Livestock Research for Rural Development 27 (8) 2015 Guide for preparation of papers LRRD Newsletter

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Participatory definition of trait preference and pastorals’ indigenous knowledge on goat breeding strategy around Aysaita district, Ethiopia

Feki Misbah, Berhanu Belay1 and Aynalem Haile2

Afar Pastoral and Agropastoral Research institute (APARI), P.O.Box10, Awash 7 killo, Ethiopia
1 Jimma University, P.O. Box 378, Jimma,
2 Ethiopia International Center for Agricultural Research Development (ICARDA), P.O. Box 5466, Aleppo, Syria


Characterization is the first step in any breed improvement and conservation strategy. This study was undertaken in Afar Region, Aysaita District with the aim of documenting preferred traits and indigenous knowledge of the community on goat breeding management that can be an input for improving performance of the breed. Stratified random sampling techniques were employed to select peasant associations and households. Participatory Rural Appraisal (PRA) tools and semi-structured questionnaireswere employed to collect data. A survey was conducted with 124 respondents (83 from two pastoral and 41 from one agropastoral PAs). Descriptive statistics were employed to analyze the data. Indexes were calculated for all ranking data.

The survey results showed that most preferred traits to be improved were milk yield (I=0.35), drought tolerance (I=0.14), fertility (I=0.103) and adaptation traits (I=0.097) for female goats, while body size and conformation (I=0.35) as well as coat color (I=0.20) were favored for males. Breed improvement is mainly undertaken through selection of male goats at juvenile age. About 81.5% of households practice controlled mating through running selected buck in the flock (49.1%) and culling undesirable males and females (31.5%). It could be concluded that, goats are adapted in arid environment and pastoralists have indigenous knowledge that favored some traits, which will suggest the introduction of community based genetic improvement coupled with improving management to benefit the households.

Keywords: breed improvement, characterization, controlled breeding, selection criteria


The breeding goal is a list of traits to be improved genetically. It should be in line with national agricultural development objectives and appropriate for the production system for which it is defined (Bourdon, 2000). In traditional societies, breeding goals are not that narrow, and diversity is often striven for (Köhler-Rollefson, 2000). A goat breed kept in a pastoralist system; it may be reasonable milk yields combined with ability to survive in an unfavorable environment (Kosgey 2004). Breeding goals are also guided by aesthetic and personal preferences, religious requirements and behavioral aspects of animals, such as alertness, flock leading, good mothering instincts, herdability, ability to walk long distances and loyalty to the owner (Laird 2002; FAO 2009; Grum2010).Previous breed improvement strategies have been focusing only on productive traits. However, some – behavioral & Adaptive – traits that are associated with the particular community and production system may be equally important. Many scholars agreed that avoidance of community indigenous knowledge and such trait in the breeding objective as one of the main reason for failure to breed improvement strategy in Ethiopia rural community (Philipsson et al 2006; Duguma et al 2010; Tadele 2010).

Indigenous knowledge about animal breeds and breeding is the knowledge that communities use to manipulate the genetic composition of their livestock. It includes knowledge and experience about the genetic attributes of livestock and inheritance, as well as conscious strategies and social mechanisms that influence the gene pool (Köhler-Rollefson, 2000; Rege and Okeyo 2006).This rather extensive and complex knowledge system has not yet been adequately characterized and documented(Wurzinger et al 2005)

The conventional characterization of indigenous goat population of Ethiopia appeared in the series of surveys summarized in the ILRI monograph by FARM-Africa (1996). However, the work lacks a detail description of the role of associated livestock keeping communities and their indigenous knowledge in shaping and managing the breed. Ignoring such wealth of knowledge could partly be the reason why livestock genetic improvement programmes have generally failed in many developing tropical countries (Sölkner et al 1998; Rege and Okeyo 2006; Philipsson et al 2006; Kiwuwa 1992). Therefore, this paper contributes for community based breed improvement of Afar goat and aimed with the objectives of:

Participatory definition of local trait preferences and Investigate the community’s indigenous knowledge on goat breeding strategy.

