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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 73
Research Article
Phenotypic characterization of the Gamo highland sheep population in Gamo Zone, South
Ethiopia
Dereje Dea
1*
, Ermias Eramo
1
, Deribe Gemiyo
2
1
Arba Minch Agricultural Research Center, Arba-Minch, Ethiopia
2
Southern Agricultural Research Center, Hawassa, Ethiopia
Corresponding author: deredea12@gmail.com
Received: September 25, 2022; Received in revised form: May 4, 2023; Accepted: May 5, 2023
Abstract: The study aimed to identify physical characteristics and prediction of live weight using linear body
measurements of indigenous sheep types in two highland districts of the Gamo zone (Chencha and Qogota).
Districts were purposively selected whereas farmers and animals were randomly selected. About 335 mature sheep
(270 female and 65 male) were sampled for the body measurements. Both qualitative and quantitative data were
analysed using SPSS version (20). Overall, the current findings revealed that mixed (62.50%) followed by black
(21.90%) were the dominant coat colours with patchy coat colour patterns (56.30%). The majority of the sheep were
horned (62.5%), curved horn (67.50%) and obliquely backward horn types (77.50%). Horizontal ear orientation
(76.00%) and straight head profile (96.90) were predominantly observed. In general, about 71.60% of the sheep
were hairy type and had straight crimp-curled hair (73.60%). The total hair coverage on the head, face, belly and
leg was about 3.0%, 94%, 92.5% and 13.4%, respectively. About 55.20% of the study sheep revealed near hocks tail
length. The mean body weight, body length, height at wither, chest girth, horn length, head length, hair length, ear
length and tail length were 20.26±3.60 kg, 54.55±3.48, 55.13±3.83, 66.73±4.79, 9.42±7.46, 16.83±1.85, 7.41±3.12,
10.27±0.97 and 26.62±2.66 cm, respectively. In general, sex, district and age (dentition) significantly (P<0.05)
affected linear body measurements. Body weight and most of the linear body measurements were positively
correlated. Chest girth was the single best predictor of body weight (P<0.05). Molecular characterization of Gamo
highland sheep is recommended for further advanced breeding strategies.
Keywords: Body weight, Chest girth, Highland sheep; Linear body measurement, Phenotypic traits
This work is licensed under a Creative Commons Attribution 4.0 International License
1. Introduction
The total sheep population in Ethiopia is estimated to
be about 42.9 million of this, and about 99.52% are
indigenous (CSA, 2021). The majority of the sheep
are found in the north western highlands of the
country (Solomon et al., 2008; Assen and Aklilu,
2012). Morphological and molecular
characterizations of sheep breeds in the country are
traditionally recognized by ethnic or geographic
nomenclatures. In Ethiopia, only a few breeds have a
fair description of their physical appearance
(Fsahatsion et al., 2018). Based on this, the sheep
breeds have been classified into 14 traditional
populations in 9 breeds within 6 major breed groups
(Solomon, 2008).
Identification and characterization of the existing
livestock genetic resources, their production
environment and constraints are crucial for long-term
Dea et al. J. Agri. Environ. Sci. 8(1), 2023
Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 74
genetic improvement, to diagnose the status and
trends of the system and conservation (Getahun et al.,
2008; Zewdu et al., 2009; Aamir et al., 2010;
Sowande et al., 2010; Ibrahim and Isa, 2011; Asefa et
al., 2017). The classical description of breeds is
based upon phenotype because an organism’s
phenotype is principally a manifestation of its
genotype, and it lends itself to direct measurement of
the organism. As such, phenotypic characterisation is
therefore complementary techniques for measuring
genetic diversity (Fsahatsion et al., 2018).The
productivity of sheep as in the case of most ruminants
is markedly low due to several genetic and
environmental factors (Markos, 2006).
Information on the phenotypic traits of the Gamo
highland sheep population is limited despite its
contribution and role as a source of cash income and
improving food security in the highlands of the Gamo
zone. For a more detailed characterization study of
Gamo highland sheep; updating phenotypic
appearances by routine inventories and on-going
monitoring are vital since genetic resources and
production systems are not static. Hence, this study
attempted to physically characterize indigenous sheep
types in the Gamo zone, south region, Ethiopia.
