https://doi.org/10.52973/rcfcv-e34496
Received: 24/07/2024 Accepted: 07/10/2024 Published: 23/12/2024
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Revista Científica, FCV-LUZ / Vol. XXXIV, rcfcv-e34496
ABSTRACT
The morphological characterization of animal genetic resources
is a fundamental approach to ensure food security in developing
countries. The objective of this study was to morphologically
characterize the sheep of the Djelfa province, a prominent region in
sheep farming in Algeria. After evaluating 396 sheep, including 32
rams, and analyzing 34 parameters, including 19 quantitative ones, it
was found that sheep in this region are characterized by their white
color, with hind limbs spotted in fawn, pigmentation around the
nostrils, and drooping ears not exceeding the labial commissures,
as well as a ne, long tail extending beyond the hock. The ewes are
characterized by a long and eumetric body shape, with a subconcave
to straight prole along the dorsal line, and a semi–invading eece
with pigmentation around the udder. Rams, on the other hand, are
horned, hypermetric in body shape, with a straight prole of the
muzzle, and an invading eece with pigmentation around the scrotum
and prepuce. Analysis of quantitative data by PCA and Hierarchical
Cluster Analysis (HCA) revealed the presence of a small–sized group
in the Western regions of Djelfa and a large–sized group in the Eastern
regions. This morphological diversity results from the complex
interaction of biological, environmental, and economic factors.
Key words: Sheep; morphological trait; PCA analysis; Djelfa
RESUMEN
La caracterización morfológica de los recursos genéticos animales es
un enfoque fundamental para garantizar la seguridad alimentaria en
los países en desarrollo. El objetivo de este estudio fue caracterizar
morfológicamente las ovejas de la provincia de Djelfa, una región
destacada en la ganadería ovina en Argelia. Después de evaluar 396
ovejas, incluidos 32 carneros, y analizar 34 parámetros, incluidos
19 cuantitativos, Se encontró que las ovejas de esta región se
caracterizan por su color blanco, con miembros posteriores
manchados de color leonado, pigmentación alrededor de las fosas
nasales y orejas caídas que no sobrepasan las comisuras labiales, así
como una cola na y larga que se extiende más allá del corvejón. Las
ovejas se caracterizan por una forma corporal larga y eumétrica, con
un perl subcóncavo a recto a lo largo de la línea dorsal y un vellón
semi–invasor con pigmentación alrededor de la ubre. Los carneros,
por otro lado, tienen cuernos, forma corporal hipermétrica, con un
perl recto del hocico y un vellón invasor con pigmentación alrededor
del escroto y el prepucio. El análisis de datos cuantitativos mediante
PCA y análisis de conglomerados jerárquicos (HCA) reveló la presencia
de un grupo de tamaño pequeño en las regiones occidentales de
Djelfa y un grupo de tamaño grande en las regiones orientales. Esta
diversidad morfológica es resultado de la compleja interacción de
factores biológicos, ambientales y económicos.
Palabras clave: Oveja; caracteres morfológicos; Análisis PCA ; Djelfa
Morphological characterization of sheep in Djelfa province (Algeria)
Caracterización morfológica de ovejas en la provincia de Djelfa (Argelia)
Sahraoui Harkat
1
, Abbas Laoun
2
, Benalia Yabrir
2
* , Mohamed Lafri
1
1
University of Blida 1, Institute of Veterinary Sciences, Laboratory of Biotechnologies Related to Animal Reproduction (LBRA). Algeria.
2
University of Djelfa, Faculty of Nature and Life Sciences. Algeria.
*Corresponding author: byabrir@yahoo.fr
TABLE I
Quantitative parameters for morphological characterization
of Algerian sheep in Djelfa province
Parameter Symbol Denition
Body Weight
1
BdW Live weight
Head Length
2
HdL
Distance between the upper limit of the forehead to the
tip of the nose
Head Width
4
HdW Maximum distance between zygomatic arches
Ear Length
2
ErL
Distance from the base to the tip of the right ear, along
the dorsal surface
Ear Width
2
ErW Taken at the middle of the ear, on the outer side.
