Figure 1. Map of the study areas
| Livestock Research for Rural Development 30 (4) 2018 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
The objective of this study was to evaluate body weight and milk yield improvement under community based breeding program (CBBP) in Tanqua-Abergele and Ziquala districts of Northern Ethiopia. A total of 1540 progenies (1249 for body weight and 291 for milk yield) from base flocks and selected bucks were used to evaluate genetic improvements of selective breeding. General linear model procedures were employed to evaluate selective breeding progress based on body weight and milk yield of progenies of base flocks and selected bucks. The result revealed that birth weight of progenies of selected bucks (2.39±0.02 kg) were significantly (p<0.001) heavier than base flock progenies (2.17±0.02 kg). However, the weight improvement is not continued in the subsequent growth stages. The daily milk yield of progenies of selected bucks was 372±14.8 ml significantly (p<0.05) lower than base flock does (408±6.72 ml). Moreover, there was significant variation of daily milk yield (p<0.05) between the goat populations in the study districts (404±14.2 ml in Tanqua-Abergele and 375±7.10 ml in Ziquala) and seasons (403±11.2 ml in wet and 376±8.49 ml in dry). There was no considerable improvement observed on body weight and milk yield in the CBBP, which could be influenced by environmental factors or lack of proper implementation of the selective breeding program or it could be because of the few generations used for the study. However, the study also revealed slight improvement in the fourth year of selective breeding, indicating that breeding goals require selective breeding in successive generations to achieve success.
Key words: body weight, goats improvements, milk yield, selective breeding
Ethiopia is home to the largest livestock population in Africa, supporting and sustaining the livelihood of rural people (Tilahun and Schmidt 2012; CSA 2016). Livestock are the main part of agricultural sector in Ethiopia that contributes 45% to national agricultural gross domestic product of the country (Behnke et al 2010). The livestock population has diversified genetic resources and production environments. Based on phenotypic characterization, the country is endowed with 15 goat populations (IBC 2004), even though, the recent molecular study regrouped in to seven genetic entities (Mekuriaw 2016). A huge number of goats which estimated in 29.70 millions are reared across the diverse agro-ecological zones and production system of the country (CSA 2016).
Despite the country has diverse genetics, resistant to harsh environment and large number goat populations, their productivity is below the expectations. This is because of feed shortage, disease prevalence, inferior genotype, poor marketing system and infrastructure (Gizaw et al 2010; Abegaz 2014). Consequently, many efforts have been conducted for improving production and productivity of goat but the success is limited. Among the efforts, crossbreeding was the major one that had focused for several years using exotic breeds. However, it has not succeed due to lack of a clear and documented breeding and distribution strategy, very little consideration of farmers’ needs and indigenous practices (Haile et al 2011). Recently the government of Ethiopia, as part of Livestock Master Plan (LMP), suggested designing appropriate breeding programs with feed and health service interventions.
Goats are the significant species for the rural communities of Tanqua-Abergele and Ziquala districts that reared in large flock since they are adaptive to harsh environment than sheep and cattle species. Goats are provided 3.4 and 1.6 times higher gross margin than sheep and cattle, respectively in dry area of the country (Woldu 2016). Community-based breeding program (CBBP) refers to participatory village-based breeding activities with technical supports. It is viable genetic improvement option under low input production system (Mueller et al 2015). Some indigenous goat populations including Abergelle goat in Ethiopia has been initiated and implemented selective breeding under CBBP to improve meat and milk production (Gizaw 2013; Alemu 2015). This selective breeding has been implemented since 2013 in villages of Tanqua-Abergele and Ziquala districts based on selecting phenotypicaly supporior bucks and farmers preference (Dessie et al 2014). Any breeding program should be evaluated in order to disseminate the strategy as well as elite animal as a parent or founding flock in the wider population of a particular breed (FAO 2015). However, information on the progress of current breeding programs is limited. Therefore, the objective of this paper was to evaluate body weight and milk yield improvements performance of Abergelle goat population in the CBBP.