2. Materials and Methods
2.1. Description of the study area
The study was conducted in two districts (Chencha
and Qogota) of Gamo zone Highlands of south
Ethiopia. Gamo zone is bordered on the south by
Dirashe special woreda, on the southwest by Debub
Omo zone, on the northwest by the Konta zone, and
on the north by Dawuro and Wolayta zones, on the
northeast by Lake Abaya and on the southwest by the
Amaro special woreda.
Chencha woreda is located in the Gamo zone of
the Southern region, 37 kilometers north of Arba
Minch. Part of the Gamo Zone, Chencha is bordered
on the south by Arba Minch Zuria, on the west
by Dita & Gofa on the north by Kucha and Boreda,
and on the east by Mirab Abaya. Chencha has a
longitude and latitude of 6°15′N and 37°34′E,
respectively and an elevation of 2732 meters above
sea level.
Qogota is one of the recently established woreda. It is
bordered on the south by Chencha, on the west by
Kucha, on the north by Boreda and on the east by
Mirab-Abaya woredas. Qogota woreda has an
altitude of 2569 meter above sea level with
6°17′26’’N and 37°32′46’’E.
Gamo highland areas are characterized by a mixed
farming system. The major crop types produced
include inset, barley, wheat, bean, pea and potatoes
(Dereje, 2020).
2.2. Sources of animals
Indigenous sheep type found in the study districts of
Gamo zone was used as experimental animals. Since
it is on farm characterization, animals in the hands of
farmers were used and data regarding body
measurement and morphometric characteristics were
collected early in the morning before the animal was
released for grazing.
2.3. Sample size and sampling techniques
The study districts were selected purposively based
on their highland agro-ecology and sheep population
potential whereas smallholder farmers were selected
randomly. For morphological characters (qualitative)
and body measurements (quantitative) about 335
sheep (270 female and 65 male) from 70 households
were selected based on sex and age of animals.
Pregnant females (ewes) were excluded from the
sampling because pregnancy has an influence on
body parameters. Each experimental animal was
identified by sex, site and estimated age group. All
age groups of the sheep were classified into five age
groups using the number Pairs of the Permanent
Incisors (PPI): (0PPI, 1PPI, 2PPI, 3PPI and 4PPI) as
indicated in Table 1 (ESGPIP, 2009).
Sheep sample size was determined based on the
formula [1] described by Mezgebu et al. (2022).

[1]
Where;
n = required sample size
N = population size
e = error margin (e = 0.07)
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Table 1: Description of dentition with corresponding sheep age estimates
S/No.
Description
Estimated age
Source
1
The milk teeth have started to wear down, or are fully spread out
12 months
ESGPIP, 2009
2
With erupted and growing 1st pair of permanent teeth
14–17 month
3
With erupted and growing 2nd pair of permanent teeth
18–23 month
4
With erupted and growing 3rd pair of permanent teeth
24–36 month
5
With erupted and growing 4th pair of permanent teeth
3–5 years
2.4. Data collection
Data was recorded on the prepared format adopted
from the standard description list developed by FAO
(2012). All the data were taken early in the morning
since body measurements are influenced by the
posture, motion, and gut content of the animals.
Morphological characters like coat colour type and
pattern, horn type, horn shape, horn orientation, ear
orientation, head profile, wattle, beard, ruff and hair
type were studied with naked eye observation.
Body weight in kg, chest girth, body length, height at
wither, horn length, head length, hair length, ear
length, tail length and crimp curl were measured
using tailors measuring tape with records taken to the
nearest centimetre after restraining and holding the
animal in an unforced position (Figure 1). Weight
was measured in the morning before their release for
feeding to minimize post-prandial gut variation and
measured using a suspended spring balance having
50 kg capacity with 0.2 g precision.