Neck Length
2
NkL
Distance from the throat to the tip of the shoulder in the
medium
Trunk length
3
TrL Measured from the tip of the shoulder to the tip of the hip.
Body Length
2
BdL Taken from the base of the head to the base of the tail.
Chest Width
3
ChW
Maximum intercostal diameter at the level of the 6
th
rib,
just behind the elbows
Rump Length
3
RpL Distance from hip to pin
Rump Width
3
RpW Maximum distance between left and right hurls
Ischium Width
3
IsW Distance between Ischia
Chest Girth
2
ChG Perimeter of the chest at the level of the 6
th
rib
Chest Depth
3
ChD
Vertical distance from the top of the withers to the xyfoid
process of the sternum
Wither Height
3
WtH Height from the top of the withers to the ground
Back height
3
BkH Back height taken at the middle of the back to the ground
Sacrum
height
3
ScH
Measured from the highest point of the sacrum down to
the bottom of the hoof
Cannon
Perimeter
2
CnP
Perimeter of the right foreleg, between the knee and the
pastern
Tail Length
2
TaL Distance from the root of the tail to the tip
The numbers indicate the measuring tools:
1
: Portable electronic scales,
2
: Metric
tapes,
3
: Measuring stick,
4
: Caliper. All the variables are taken in cm except the Body
Weight, which is taken in kg
Morphological traits of Algerian sheep / Harkat et al. _______________________________________________________________________________
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INTRODUCTION
The diversity of livestock genetic resources is vital for food security,
requiring prevention of genetic dilution to maintain adaptability to
climate change and diseases. Characterization of genetic resources
is essential for conservation and can be morphological, genetic, or
historical [1]. Morphological characterization details external traits
and performance within specic contexts, especially important in
developing countries. Molecular genetic characterization evaluates
genetic diversity through proteins and desoxyribonucleic acid
(DNA), offering high precision but needing signicant resources
[2]. Historical characterization explores the origins and evolution
of genetic resources to aid sustainable conservation strategies.
Both morphological and genetic approaches are complementary [3].
In Algeria, sheep (Ovis aries) farming is predominant in the steppe
region, representing about 80% of animal production with around 20
million sheep, contributing over 50% of national red meat output. Eight
sheep breeds are adapted to local conditions, with the Ouled–Djellal
breed being particularly favored for its productivity and adaptability,
notably in the central and eastern steppes, especially in Djelfa province
[4]. Djelfa Province is a key area for sheep farming and meat supply. This
study aims to characterize sheep in Djelfa using both quantitative and
qualitative morphological traits according to the Food and Agriculture
Organization of the United Nations (FAO) guidelines and identify any
morphological differences within the breed.
MATERIALS AND METHODS
Study area
This study was conducted in four municipalities in Djelfa Province:
Aïn Oussera (AO), Birine (BR), Hassi Bahbah (HB), and Sidi Ladjel (SL).
These areas are located between 650 m and 850 m above sea level,
are central to the Algerian steppe and play a crucial role in sheep and
merchandise transit. Livestock farming is the main income source, with
85% of the area being steppe–grazing lands. Djelfa, along with the studied
municipalities, is renowned for sheep farming and hosts the largest
livestock markets [5]. The region’s climate is semi–arid with cool winters.
The hottest month is July with an average maximum temperature of
36.9°C, while January is the coldest with an average minimum of 1.3°C.
The rainy season lasts from September to May, and the dry season from
June to August. Frost occurs between November and March, peaking in
January. Hot summer winds, “Sirocco,” prevail, averaging 3.4 m·s
–1
[6].
The soil is mainly limestone with good soil found in depressions.
Vegetation includes Aleppo pines, grasses like Alfa and sparte,
Chamaephytes on slopes, and saline soil plants such as Atriplex
halimus and Salsola vermiculata [6]. Livestock management of sheep
in Algeria is typically classied into two categories based on mobility:
sedentary or semi–sedentary systems, which utilize pastures within
50 km, and transhumant systems, characterized by movements of over
50 km that vary depending on the season. Djelfa breeders generally
prefer provinces in central and eastern Algeria, such as Médéa, Bouira,
Bordj Bou Arreridj, and Sétif [4, 5].