Material and methods

Description of the Study Area

Afar National Regional State (ANRS) is located between 8° 45’ to 14° 27’ latitude North and 39° 51’to 42° 23’ longitude East. The Region has an estimated population of 1.2 million (CSA 2007) of which 90% are pastorals and 10% agropastoral.About 51.4% of the Region is categorized by arid agro-climate.While, 35.5%by desert agro-climate which falls below 400 meters above sea level and small rain fall of less than 300mm. The study was conducted in Aysaita District.  The District is sub – divided in to 13 peasant association (6 pastoral, 5 agro pastoral and 2 urban). The agro – climate of the woreda is about 85% arid and 15% semi – arid with an average annual temperature of 35°C and little rainfall ranging from 200 – 300 mm per annum (Nigatu 1994; Solomon 2006).

Sampling Method and Sample Size

Stratified random sampling procedure was employed. The district was stratified into pastoral and agropastoral production systems. Since pastoralism represent about 90% of the population, two pastoral and one agropastoral peasant associations were randomly selected.Fifty households were interviewed from each PA using systematic random sampling. However, some questioner sheets that seem unreliable were rejected and 83 for pastoral and 41 for agropastoral sample unit was used for data analysis.

Data Collection

Data was generated by administrating a structured questionnaire, via participatory rural appraisal (PRA) tools and from secondary sources. The household survey used a set of structured questionnaires which was a slightly modified version of those designed for livestock breed survey in Oromiya Regional State (Workneh and Rowland 2004). A pretested questionnaire was administered to randomly selected household head. The PRA tools employed include focus group discussions (FGD) and key informants.Group discussion was held with a focal-group, consisting of 8 – 10 members, established at each production system.

Methods of Data Analysis

Data collected through questionnaire were analyzed by descriptive statistics using Statistical Package for Social Sciences (SPSS 16.0 for windows release 16.0 2010). Chi - square test was employed when required to assess the statistically significant variation between/among variables at 5% probability level. Indexes were calculated for all rankings data according to a formula:  Index = sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) given for an individual reason (attribute) divided by the sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) for overall reasons.

Result and discussion

Participatory definition of trait preferences

Goat flock owners were asked to choose their first, second and third best male and female goat among the flocks and then to mention the reasons for their preferences. Subsequently, only the first three reasons from the first, second and thirdly chosen animal were used for ranking. This participatory definition of trait was used since it allow respondents to mention as many reason as possible for their preferences without being limited to predetermined lists.

Milk yield was the first and highly valued traits in both production systems (Table 1). Since milk is the principal and continually recurring ingredient of the diet in the area, there is no doubt that does with high milk yield would be the first choice regardless of weakness in other traits. Drought tolerance, fertility and adaptive traits were also frequently mentioned to define the best female in both production systems.

Drought tolerancewas referred as the ability of doe to survive and produce during dry seasons providing milk for their children when most of the female fail to do so.Adaptive traits commonly stated to define the best female were diseases tolerance,ability to walk long distance, foraging ability/feeding competency and mothering care. In pastoral production where flock size matter most to minimize risk, the locale also attached strong preferences of doe for fertility. This survey result was in agreement with Workneh (1992) who stated pastorals and agropastorals more preferences toward milk yield, adaptability and drought resistance features of goats.

Table 1. List of trait preference of households and their corresponding rating for does
Traits Pastoral Agropastoral
R1 R2 R3 Index R1 R2 R3 Index
Milk yield 42.0 25.9 12.3 0.317 53.7 29.3 9.8 0.382
Fertility 8.6 18.5 12.3 0.126 7.3 9.8 7.3 0.081
Offspring quality 6.2 9.9 7.4 0.076 4.9 9.8 12.2 0.077
Drought tolerance 14.8 13.6 16.0 0.146 9.8 19.5 17.1 0.142
Adaptive* 7.4 9.9 18.5 0.101 4.9 12.2 17.1 0.093
Body size and conformation 4.9 4.9 9.9 0.058 7.3 2.4 2.4 0.049
Color 3.7 3.7 6.2 0.041 4.9 2.4 14.6 0.057
Twining rate 7.4 8.6 3.7 0.072 7.3 2.4 7.3 0.057
Family history - - - - - - - -
Behavioral** 0.0 1.2 4.9 0.012 - - - -
Kidding interval 2.5 2.5 6.2 0.031 - 7.3 7.3 0.037
Longevity 2.5 1.2 2.5 0.021 - 4.9 2.4 0.02
R1, R2 and R3 = Rank 1, 2 and 3 respectively. Index = sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) given for an individual attribute divided by the sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) for overall attributes.
*Adaptive traits like diseases & heat tolerance, ability to walk long distance, foraging ability, mothering care
** Behavioral traits like flock leading, turning to the owner as he/she calls its name, docility

