University, Ethiopia. 65p. Tsehay Redda. 2001. Small scale milk marketing and processing in Ethiopia. In Proceedings of the South-South Workshop on Smallholder Dairy Production and Marketing, Constraints and Opportunities, Anand, India. March 12-16. Yitaye Alemayehu, Azage Tegegne and Mohamed Yesuf Kurtu, 2001. The livestock production systems in three peasant associations of the Awassa Woreda. pp. 155-167. In: Proceeding of the 8th Annual Conference of the Ethiopian Society of Animal Production (ESAP). 24-26 August, 2000, Addis Ababa, Ethiopia. Zelalem Yilma and Ledin Inger,. 2001. Milk production, processing, marketing and the role of milk and milk products on smallholder farmers’ income in the central highlands of Ethiopia. pp. 139-154. In: Proceedings of the 8th Annual Conference of the Ethiopian Society of Animal Production (ESAP). 24-26 August, 2000, Addis Ababa, Ethiopia. Zelalem Yilma, 2010. Quality Factors that Affect Ethiopian Milk Business: Experiences from selected dairy potential areas. Netherlands Development Organization, Addis Ababa, Ethiopia. Zewdu Wuletaw, 2004. Indigenous cattle genetic resources, their husbandry practices and breeding objectives in North-western Ethiopia. M.Sc. Thesis. Almaya University of Agriculture, DireDawa, Ethiopia. 127p. Zewdu Wuletaw, Workneh Ayalew and Sölkner J. 2006. Breeding scheme based on analysis of community breeding objectives for cattle in north-western Ethiopia. Ethiopian Journal of Animal Production 6(2): 53-66p.

29 Page