Animal sampling
The study was conducted on a total of 396 Ouled Djellal breed sheep,
including 32 rams, spread across 10 farms ranging in size from 72
to 612 heads and covering ve municipalities in different areas: Aïn
Oussera, Birine, Hassi Bahbah, and Sidi Laadjel; the sample size
ranged from 32 to 55 heads per farm. The phenotyping to individuals
was restricted at least 24 months old and non–pregnant ewes; 24
months marks the point at which sheep cease to grow [7]. Age
determination was conducted through dental examination using
the method outlined by Wilson and Durkin [8].
Morphological Characterization
Morphological characterization involves the assessment of 34
parameters, including 19 quantitative and 15 qualitative ones (TABLEI,
TABLE II), following FAO recommendations [1].
For the assessment of quantitative parameters, the following metric
tools were used in addition to a 150 kg First Kamer electronic scale
from France: a 150 mm Tiah digital caliper and a 150 cm tape measure
from China. In addition, a wooden measuring stick and a palette
composed of colored and coded leaves grouped in an improvised
fan from Algeria were used.
Statistical analyses
Data obtained was submitted to separate descriptive statistical
analyses for both sexes. For quantitative data, means, standard
deviations (SD), minimums (Min), maximums (Max), and standard
TABLE II
Qualitative parameters for morphological characterization
of Algerian sheep in Djelfa province
Parameter Symbol Parameter classes
Horn Presence
HP Present, Absent
Horn Shape HS Polled, Stumps, Curved, Spiral
Horn Orientation HO Polled, Stumps, Laterally
Ear Length EL Short, Medium, Long (relatively to labial commissure)
Ear Shape ES Erect, Semi–horizontal, Drooping
Face Prole FP Straight, Convex, Ultra convex
Tail Length TL
Short (above the hocks), Medium (about the hocks), Long
(below the hocks)
Tail Texture TT Fine, Greasy
Fleece Extente FE Invasive, Semi–invasive, Not invasive
Wattles Wls Present, Absent
Back Prole BP Straight, Sub–Concave
Head Colour HC White, White and Fawn
Fleece Colour FC O–white (OW), White Chalk (WC), Pale Yellow (PY)
Limb Colour LC White, White and fawn
Body Skin Colour
BSC Pigmented, Non–pigmented
TABLE III
Statistics for qualitative parameters for morphological characterization
of Algerian sheep in Djelfa province, according to sex
Parameter Modalities Rams Ewes
HP
Absent 3.13% 95.59%
Present 96.88% 4.41%
HS
Curved 0% 1.38%
Polled 6.26% 96.70%
HO
Stumps 65.63% 1.65%
Spiral 28.13% 0.28%
Laterally 28.13% 1.38%
Polled 3.13% 96.69%
ES
Stumps 68.75% 1.93%
Semi–horizontal 3.13% 7.44%
Drooping 96.88% 92.56%
EL
Long 3.13% 10.74%
Medium 25.00% 27.27%
Short 71.88% 61.98%
FP
Convex 90.88% 83.79%
Ultra convex 3.13% 0%
Straight 0% 16.53%
TL
Long 68.75% 45.18%
Short 0% 11.57%
Medium 31.25% 43.25%
TT
Fine 100% 100%
Greasy 0% 0%
FE
Invasive 43.75% 8.54%
Not invasive 0% 9.09%
Semi–invasive 56.25% 82.37%
WLs
Absent 100.00% 97.52%
Present 0% 2.48%
BP
Straight 37.50% 28.37%
Sub–Concave 62.50% 71.63%
HC
White 96.88% 96.42%
White and Fawn 3.13% 3.58%
FC
O–white 62.50% 50.14%
White Chalk 12.50% 26.99%
Pale Yellow 25.00% 22.87%
LC
White 84.38% 51.79%
White and Fawn 15.62% 48.21%
BSC
Non–pigmented 0% 3.58%
Pigmented 100.00% 96.42%
_____________________________________________________________________________Revista Cientifica, FCV-LUZ / Vol. XXXIV, rcfcv-e34496
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errors (SE) were calculated. For qualitative data, the percentages
of categories were determined. These analyses were performed
using Excel 2013. Additionally, multivariate descriptive analyses were
conducted to explore the formation of heterogeneous groups among
the sheep in this region. Principal Component Analysis (PCA) was
performed on quantitative data, and hierarchical clustering was
conducted using the “ward.D2” method after centering and scaling the
data. Initially, the number of clusters (k) was set to 4, representing the
regions, and then adjusted it based on the average silhouette index
to determine the optimal number of clusters. All statistical analyses
and visualizations were carried out using R software version 4.3.3 [9].