The study was conducted in two CBBP sites of Tanqua-Abergele and Ziquala districts located in central zone of Tigray and Wag Himera zones of Amhara regional states, respectively in Northern Ethiopia. Farmers’ livelihood of the area is depending on crop-livestock mixed production system with dominant small ruminant production (Gebremariam and Belay 2016). As a result, International Livestock Research Institute and International Center for Agricultural Research in the Dry Areas in collaboration with Tigray Agricultural Research Institute and Amhara Agricultural Research Institute initiated CBBP aiming to improve the goat productivity through selective breeding.
|
Table 1. Agro-ecology of the study districts |
||
|
Climate factors |
Tanqua-Abergele |
Ziquala |
|
Altitude |
<1500 masl |
<1500 masl |
|
Rainfall |
400-600 mm |
255 mm |
|
Temperature |
21-41 °C |
22 °C |
|
Agro-ecology |
warm sub-moist lowland |
warm sub-moist lowland |
|
Source: respective districts’ office of Agriculture and rural development (2015) |
||
|
Figure 1. Map of the study areas |
Study areas were selected based on the intervention of designed breeding program. Each selected study district has one CBBP site. From these two sites, about 73 monitored flocks under the CBBP were used.
The data were collected during 2013 to 2017 under the CBBP sites. At the beginning, a total of 1246 dams were randomly ear tagged in both districts for identification using plastic ear tag code to monitor own and their progenies performances. Subsequently, eight months to yearly aged elite bucks were selected by ranking and farmers’ preference, especially in color, based on their body weight and dams’ milk yield. The candidate bucks were selected based on recorded data (own and maternal performance) for the body weight and milk yield selection traits. The following selection index was employed to select the candidate bucks for natural mating:
Index = Owt +DMYPD
Owt = birth weight + (actual weight at farm gate –birth weight)/ age *100
DMYPD = total milk yield in the lactation recorded one day per week/ number of recorded days
Where:
Owt = Own Weight with 75 % economic weight
DMYPD = Dams’ milk yield per day with 25 % economic weight
Each household were received the selected bucks with consideration of inbreeding by shifting of bucks in yearly interval and mating ratio to be one buck to fifteen does. Flock management activities such as data recording, castrating the unselected bucks and vaccination were monitored regularly. A total of 1249 progenies (640 from base flocks and 609 from selected bucks) for body weight and 291 does (167 from base flocks and 124 from selected bucks) for milk yield evaluation were used. Spring hanging weight balance of 50 kg capacity with accuracy of 200 g was used to record body weight at birth, three months, six months and nine months. Milk yield was recorded weekly and twice a day (morning and evening) for three months lactation using a 500 ml graduated plastic cylinder.
The data were analyzed using general linear model procedure (PROC GLM) of SAS version 9.1. Breeding practice, district, sex, birth type, season and parity for body weight and milk yield variables were fitted as fixed effect. Least square mean with respective standard error was separated using Tukey-Kramer test. The following models for body weight and milk yield variables with the fixed effects were fitted according to R 2 (model of fitness). The models were:
Yijkl =µ + Di + BPj +Sk + B l + (D*BP)ij+eijkl
Where: Yijlm = the observed growth performance of goat under CBBP by weight at birth, three, six and nine months
µ = overall mean
Di= is the effect of ith district or CBBP site (Tanqua-Abergele and Ziquala)
BPj = is the effect of jth breeding practice (progenies of base flock and selective bucks)
Sk = is the effect of kth sex (male and female)
Bl= is the effect of lth birth type (single and twin)
(D*BP)ij= is the interaction effect of ith district with of jth breeding practice
eijkl= is random residual error
Yijk= µ + Di + Pj+Sk +B l+ (D*BP)il + eijkl
Where: Yijkl the observed milk yield
µ= overall mean
Di = is the effect of ith district or CBBP site (Tanqua-Abergele and Ziquala)
Pj= is the effect of kth parity (1, 2 and 3)
Sk= is the effect of jth season (wet and dry)
BPl= is the effect of jth breeding practice (progenies of base flock and selective bucks)
(D*BP)il = is the interaction effect of ith district with jth breeding practice
eijkl= is random residual error
The least square mean (LSM±SE) for body weight performance of kids before and after selection, which termed as progenies of base flocks and progenies of selected bucks, respectively in the current study, is presented in the Table 2. The overall mean of weight at birth, three months, six months and nine months were 2.28±0.02 kg, 7.40±0.09 kg, 9.48±0.15 kg and 11.38±0.19 kg, respectively.