Photo 1. An individual household’s preferred female (left) and male (right) goat

Unlike doe, the best buck was primarily rated based on the physical appearance. Males with big body size and good conformation (tall, up right standing, strait back profile etc) was viewed as best buck in both production systems followed by a beautiful color (patchy or spotted –photo 2) in agropastoral and behavior in pastoral system (Table2). A higher preference for body size was also reported for Kenya pastoral (Kosgey 2004). Behavioral traits received higher preference in pastoral communities, since it is more important than color where there exist large number of flock and constant mobility. While, color is more important to attract good price than behavior for agropastoral.

Table 2. List of trait preference of households and their corresponding rating for buck
Traits Pastorala Agropastorala
R1 R2 R3 Index R1 R2 R3 Index
Body size and conformation 40.2 32.9 11.0 0.329 42.9 39.3 3.6 0.351
Offspring quality 8.5 4.9 14.6 0.083 7.1 7.1 - 0.06
Behavioral 17.1 22.0 20.7 0.193 17.9 10.7 28.6 0.173
Kid sex 7.3 4.9 4.9 0.061 3.6 - 7.1 0.03
Color 9.8 18.3 28.0 0.157 25.0 35.7 32.1 0.298
Growth rate 1.2 2.4 3.7 0.02 - - - -
Drought tolerance - 1.2 1.2 0.006 - - - -
Walking style - - 2.4 0.004 - - - -
Libido/strength 12.2 9.8 9.8 0.11 - 3.6 10.7 0.03
Twining rate 2.4 - - 0.012 - - - -
Horn length 1.2 2.4 2.4 0.018 - 3.6 17.9 0.042
Dam milk yield - 1.2 1.2 0.006 3.6 - - 0.018
R1, R2 and R3 = rank 1, 2 and respectively. Index = sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) given for an individual reason (attribute) divided by the sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) for overall reasons.
*Behavioral traits like flock leading, paternal care/standing at night as guard, not mixing with other flock, docility

In pastoral production system especially with large flock size, behavior of goat like flock leading is associated with a character to exploit seasonal variations in feed resources and maximize “feeding competence” with other flock. Similar phenomenon was indicated in Niger (Krätli, 2008). Other behavior like a goat standing in the flock during the night as guard or alert to predator (while other goats asleep) was also indicated as important character especially when predators are a great challenge. Nari herders’ in India are well know developing Nari cows, which have special behavior of defending their calves from leopards by forming a circle around the young animals (Köhler-Rollefson and LIFE Network, 2007).

Identification system and genealogical keeping

In an endeavor to differentiate among and within flock, the most important identification systems used were recalling/memorizing, coat color and ear notching (Table 3). There is a unique type of ear cut for each clans and sub – clan flocks. Additionally, by varying the position of the ear cut, each household flock will be further separated among other flocks.

It was also noted that in some households best does are represented by one of the family members’ name. Consequently, her offspring belong to that same individual. This association facilitated easily sorting the descendants of best females and grouping of the flock. Elsewhere in Kenya the Maasai pastoral was reported to structure their cow herd in to “house”, or female lineages. All descendants of a single cow form a “house”, and they are all called by the same name (Galaty 1989).

Table 3. Identification systems employed in pastoral and agropastoral systems
Systems Pastoral Agropastoral
R1 R2 R3 Index R1 R2 R3 Index
Recall system 39.8 16.9 9.6 0.27 56.1 17.1 17.1 0.37
Ear notching 21.7 25.3 19.3 0.23 14.6 9.8 19.5 0.14
Branding 2.4 6.0 10.8 0.05 7.3 14.6 14.6 0.11
Color 25.3 28.9 30.1 0.27 17.1 36.6 31.7 0.26
Horn type 2.4 10.8 16.9 0.08 - 2.4 4.9 0.02
Naming & family group 8.4 12.0 13.3 0.10 4.9 19.5 12.2 0.11
R1, R2 and R3 = Rank 1, 2 and 3 respectively. Index = sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) given for an individual reason (attribute) divided by the sum of (3 for rank 1 + 2 for rank 2 + 1 for rank 3) for overall reasons

The Afar community has a culture of memorizing personal ancestral genealogy as well as genealogy of their animals. Accordingly, 75.8% of overall respondents reported to mentally memorize genealogy through the maternal line of descent (Table 4). About 6 lines of maternal line recalling was mentioned in this survey result. In the meantime, 80.6% of the respondents mentioned to recognize the sire of a kid (Table 4). They reported identifying sire of an offspring through observing the coat color, body conformation, ear form, horn shape and type of the offspring.