RESULTS AND DISCUSSION
Univariate Descriptive Analysis
The results of the qualitative data are presented in TABLE III.
The predominant color in both sexes is light white, representing
more than 50% of cases. Ewes are distinguished by hind limbs spotted
with fawn in approximately 50% of cases. The eece is mainly semi–
invading in ewes, reaching approximately 75%, while it is both invading
and semi–invading in rams, representing approximately 50% each.
Sheep in this region have a thin tail that extends beyond the hock level
in 100% of cases and do not possess wattles. The back silhouette
is sub–concave in approximately 70% of cases for both sexes, but
at the head level, it is arched in rams in about 90% of cases and
slightly arched or straight in ewes in about 80% of cases. Ears droop
in over 90% of cases and are short, not extending beyond the labial
commissures in about 70% of cases. Horns are present in rams and
absent in ewes, in over 95% of cases for both sexes.
The Algerian steppe, often termed as “sheep country,” is primarily
dedicated to sheep farming [10]. This farming practice plays a crucial
role in supplying red meat to major urban areas in Algeria [6, 11].
The predominant breed in this region is the Ouled–Djellal. While
debates persist about its origin, it remains one of the oldest and most
signicant breeds in Algeria, having evolved over centuries through
TABLE IV
Statistics for quantitative parameters for morphological characterization
of Algerian sheep in Djelfa province, according to sex
Parameter
Ewes Rams
M SD SE M SD SE
BdW
58.47 13.69 0.72 94.16 17.95 3.17
HdL 24.19 1.51 0.08 28.05 1.93 0.34
HdW 9.83 1.03 0.05 11.56 0.89 0.16
ErL 17.60 1.91 0.10 17.31 1.99 0.35
ErW 8.85 0.82 0.04 9.46 0.74 0.13
NkL 34.70 4.15 0.22 38.28 4.14 0.73
TrL 74.29 5.26 0.28 84.98 5.97 1.05
BdL 115.27 8.63 0.45 127.80 10.53 1.86
ChW 21.33 3.27 0.17 26.02 3.97 0.70
RpL 24.50 3.08 0.16 29.16 4.70 0.83
RpW 21.04 2.66 0.14 24.41 3.04 0.54
IsW 19.04 2.47 0.13 20.94 3.14 0.56
ChG 97.08 10.12 0.53 114.08 8.55 1.51
ChD 36.56 2.52 0.13 42.69 3.87 0.68
WtH 80.60 5.52 0.29 92.39 4.68 0.83
BkH 78.00 3.55 0.19 87.97 4.31 0.76
ScH 79.23 3.76 0.20 89.27 4.23 0.75
CnP 8.54 0.67 0.03 10.36 0.80 0.14
TaL
43.20 6.16 0.32 50.72 6.50 1.15
M: Mean, SD: Standard Deviation, SE: Standard Error
FIGURE 1. Correlation matrix for quantitative traits on ewe morphological data
of Algerian sheep in Djelfa province
Morphological traits of Algerian sheep / Harkat et al. _______________________________________________________________________________
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natural selection and traditional breeding practices, endowing it
with remarkable adaptability [12]. Sheep in this area are typically
white, with variations in shade depending on the breeding and
environmental conditions, although these variations are minimal.
Our ndings support previous conclusions by Chellig [4], Kheli
[13], and Djaout [14], who described these sheep as having white,
non–evasive eece, long and drooping ears, and a thin tail. They
also noted that these characteristics are similar between males
and females, with very slight differences. According to Craplet and
Thibier [7], sweat glands produce uids that, combined with foreign
particles, can slightly inuence the intensity of eece color, although
this modication is temporary. All authors working on phenotypic
diversity, like Chellig [4], Kheli [13], and Djaout [14], agree that sheep
in Algeria are characterized by a thin–tailed breed, while the fat–tailed
sheep only exist in Tunisia, Libya, and the Middle East in arid regions.