Comparatively, the average birth weight for progenies of selected bucks was 2.39±0.02 kg and 2.17±0.02 kg was for the progenies of base flocks. The former is highly significantly (p<0.001) heavier than progenies of base flocks. However, in latter age (at three months, six months and nine months) the weight performance between progenies of selected bucks and base flocks were not significant. The unexpected result of selective breeding might be due to the influence of environmental factors or lack of proper implementation of the breeding program. The current finding is in agreement with Haile et al (2014) stated that body weight of Horro lambs at three months and six months has not improved, but slight increment shown at birth in the beginning of selective breeding.
District and birth type were found to be the major factors of body weight under the CBBP. The least squares analysis for body weight of Abergelle goat revealed that there is significant variation between the study districts. Weights of Abergelle goat kid, at all age group were significantly higher (p<0.001) in Tanqua-Abergele district than in Ziquala district (Table 2). This could be because of environmental and/ or management variations between the districts. The present finding of weight at birth for Abergelle goat in Tanqua-Abergele (2.32±0.02 kg) and Ziquala (2.24±0.02 kg) districts are higher than former reports. Deribe and Taye (2013) and Alemu (2015) reported 1.91±0.04 kg and 1.98±0.06 kg, respectively for same goat population but in different study sites. However, the present finding at post weaning is in agreement with Alemu (2015) report, which stated that kids in Tanqua-Abergele district are heavier than Ziquala districts under conventional breeding. Although, the current result of Abergelle goat kids in Ziquala district had heavier at three months (7.22±0.10 kg vs. 6.84±0.19 kg) it is comparable at six months to the reports of the same breed under conventional breeding program (Deribe and Taye 2013). Kids born as single were significantly heavier than twin born at six and nine months but not at birth and three months.
Moreover, the interaction analysis is revealed that despite both districts had significant improvement at birth, the post weaning body weight improvement in Tanqua-Abergele district is better than in Ziquala district. Progenies of selected bucks were significantly heavier at three months (7.84±0.10 kg) and six months (10.7±0.17 kg) than of progenies of base flocks that performed 7.33±0.11 kg and 10.04±.17 kg, respectively (Table 2). Conversely, the progenies of base flocks were showed significantly heavier than progenies of selected bucks at three (7.55±0.12 kg vs. 6.90±0.11 kg) and six months (9.02±0.18 kg vs. 8.14±0.20 kg) in Ziquala. Apart from these, the nine months weight performance of progenies from selected bucks and base flocks were not significantly differ in both districts.
|
Table 2. Body weight comparison of progenies of base flocks and progenies of selected bucks |
||||||||
|
Effects and |
BW |
TMW |
SMW |
NMW |
||||
|
Levels |
N |
LSM±SE |
N |
LSM±SE |
N |
LSM±SE |
N |
LSM±SE |
|
Overall |
1249 |
2.28±0.02 |
1270 |
7.40±0.09 |
1127 |
9.48±0.15 |
832 |
11.4±0.19 |
|
R2 |
1249 |
0.18 |
1270 |
0.06 |
1127 |
0.16 |
832 |
0.07 |
|
CV% |
1249 |
10.67 |
1270 |
18.3 |
1127 |
20.7 |
832 |
17.9 |
|
District |
1249 |
*** |
1270 |
*** |
1127 |
*** |
832 |
*** |
|
TA |
698 |
2.32±0.02a |
691 |