This observation revealed that the community has a mechanism of keeping genealogy of animal and employ range of methods to identify individual animal among and within flocks. This indigenous knowledge enables the herders’ to identify a particular animal throughout its lifespan. This imply that pedigree and performance recording has been practiced through intricate knowledge. Therefore, it was apparent that the pastoralists have deliberate selection criteria.

Table 4. Indigenous knowledge of pastorals and agropastorals about goat breeding
Breeding strategies Percentage of respondents p value
Pastoral (N=83) Agropastoral (N=41) Overall
Oral record keeping of genealogy
Yes 71.1 85.4 75.8 >0.05
No 28.9 14.6 24.2
Identifying sire of an offspring >0.05
Yes 83.1 75.31 80.6
No 16.9 9.8 14.5
Mating system in the flock
Controlled 84.3 75.6 81.5
Uncontrolled 15.7 24.4 18.5
Castration of male goat <0.001
Yes 85.5 53.7 75.0
No 14.5 46.3 25.0
Castration age
3-6 months 4.2 4.5 4.3
>6 months 95.8 95.5 95.7
Mating control and castration

Controlled breeding is practiced both in pastoral and agropastoral systems (Table 4). The techniques employed to control breeding were indicated in Table 5.This investigation is not concurrent with the report of Dereje (2011) who indicated high rate of uncontrolled mating; however, it is in agreement with Workneh and Rowland (2004) that reported high rate of breeding control (86%) using selected breeding buck. Unlike Grum et al (2013) who reported castration as the major mating control (76.4%), this finding was in agreement with the result of Workneh (1992) who revealed higher rate of selection through culling poor looking animals and keeping superior male continuously in the flock. Few pastoralists also reported tying the prepuce of buck to control immature male serving the flock. The practice was reported for breeding rams in the Region, Afar (Tesfaye 2008) and also tying an apron in front of the genitals of breeding buck was reported in the Bellen societies of Eritrea (Nigatu 1994).

Table 5. Reported methods of mating control in pastoral and agropastoral systems (%)
Production systems Techniques of mating control Total
Running selected Culling Castration Physical restraining
Count 34 25 14 3 79
Percent 44.7 32.9 18.4 3.9 100
Count 19 9 4 0 32
Percent 59.4 28.1 12.5 0 100
Total (%) 49.1 31.5 16.7 2.8 100

Goats are castrated in the area, but the practice appears to be significantly higher (p<0.001) in pastoral than in agropastoral systems (Table 4). Likewise more frequency of castration in pastoral (90%) than other production systems was also reported in Oromiya Region (Workneh and Rowland 2004). This may be due to the fact that most agro-pastoralists and small-scale farmers owe small flock size hence there will be very few bucks that remains only for breeding.

Castration is mostly practiced after six months of age consistently across both production systems (Table 4). The reasons for castration were listed in Table 6. Castration of rams for the motive of leading flock was reported in Syrian Bedouins pastorals (FAO 1985). The other notable reason for castration of goats was to improve fattening to earn a better price on sell and to receive a better social status and respect.

Table 6. Reasons for castration of male goats in pastoral and agropastoral areas (%)
Production system Reasons for castration Total
Mating control Improve fattening Good behavior Social status Combination of reasons
Pastoral 6.9 25.0 38.9 12.5 16.7 100
Count 5 18 28 9 12 72
Percent 6.9 25.0 38.9 12.5 16.7 100
Agropastoral 13.6 22.7 36.4 4.5 22.7 100
Count 3 5 8 1 5 22
Percent 13.6 22.7 36.4 4.5 22.7 100
Total % 8.5 24.5 38.3 10.6 18.1 100



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Received 14 February 2015; Accepted 15 June 2015; Published 1 August 2015

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