The quantitative data ndings are shown in TABLE IV, delineating
distinct characteristics between the sexes across most parameters.
Rams exhibit an average weight of 94.16 kg, categorizing them as
hypermetric, while ewes have an average weight of 58.47 kg, hence
classied as eumetric. Both sexes have slender heads, with HdL/HdW
ratios of 2.46 for rams and 2.47 for ewes. Ear length is relatively
consistent across sexes, averaging around 17 cm, although rams have
slightly broader ears. Rams also possess longer necks compared to
ewes; measuring 38.28 cm versus 34.70 cm. Body length is roughly
three times greater than width, with TrL/ChW and TrL/RpW ratios of
3.31 and 3.51 for rams, and 3.48 and 3.54 for ewes. Both sexes have long,
somewhat slender legs, with estimated heights of around 80 cm for ewes
and approximately 90 cm for rams, alongside a cannon circumference
of roughly 9 cm. Rams have a longer hip structure relative to width
compared to ewes, with RpW/RpL ratios of 0.80 and 0.90, respectively.
Finally, there is a minor discrepancy in tail length between the sexes,
measuring 50.72 cm for rams and 43.42 cm for ewes.
The ndings support those of Traoré [15], Laoun et al. [16], and
Harkat et al. [17], which indicate that males are generally heavier
and exhibit superior morphological parameters compared to females
beyond the growth stage, except for ear measurements (ErL and
ErW), which are similar (P>0.05). Chellig [4] and Djaout [14] describe
that sheep in this region are distinguished by two varieties: heavy
and light. The heavy varieties are larger, while the light variety is
smaller and predominates in the eastern region of the central steppe.
These observations are based solely on direct observations and
morphological measurements and are not inferential.
Principal Components Analysis (PCA)
The correlation matrix for the ewes shows that all correlation
coecients are positive (FIG. 1).
Various strengths of correlation are observed, ranging from
very strong (r = 0.80 to 0.99) between BkH and ScH, indicating high
correlation, to weak correlations (0.10 < r < 0.39). Bartlett’s test
results indicate a signicant departure of the correlation matrix
from the identity matrix, with a highly signicant p–value (P<0.05).
Thus, we reject the null hypothesis and conrm the suitability of
Principal Component Analysis (PCA) for exploring the data structure.
The Kaiser–Meyer–Olkin (KMO) coecient of 0.92 and Measures of
Sampling Adequacy (MSA) for each variable (ranging from 0.82 to
0.97) demonstrate very good sampling adequacy, indicating that
each variable signicantly contributes to the data structure and is
suitable for factor analysis. The Kaiser–Guttman test and the elbow
FIGURE 2. Correlation circle showing the correlation (cos
2
) and contribution
(contrib) of variables for ewes
FIGURE 3. PCA biplots for ewes
FIGURE 4. Correlation matrix for quantitative traits on ram morphological data
of Algerian sheep in Djelfa province
_____________________________________________________________________________Revista Cientifica, FCV-LUZ / Vol. XXXIV, rcfcv-e34496
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method suggest selecting two components. These two components
collectively explain 53% of the variance, with the rst component
explaining 45% and the second approximately 8%. Together, they
offer a substantial understanding of the data structure.
The variables BdW, ScH, TrL, ChD, BkH, ChG, ErW, CnP, and ChW
show notable characteristics with elevated cos
2
values, indicating
strong correlation and contribution with the primary component.
Conversely, the variable ErL demonstrates signicant correlation
and contribution with the second component (FIG. 2). In contrast,
variables NkL, HdW, and TaL exhibit poor representation across both
components (cos
2
≤0.30).
The biplot demonstrates a clear distinction between two clusters
of individuals (FIG. 3).
One cluster comprises individuals with signicant stature and
weight, mainly from Birine (BR) and Hassi Bahbah (HB), correlating
with larger and heavier morphological traits. Conversely, the other
cluster consists of smaller individuals in terms of stature and weight,
primarily from Sidi Ladjal (SL) and Aïn Oussera (AO), associated with
smaller and lighter morphological characteristics. Notably, individuals
from both clusters exhibit both long and short ears, which does
not correspond to regional distribution. This separation suggests
substantial differentiation between the two groups based on overall
morphological traits.