7.58±0.09a |
643 |
10.4±0.15a |
530 |
12.0±0.17a |
|
Ziquala |
551 |
2.24±0.02b |
574 |
7.22±0.10b |
484 |
8.58±0.17b |
302 |
10.8±0.21b |
|
BP |
1249 |
*** |
1270 |
ns |
1127 |
ns |
832 |
ns |
|
PBF |
640 |
2.17±0.02b |
631 |
7.44±0.10 |
630 |
9.53±0.16 |
612 |
11.5±0.18 |
|
PSB |
609 |
2.39±0.02a |
634 |
7.37±0.09 |
497 |
9.43±0.16 |
220 |
11.3±0.25 |
|
Sex |
1249 |
ns |
1270 |
ns |
1127 |
ns |
832 |
ns |
|
Female |
583 |
2.27±0.02 |
596 |
7.38±0.10 |
532 |
9.39±0.17 |
403 |
11.2±0.20 |
|
Male |
666 |
2.28±0.02 |
669 |
7.42±0.09 |
595 |
9.57±0.16 |
429 |
11.5±0.20 |
|
Birth type |
1249 |
ns |
1270 |
ns |
1127 |
** |
832 |
* |
|
Single |
1189 |
2.30±0.01 |
1207 |
7.48±0.03 |
1077 |
9.89±0.06a |
791 |
11.7±0.10a |
|
Twin |
61 |
2.25±0.03 |
59 |
7.32±0.18 |
51 |
9.07±0.29b |
42 |
11.0±0.34b |
|
Sites*BP |
1249 |
* |
1270 |
*** |
1127 |
*** |
832 |
* |
|
TA*PSB |
330 |
2.44±0.02a |
327 |
7.84±0.10a |
284 |
10.7±0.17a |
185 |
11.9±0.21a |
|
TA*PBF |
368 |
2.19±0.02c |
364 |
7.33±0.11b |
359 |
10.0±0.17b |
345 |
12.1±0.19a |
|
Ziquala*PSB |
279 |
2.34±0.02b |
307 |
6.90±0.11c |
213 |
8.14±0.20d |
35 |
10.6±0.39b |
|
Ziquala*PBF |
272 |
2.15±0.02c |
267 |
7.55±0.12b |
271 |
9.02±0.18c |
267 |
10.9±0.21b |
|
BP=breeding practice, PBF= progenies of base flock, PSB= progenies of selected bucks, BW= birth weight, TMW= three month weight, SMW= six months weight, NMW= nine months weight, *** p <0.001, ** p≤0.01, * p ≤0.05, ns= non significance, LSM= least square means, SE= standard error, TA= Tanqua-Abergele |
||||||||
The progress of selective breeding across year is shown in Table 3. Year one represents for the progenies of base flock performance, while after year two is represent for the progenies of selected bucks. The figure indicated that the least square means of body weight in all growth stage were not changed for the first two years (year1 to year2 and year2 to year3) after selective bucks used. However, it was increased at year3 to year4 of the selective breeding that could be the time of second generation progenies produced.
|
Table 3. Body weight improvement performances across years of selective breeding |
||||||||
|
Parameter |
Year 1 |
∆Wt/Y |
Year 2 |
∆Wt/Y |
Year 3 |
∆Wt/Y |
Year 4 |
|
|
LSM±SE |
LSM±SE |
LSM±SE |
LSM±SE |
|||||
|
BW (kg) |
2.20±0.01 |
0.23±0.01 |
2.43±0.02 |
-0.033±0.00 |
2.40±0.02 |
0.024±0.01 |
2.42±0.01 |
|
|
TMW(kg) |
7.49±0.05 |
-0.20±0.08 |
7.29±0.13 |
-0.35±0.04 |
6.94±0.09 |
1.01±0.01 |
7.95±0.08 |
|
|
SMW(kg) |
9.98±0.08 |
-1.22±0.14 |
8.76±0.22 |
0.10±0.09 |
8.86±0.13 |
3.16±0.02 |
12.0±0.15 |
|
|
NMW(kg) |
11.9±0.08 |
-0.92±0.11 |
10.9±0.19 |
0.44±0.01 |
11.4±0.20 |
4.96±0.14 |
16.3±0.34 |
|
|
PBF= progenies of base flock, PSB= progenies of
selected bucks, BW= birth weight, TMW= three month
weight, SMW= six months weight, |
||||||||
Least square means of daily milk yield of Abergelle does under community based breeding program, before and after selection with district, parity and season effects, are presented in Table 4. The overall mean of daily milk yield for Abergelle does were 390±8.40 ml. This current finding is comparable to Berhane and Eik 2006 reports (370 – 430 g) but higher than Alemu (2015) report (346±10.08 ml) for the same goat population. The current finding indicates that Abergelle goat population produced higher milk yield than Arsi-Bale (296 g/day) (Woldu 2004) and lower than Begait (0.75±0.01 kg) (Abraham 2017) goat populations.