Figure 1: Body parts of the sheep
Source: Picture taken during the experiment
Body
length
Height at
withers
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 76
2.5. Data management and statistical analysis
All the collected data were coded and recorded in a
Microsoft Excel spreadsheet. Qualitative data from
individual observation was analyzed following the
frequency procedures of (SPSS version 20, 2011).
The chi-square test was employed to test the
assumption of equal proportion between the
categorical variables. Means, standard deviations,
standard errors and coefficients of variation
computed for all the quantitative traits measured
using the General Linear Procedure (GLM) of SPSS.
Means were separated by Duncan multiple range test.
For adult animals, the location, sex and age group of
the experimental sheep was fitted as fixed
independent variables while body weight and linear
body measurements were fitted as dependent
variables. The model employed for analyses of body
weight and other linear body measurements is
presented below in formula [2].
     [2]
Where:
Y = the observed (body weight or linear body
measurements) in the i
th
age group, j
th
sex and
k
th
districts;
μ = Overall mean;
A
i
= the effect of i
th
age group (I = 0PPI, 1 PPI,
2PPI, 3 PPI and 4 PPI);
Sj = the effect of j
th
Sex (j = male and female);
Dk = the effect of k
th
district (Chencha and
Qogota);
eijk = random residual error
Pearson's correlation coefficients for each trait were
estimated between body weight and other body
measurements. A stepwise regression procedure was
also used to determine the best-fitted regression
equation for the prediction of body weight from body
measurements. Best-fitted models were selected
based on the coefficient of determination (R
2
), mean
square error and simplicity of measurement under
field conditions. The following models were used for
the analysis of multiple linear regressions [3].
        
[3]
Where:
Y = the response variable (body weight)
Α = the intercept X1, X2, X3, X4, X5, X6 and
Xn = the explanatory variables (CG, BL, HW,
HoL, HeL, HaL, EL and TL, respectively)
β1, β2, ..., βn = regression coefficient of the
variables X (X1, X2, ...,X n)
ej = the residual random error
3. Results and Discussion
3.1. Characterization of the physical traits of
sheep
Physical body characteristics of the Gamo highland
sheep population were presented in Table 2 and
Figure 1. The results showed that there was a clear
presence of morphological variations of the
indigenous sheep types. According to the report of
Solomon et al (2008), there is high morphological,
ecological, ethnic and production systems diversity of
indigenous sheep distributions in Ethiopia. The
results of Yakubu et al. (2010) pointed out that
phenotypes are an expression of genetic
characteristics, modified by environmental conditions
and that variance in both genetics and environment
may affect phenotypic variance.
The predominant coat colour types in the study areas
were mixed (62.50%) followed by black (21.90%)
with a patchy coat colour pattern (56.30%) of which
65% were found in the Qogota district. Majority of
the sheep population were horned (62.50%), curved
horn shape (67.50%) and obliquely backward horn
orientation (77.50%). The predominant ear form was
horizontal (78.10%). They were mainly characterized
by the absence of wattle (92.5%) and the absence of
ruff (64.20%). They are also characterized as having
hairy (71.60%), straight crimp curl (73.10%), bare
head hair (97.00%), bare hair cover (86.60%), face
hair cover (94.00%) and belly hair cover (92.50%).
The main tail types were thin-tailed (100%), and near
to hock tail length (55.50%) followed by well above
hocks tail length (40.30%). Almost, similar results
were found for the Bale sheep population (Wossenie
et al., 2012; Belete et al., 2017) and Wossenie (2012)
for the Hararghe Highland sheep.
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Table 2: Qualitative traits of the Gamo highland sheep in two districts
Number of observations
Chencha (%)
Qogota (%)
Total (%)
χ2
Sig.