The correlation analysis for rams data reveals varying degrees of
correlation among different variables (FIG. 4).
Strong to very strong positive correlations (0.60 < r < 0.99) are
evident, such as between BdW and ChG (r = 0.83), indicating signicant
associations. Additionally, moderate positive correlations (0.40 < r
< 0.59) are observed, for instance, between ChW and RpL (r = 0.58),
suggesting relevant but less intense relationships. Conversely,
weak to very weak positive correlations (0.1 < r < 0.39) are noted,
including between NkL and TrL (r = 0.21), indicating less pronounced
connections. Furthermore, a few practically weak correlations, both
positive and negative (-0.09 < r < 0.09), such as between BdW and
ErL (r = – 0.09), highlight weaker yet present relationships. These
findings support the utilization of PCA for revealing underlying
data structures, as Bartlett’s test yields a very low p–value (P<0.05),
justifying the rejection of the null hypothesis H
0
The overall Kaiser–
Meyer–Olkin (KMO) coecient, indicating the sampling adequacy for
FIGURE 5. Correlation circle showing the correlation (cos
2
) and contribution
(contrib) of variables for rams
FIGURE 6. PCA biplots for rams
Morphological traits of Algerian sheep / Harkat et al. _______________________________________________________________________________
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Principal Component Analysis (PCA), is 0.66, suggesting a good t
for the analysis. Most variables have KMO values ranging from 0.59
to 0.92, indicating their signicant contribution to the data structure
and suitability for factor analysis. However, variables ErL, ErW, and
bkL exhibit lower contributions, with KMO values ranging from 0.30
to 0.45. The Kaiser–Guttman test, along with the elbow method,
suggests two components, explaining approximately 57% of the
total variance. The rst component captures around 47%, and the
second component around 10%, providing insight into a substantial
portion of the data structure.
According to the correlation circle, the majority of variables (BdW,
HdL, HdW, TrL, ChW, BdL, RpL, RpW, IsW, ChG, ChD, BkH, CnP, and
TaL) are well–correlated with the rst principal component of the
PCA, with r > 0.50 and a P–value < 0.05 (FIG. 5).
Hierarchical Cluster Analysis (HCA)
The results obtained from the analysis of dissimilarity among
individuals, assessed using the average silhouette index, reveal a
clear distinction between the groups. Indeed, after testing various
congurations, the highest silhouette score is 0.35 for ewes and
0.36 for rams, both occurring at K=2 clusters (FIG. 7 and 8). In
this conguration, two distinct groups of individuals were clearly
identied. On one side, we observe a set of individuals characterized
by their lightness and small size, primarily represented by sheep from
the locales of Sidi Laadjel (SD) and Aïn Oussera (AO). On the other side,
a group stands out with heavier and larger individuals, mainly from
the locales of Birine (BR) and Hassi Bahbah (HB) (TABLE V and VI).
The percentage of assignment to groups is shown in TABLE VII. Most
ewes from Hassi Bahbah (HB) and Birine (BR) are placed in group 2,
while those from Sidi–Ladjel (SD) and Aïn Oussera (AO) are mainly
assigned to group 1. However, this pattern differs for rams; rams from
HB are predominantly in group 2, while those from BR and SL are in
group 1. Rams from AO show an even distribution across both groups.
From this standpoint, researchers like Chellig [4] and Djaout
[14] have identied two distinct varieties within the Ouled–Djellal
sheep breed: a large–sized type predominant in the eastern steppe,
particularly in regions like M’sila, Biskra, and Sétif, and a small–sized
variety more common in the central steppe, notably in Djelfa and
Tiaret. These observations align with our study’s ndings in Djelfa
province, where sheep are categorized into large and small types.