The progenies of selected bucks (372±14.8 ml) had significantly (p <0.05) lower daily milk yield than base flock does (408±6.72 ml). This indicated sire line selective breeding is responded negatively for milk yield improvement. The reason could be the breeding bucks were selected based on performances of growth traits rather than milk yield productivity. Besides, district and season were the significantly contributed for the variability of daily milk yield. Milk yield is increased when the plenty of feeds and water available (Mengistu 2007). The availability of feed is better in Tanqua-Abergele than Ziquala district. In the present study, does found in Tanqua-Abergele district had significantly (p<0.05) higher milk yield than Ziquala district and similarly milk yield in wet season were higher than in dry season (Table 4).
|
Table 4. Milk yield improvements of Abergelle goat after selective breeding |
|||||
|
Effects and |
N |
Daily milk yield |
Effects and |
N |
Daily milk yield |
|
LSM±SE |
levels |
LSM±SE |
|||
|
Overall |
291 |
390±8.40 |
Overall |
291 |
390±8.40 |
|
R2 |
291 |
0.22 |
R2 |
291 |
0.22 |
|
CV% |
291 |
20.4 |
CV% |
291 |
20.4 |
|
District |
291 |
* |
Birth season |
291 |
* |
|
TA |
91 |
404±14.2a |
Wet |
71 |
403±11.2a |
|
Ziquala |
200 |
375±7.10b |
Dry |
220 |
376±8.50b |
|
BP |
291 |
* |
District*BP |
291 |
** |
|
PSB |
124 |
372±14.8b |
TA*PSB |
11 |
357±26.8b |
|
PBF |
167 |
408±6.72a |
TA*PBF |
80 |
452±10.0a |
|
Parity |
291 |
ns |
Ziquala*PSB |
115 |
387±9.80b |
|
1 |
154 |
377±9.30 |
Ziquala*PBF |
85 |
364±9.20b |
|
2 |
89 |
386±10.5 |
|||
|
3 |
48 |
405±14.0 |
|||
|
LSM=least square mean; SE= standard error *= p≤0.05 **= p≤0.01, BP=breeding practice, PBF= progenies of base flock, PSB= progenies of selected bucks, ns= non significance |
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Abegaz S, Mwai O, Gebreyesus G, Haile A, Rischkowsky B A, Gizaw S and Dessie T 2014 Review of goat research and development projects in Ethiopia. International Livestock Research Institute, project report, Nairobi, Kenya, http://hdl.handle.net/10568/42173
Alemu A 2015 On-farm phenotypic characterization and performance evaluation of Abergelle and Central Highland goat breeds as an input for designing community-based breeding program. MSc Thesis, Haramaya University, Ethiopia
Behnke R and Fitaweke M 2010 The contribution of livestock to the Ethiopian economy: study findings, application of the methodology in Ethiopia and recommendations for further work. IGAD LPI working paper, No. 02-11, Addis Ababa, Ethiopia
Berhane G and Eik LO 2006 Effect of vetch (Vicia sativa) hay supplementation on performance of Begait and Abergelle goats in Northern Ethiopia: Milk yield and composition. Small Ruminant Research, 64, 225-232, https://doi.org/10.1016/j.smallrumres.2005.04.021
CSA 2016 Agricultural sample survey report on livestock and livestock characteristics (private peasant holdings). Federal democracy of Ethiopia, central statistics agency, Volume II, statistical bulletin 578, Addis Ababa
Deribe B and Taye M 2013 Evaluation of growth performance of Abergelle goats under traditional management systems in Sekota district, Ethiopia. Pakistan Journal of Biological Science, 16(14), 692–696, http://scialert.net/abstract/?doi=pjbs.2013.692.696
Dessie T, Gebreyesus G, Mekuriaw G, Woldu T, Jembere T, Morris A and Okeyo M 2014 Participatory definition of trait preferences for designing village breeding schemes for goats in harsh environments of Ethiopia. Proceeding of the 10th world congress of genetics applied to livestock production. Vancouver, Canada, pp. 12-14
FAO 2015 The second report on the state of the world’s animal genetic resources for food and agriculture edited by B.D. Scherf and D. Pilling. Food and Agriculture Organization, Rome, Italy, http://www.fao.org/3/ai4787e/index.html