White (30)
66.67
33.33
9.40
24.280
0.000
Brown (20)
0.00
100.00
6.30
Black (70)
42.86
57.14
21.90
Mixed (200)
35.00
65.00
62.50
Plain (140)
28.57
71.43
43.80
8.470
0.004
Patchy (180)
44.44
55.56
56.30
Polled (120)
20.83
79.17
37.50
22.760
0.000
Horned (200)
47.50
52.50
62.50
Straight (45)
0.00
100.00
22.50
66.330
0.000
Curved (135)
55.56
44.44
67.50
Spiral (20)
100.00
0.00
10.00
Lateral (45)
88.89
11.11
22.50
39.890
0.000
Obliquely backward (155)
35.48
64.52
77.50
Carried horizontal (250)
24.00
76.00
78.10
88.870
0.000
Semi pendulous (70)
85.71
14.29
21.90
Straight (310)
38.71
61.29
96.90
6.190
0.013
Slightly convex (10)
0.00
100.00
3.10
Present (25)
40.00
60.00
7.50
0.001
0.975
Absent (310)
40.32
59.68
92.50
Present (120)
100.00
0.00
35.80
227.003
0.000
Absent (215)
6.98
93.02
64.20
Hairy (240)
16.67
83.33
71.60
196.451
0.000
Woolly (95)
100.00
0.00
28.40
Straight (245)
30.61
69.39
73.10
35.564
0.000
Low crimp frequency <4/ cm
(90)
66.67
33.33
26.90
Covered (10)
100.00
0.00
3.00
15.271
0.000
Bare (325)
38.46
61.54
97.00
Bare (20)
100.00
0.00
6.00
31.511
0.000
Covered (315)
36.51
63.49
94.00
Covered (310)
40.32
59.68
92.50
0.001
0.975
Bare (25)
40.00
60.00
7.50
Covered(45)
44.44
55.56
13.40
3.697
0.157
Bare (285)
40.35
59.65
86.60
Well above hocks(135)
14.81
85.19
40.30
83.323
0.000
Near hocks(185)
62.16
37.84
55.20
Well below hocks(15)
0.00
100.00
4.50
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3.2. Live body weight and linear body
measurements
Live body weight and linear measurements body
measurements were an important growth and
economic trait. It was not always possible to measure
it due to mainly the lack of weighing scales,
particularly in rural areas. Body measurement can
also be used routinely in weight estimation and
selection programmes based on its utility in
determining breed evolution trends (Belete et al.,
2017).
3.2.1. Sex effect
The least-square means and standard errors for the
effect of sex and their interaction on body weight and
other body measurements are presented in Table 3.
Body weight and some other linear body
measurements have shown significant differences
between sexes. For traits showing significant
differences, males were larger than females. The
current results contradict with the sheep type in the
Selale area where females have larger linear body
measurements than their male counterparts
(Amelmal, 2011; Aberra et al., 2014).
3.2.2. Age effect
The size and shape of the animal increases until the
animal reaches maturity and the effect of age on body
weight and other body measurements was also
observed in sheep breeds of Ethiopia (Tesfaye, 2008).
Body weight and all body measurements were
significantly affected by age group as observed in
Table 2. Generally, the body measurements were
increased as the age increased from the age group
(1PPI) to the oldest 4PPI. Similar findings were
reported by Fsahatsion et al. (2018) who noted that
body weight and body measurements increased with
age of ewes for the first three years and then
decreased slightly for ewes above four years (Asefa
et al., 2017).
3.2.3. District effect
District had a significant effect (P<0.05) on body
weight and all other linear body measurements except
hair length and ear length. Sheep in the Chencha
district were higher on the above-mentioned traits
compared to that of the Qogota district. The findings
are in agreement with the report of Wossenie (2012)
and Asefa et al. (2017).