The central and eastern parts of the province are mainly represented
by large sheep varieties like Birine (BR) and Hassi Bahbah (HB), while
smaller sheep types, such as those from Sidi Laadjel (SL) and Aïn
Oussera (AO), are more prevalent in the west. It’s interesting to note
that Chellig [4] referred to the small–sized variety as the "Chellalia
white breed", derived from its origin near Sidi Laadjel in Djelfa
province, close to Ksar Chellala in Tiaret province.
It is also observed that the variable RpW is correlated with the
second component with r = -0.59 and a P–value < 0.05. However, the
variables (ErL, NkL, ErW) are correlated with the third component
with r > 0.50. In terms of contribution, the variables that contribute
the most to the first component are BdW, TrL, and RpL, with
contribution values of 8.414, 0.784, and 6.844 respectively. For
the second component, the most contributive variables are ErL,
HdL, and ChW, with contribution values of 11.456, 8.332, and 13.695
respectively (FIG. 5). The biplot highlights three distinct groups of
individuals (FIG. 6). The rst group, mainly represented by rams from
Hassi Bahbah (HB), stands out due to their large size and high weight,
suggesting signicant morphological characteristics. The second
group, composed of rams from Aïn Oussera (AO) and Birine (BR),
exhibits average dimensions in terms of size and weight. Lastly, the
third group, consisting of rams from Sidi Ladjal (SL), is characterized
by smaller size and weight, indicating lighter morphological traits.
FIGURE 7. Dendrogram of Hierarchical Ascendant Classication (HAC) and silhouette index graph for ewes
FIGURE 8. Dendrogram of hierarchical ascendant classication (HCA) and silhouette index graph for rams
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Renard [18] emphasizes that the genetic makeup of domestic
species depends on both biological and economic forces. Regarding
the biological aspect, he suggests that the genetic heritage of
domestic species is constantly reshaped, beneting from a high
capacity for adaptation and variation due to frequent mechanisms
of mutation and sexual reproduction. As for the economic aspect,
Renard [18] observed that the selection of breeders has evolved from
natural selection to systematic human selection. Initially, the most
capable breeders were chosen for their ability to provide food and
labor, leading to the creation of locally adapted breeds.
TABLE V
Results of quantitative parameters among HCA
groups for rams. G1:group 1; G2: group 2
Parameter
Mean Median Min Max
G1 G2 G1 G2 G1 G2 G1 G2
BdW
77.28 106.80 80.00 105.00 41.00 96.00 96.00 121.50
HdL 27.50 28.42 27.50 28.00 23.00 26.00 31.00 32.50
HdW 10.95 12.01 11.10 12.10 8.90 10.20 11.90 12.90
ErL 17.69 17.07 17.00 17.25 15.00 14.50 21.50 22.00
ErW 9.28 9.57 9.50 9.60 7.80 8.50 10.50 10.50
NkL 37.62 38.61 38.50 38.25 31.00 29.00 45.00 46.00
TrL 81.12 87.33 80.00 86.50 68.00 80.00 89.50 95.00
BdL 120 132.70 122 132.00 98 120.00 133 153.00
ChW 24.12 27.22 24.50 26.00 17.00 22.50 30.50 38.50
RpL 25.81 31.53 29.00 32.25 15.00 23.50 30.50 36.00
RpW 23.31 25.06 24.00 24.50 20.00 20.00 26.00 31.50
IsW 20.27 21.03 20.50 20.75 15.50 17.00 25.00 26.00
ChG 106.90 118.90 108.00 120.00 86.00 112.00 121.00 126.00
ChD 41.38 43.53 41.50 44.50 33.00 27.50 43.00 47.00
WtH 89.23 94.47 91.00 95.00 74.00 91.00 95.00 99.00
BkH 86.15 89.06 87.00 90.00 71.50 83.00 97.00 93.00
ScH 86.50 91.03 87.50 91.75 73.00 82.00 91.00 94.00
CnP 9.86 10.68 10.00 10.65 7.80 9.50 10.60 11.90
TaL
48.12 51.97 47.00 51.25 35.00 43.00 65.00 65.00
TABLE V
Results of quantitative parameters among HCA
groups for ewes. G1:group 1; G2: group 2
Parameter
Mean Median Min Max