FARM-Africa 1996 Goat type of Ethiopia and Eritrea: physical description and management systems. Published jointly by FARM-Africa, London, UK and International Livestock Research Institute, Nairobi, Kenya
Gebremariam T and Belay S 2016 Livestock feed resources utilization practices in Tanqua-Abergele district of Tigray, Northern Ethiopia. Tropical Animal Health and Production, 48(4), https://doi.org/10.1007/s11250-016-1073-y
Gizaw S 2008 Sheep resources of Ethiopia: genetic diversity and breeding strategy. PhD Thesis, Wageningen University, Netherlands
Gizaw S, Tegegne A, Gebremedhin Band Dirk H 2010 Sheep and goat production and marketing systems in Ethiopia: characteristics and strategies for improvement. International Livestock Research Institute, working paper No. 23, Nairobi, Kenya
Gizaw S, Tesfaye G, Zewdu E, Tadele M, Gemeda D, Markos T and Haile A 2013 Characterization of indigenous breeding strategies of the sheep farming communities of Ethiopia: a basis for designing community-based breeding programs, International center for research in Dry land Areas working paper, Aleppo, Syria
Hagos A, Gizaw S and Urge M 2017 Milk production performance of Begait goat under semi intensive and extensive management in Western Tigray, North Ethiopia. Livestock Research for Rural Development. Volume 29, Article #240, http://www.lrrd.org/lrrd29/12/hags29240.html
Haile A, Dessie T and Rischkowsky B 2014 Performance of indigenous sheep breeds managed under community-based breeding programs in the highlands of Ethiopia. International center for research in Dry land Areas, preliminary results, Addis Ababa, Ethiopia
Haile A, Wurzinger M, Mueller J, Mirkena T, Duguma,G, Mwai O and Rischkowsky B 2011 Guidelines for setting up community-based sheep breeding programs in Ethiopia: lessons and experiences for sheep breeding n low-input systems. International center for research in Dry land Areas, No.1, Aleppo, Syria.
IBC 2004 The state of Ethiopia's farm animal genetic resources. Institute of biodiversity and conservation, country report for a contribution to the first report on the state of the world's animal genetic resources, Addis Ababa, Ethiopia
Mekuriaw G 2016 Molecular Characterization of Ethiopian indigenous goat populations: genetic diversity and structure, demographic dynamics and assessment of the kisspeptin gene polymorphism. PhD Thesis, Addis Ababa University, Addis Ababa, Ethiopia
Mueller J P, Rischkowsky B, Haile A, Philipsson J, Mwai O, Besbes B and Wurzinger M 2015 Community-based livestock breeding programmes: essentials and examples. Journal of Animal Breeding and Genetics. 132, 155–168. https://doi.org/10.1111/jbg.12136.
Tilahun H and Schmidt E 2012 Spatial analysis of livestock production patterns in Ethiopia. Ethiopia Strategy Support Program working paper 44, Addis Ababa, Ethiopia and Washington DC, USA
Urge 2007 Performance of the Ethiopian Somali goat during different watering regimes. PhD Thesis, Swedish University of Agricultural Sciences, Uppsala, Sweden
Woldu T, Dadi H, Guru M and Gelashe D 2004 Productivity of Arsi Bale goat types under farmers’ management condition: a case of Arsi Negelle. Proceedings of the 13th annual conference of the Ethiopian Society of Animal Production, Addis Ababa, Ethiopia, 25–27 August 2004. pp. 67–71
Woldu T, Markemanna A, Reiber C, Philipp C M and Valle Zárate A 2016 Optimizing contributions of goat farming to household economic success and food security in three production systems in Ethiopia. Journal of Agriculture and Rural Development in the Tropics and Subtropics, 117: 73-85
Received 10 September 2017; Accepted 23 February 2018; Published 1 April 2018