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Table 3: The least-square means and standard error (LSM ± SE) of body weight (kg) and linear body measurement (cm) of the Gamo sheep population
Traits (N)
BW
BL
HW
CG
HoL
HeL
HaL
EL
TL
Total (335)
20.26±3.60
54.55±3.48
55.13±3.83
66.73±4.79
9.42±7.46
16.83±1.85
7.41±3.12
10.27±0.97
26.62±2.66
R
2
0.83
0.70
0.71
0.86
0.94
0.57
0.78
0.56
0.39
Sex
*
*
*
*
*
*
*
*
NS
Male (65)
21.15±4.45
a
56.00±2.33
a
58.55±4.47
a
72.18±3.43
a
24.43±4.13
a
17.82±1.19
a
9.00±1.48
a
9.77±1.07
a
26.18±2.11
Female (270)
20.05±3.35
b
54.25±3.60
b
54.42±3.28
b
65.60±4.23
b
6.03±1.26
b
16.62±1.90
b
7.08±3.27
b
10.38±0.92
b
26.72±2.76
Location
*
*
*
*
*
*
NS
NS
*
Chencha (135)
20.76±4.01
a
56.00±3.04
a
55.46±3.18
a
67.12±4.23
a
10.53±7.34
a
17.08±0.96
a
7.29±2.41
10.54±0.65
27.79±2.41
a
Qogota (200)
19.93±3.27
b
53.68±3.44
b
54.93±4.17
b
66.50±5.12
b
8.32±7.47
b
16.68±2.21
b
7.49±3.49
10.11±1.09
25.92±2.56
b
Age
*
*
*
*
*
*
*
*
*
0PPI (70)
15.50±2.12
d
50.36±1.18
d
53.18±2.93
c
61.82±2.70
c
11.67±9.74
b
16.27±1.07
b
7.27±1.11
b
9.64±1.08
ab
25.64±2.50
ab
1PPI (85)
20.32±2.21
c
53.94±2.67
c
55.41±4.22
d
67.35±5.18
b
11.40±9.31
b
16.00±2.99
b
10.82±3.21
a
9.91±0.90
b
27.12±2.73
b
2PPI (50)
23.10±3.81
a
57.40±4.32
a
59.70±3.73
a
70.90±4.00
a
24.00±0.00
a
17.60±1.13
a
6.65±1.90
a
11.00±0.79
b
26.80±3.63
a
3PPI (85)
21.82±2.37
b
55.71±2.21
b
55.00±1.70
b
67.53±3.57
b
6.73±0.76
c
17.18±0.93
b
5.88±2.13
c
10.47±0.86
a
26.18±2.25
ab
4PPI (45)
21.44±2.03
b
55.44±2.26
b
52.11±1.89
c
65.44±3.37
b
5.78±1.48
c
17.56±0.51
b
4.89±1.70
c
10.56±0.51
a
27.56±1.60
ab
The means with different superscripts within the same column and class are statistically different. NS = Non significant (P>0.05); *Significant (p< 0.05); 0PPI =
0 pair of permanent incisors; 1PPI = 1 pair of permanent incisors; 2PPI = 2 pair of permanent incisors; 3 PPI = 3 pairs of permanent incisors; 4PPI = 4 pair of
permanent incisors; BL = Body length; BW = Body Weight; CG = Chest Girth; HW = Height Weather; HaL = Hair length; HeL = Head Length; HoL = Horn
Length; EL = Ear Length; TL = Tail length
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3.3. Correlation between body weight and linear
body measurements
According to Younas et al. (2013), determining
animal live body weight, linear body measurements,
and their inter-relationship and correlation is
imperative for determining genetic potential, breed
standards, and improved breeding programs. The
association between body weight and different linear
measurements for the Gamo highland sheep
population are presented in Table 4. The highest
coefficient of correlations was obtained between BW
and CG (r = 0.79), BL (r = 0.73) and HeL (r = 0.72).
These implied that a better prediction of body weight
could be obtained in Gamo highland sheep by using
chest girth, body length and head length as
independent variables. Almost similar findings were
presented for the positive and strong association
between BW and CH for other sheep breeds
(Solomon et al., 2011; Abera et al., 2014; Mesfin,
2015).
Table 4: Pearson correlation coefficient between body weight and different linear measurements for Gamo highland
sheep population
Traits
BW
BL
HW
CG
HoL
HeL
HaL
EL
TL
BW
BL
0.73
*
HW
0.54
*
0.40
*
CG
0.79
*
0.71
*
0.63
*
HoL
0.32
NS
0.21
NS
0.71
*
0.64
*
HeL
0.72
*
0.52
*
0.39
*
0.57
*
0.26
NS
HaL
-0.35
NS
-0.36
NS
0.19
NS
-0.07
NS
0.37
*
-0.42
*
EL
0.05
NS
-0.06
NS
-0.26
NS
-0.35
*
-0.40
*
-0.08
NS
-0.44
*
TL
0.42
*
0.08
NS
0.29
NS
0.10
NS
-0.09
NS
0.35
*
-0.47
*
0.50
*
NS = Non-significant (P>0.05); *statistically significant (P<0.05); BW = Body Weight; BL = Body length; CG =
Chest Girth; HW = Height at Weather; HaL = Hair length; HeL = Head Length; HoL = Horn Length; EL = Ear
Length; TL = Tail length
3.4. Prediction of body weight from linear body
measurements
The knowledge of livestock weight assessment
remains the backbone on which all animal production
management practices are hinged (Otoikhian et al.,
2008). Regression analysis was carried out to predict
the live body weight of an animal over independent
variables, which have a higher correlation with body
weight to set an adequate model for the prediction of
body weight as depicted in Table 5. In the current
study, live weight estimation using chest girth alone
would be preferable to combinations with other
measurements because of the difficulty of the proper
animal restraint during measurement and the low
proportion of animals at each dentition class as
well. The importance of chest girth in weight
estimation demonstrated in the present study could be
a result of the fact that muscle and some fat along
with bone structure contribute to its formation
(Okpeku et al., 2011). Several authors in similar
studies have concluded that heart girth can be used as
a sole predictor of body weight due to the high
associate regression coefficients obtained (Zewdu,
2008; Taye et al., 2010; Asefa, 2017). However, the
more measurement traits incorporated in the model,
the more body weight predicted.
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Publication of College of Agriculture and Environmental Sciences, Bahir Dar University 81
Table 5: Linear Regression coefficients for Gamo highland sheep population by stepwise method
Model
Unstandardized Coefficients
Standardized
Coefficients
t
R
2
Sig.
Beta
Standard error
Beta
Constant
-16.21
2.08
-7.78
0.000
CG
0.56
0.03
0.79
17.75
0.63
0.000
Constant
-40.98
2.92
-14.01
0.000
CG
0.65
0.03
0.92
24.36
0.76
0.000
EL
1.80
0.17
0.39
10.31
0.000
Constant
-48.51
2.93
-16.57
0.000
CG
0.56
0.03
0.80
19.91
0.80
0.000
EL
1.75
0.16
0.38
10.95
0.000
HeL
0.80
0.13
0.24
6.24
0.000
Constant
-50.65
2.86
-17.70
0.000
CG
0.46
0.04
0.65
12.47
0.82
0.000
EL
1.55
0.16
0.34
9.64
0.000
HeL
0.76
0.13
0.22
6.10
0.000
BL
0.21
0.05
0.19
4.06
0.000
Constant
-49.34
2.70
-18.26
0.000
CG
0.41
0.04
0.58
11.32
0.84
0.000
EL
0.95
0.19
0.21
4.95
0.000
HeL
0.57
0.12
0.17
4.67
0.000
BL
0.27
0.05
0.24
5.32
0.000
TL
0.31
0.06
0.20
5.03
0.000
CG = chest girth, EL= ear length, HeL= head length, BL= body length, TL= tail length
4. Conclusion and Recommendations
The characterization of sheep in this study was
helpful to livestock farmers and researchers in
preserving the genetic resources of the indigenous
Ethiopian sheep breeds. Even though the study areas
were rich in sheep resources, little has been done to
characterize, identify and document the existing
indigenous sheep types. The current study revealed
that Gamo highland sheep populations were
identified as multi-coloured, thin-tailed, and
moderately sized in general. Polymorphisms, both in
qualitative and morphometric traits, were inferring
considerable genetic variability. Therefore,
population divergence in these morphological traits
needs to be further verified by comparing relative
levels by the DNA markers.
Funding statement
This research received financial and material
supports from Southern Agricultural Research
Institute (SARI).
Data availability statement
Data will be made available on request.
Declaration of interest’s statement
The authors declare no competing interests.
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