G1 G2 G1 G2 G1 G2 G1 G2
BdW
50.37 71.9 50.40 70.7 32.00 50.0 73.50 100.0
HdL 23.84 24.76 24.00 25.00 20.50 20.00 32.50 29.00
HdW 9.65 10.14 9.70 10.20 7.10 7.30 19.90 19.00
ErL 17.15 18.34 17.00 18.00 12.00 12.60 22.50 23.00
ErW 8.57 9.32 8.500 9.20 6.50 8.00 10.50 11.00
NkL 33.54 36.62 33.00 37.00 21.50 22.50 51.50 49.00
TrL 71.99 78.09 72.50 78.50 58.00 57.50 83.00 89.00
BdL 111.5 121.5 112.0 121.0 72.0 108.0 180.0 140.00
ChW 19.84 23.8 20.00 23.0 10.50 10.9 28.00 34.50
RpL 23.3 26.49 23.0 26.50 14.5 21.00 31.0 39.00
RpW 19.96 22.84 20.00 22.50 14.00 15.50 27.00 33.50
IsW 18.24 20.35 18.50 20.00 14.00 16.00 24.00 28.00
ChG 92.01 105.9 92.50 105.0 73.00 91.0 105.00 134.00
ChD 35.41 38.41 35.50 38.50 21.50 31.00 40.00 44.50
WtH 78.96 83.79 79.50 84.00 67.50 76.00 88.50 90.00
BkH 76.42 80.57 77.00 80.50 67.00 70.50 83.50 88.00
ScH 77.41 82.26 77.50 82.00 68.50 73.50 85.50 90.00
CnP 8.24 9.02 8.20 9.00 6.200 8.00 10.00 10.50
TaL
41.42 46.69 41.00 47.00 25.00 34.50 54.00 59.00
TABLE VII
Percentages of assignment to groups from HCA for
ewes and rams G1: group 1; G2: group 2
Locality
Ewes Rams
G1 G2 G1 G2
Birine (BR)
47.37 52.63 100.00 0.00
Ain Oussara (AO)
87.10 12.90 50.00 50.00
Sidi Ladjel (SL)
99.09 0.91 88.89 11.11
Hassi Bahbah (HB)
36.73 63.27 0.00 100.00
Morphological traits of Algerian sheep / Harkat et al. _______________________________________________________________________________
8 of 10
Socio–cultural and economic inuences play a signicant role in
the preservation and evolution of animal genetic heritage, particularly
through breeding practices, cultural preferences, and economic
pressures. Breeding practices reect the techniques and resources
used in production, aiming to fully exploit the potential of the raised
breed. The choice of a breed to raise is guided by its productive and
adaptive capacities. The production and reproductive performances
of the Djellalia and Hodnia varieties (large–sized varieties) of the
Ouled–Djellal breed have sparked the interest of breeders, thus
explaining their widespread distribution throughout the national
territory) [19]. However, climatic constraints have been highlighted by
Chellig [4], limiting this expansion; the Djellalia and Hodnia varieties,
although large–sized and robust, do not tolerate cold weather. In
contrast, the “Chellalia” variety, smaller in size, adapts better to the
cold climates of Djelfa. With the evolution of sheep farming systems
and the increasing trend towards sedentarization, as well as the shift
from extensive to semi–extensive and intensive farming methods,
where environmental conditions are controlled to some extent [20,
21], this climatic constraint could decrease in importance as a limiting
factor, thus promoting the expansion of these two varieties.
Sheep play a central and diverse role in Algerian societies,
encompassing various aspects including economic, social, cultural,
and symbolic dimensions [22]. The act of sacricing sheep during
Eid al–Adha holds signicant importance for Muslims, symbolizing
the faith of Ibrahim, submission to God, gratitude, and solidarity. It is
crucial to select high–quality sheep for this purpose to demonstrate
respect and prosperity. This ritual not only strengthens community
ties and preserves cultural traditions but also imparts values of
generosity and sharing to the younger generation [23, 24]. Hadbaoui
et al. [25] highlight the significant potential of the steppe for
producing sheep meat intended for Eid al–Adha, underscoring the
socio–cultural importance of breeding large–sized sheep possessing
the necessary qualities for sacrice.
In Algeria, breeding the Ouled–Djellal breed goes beyond mere
meat production. It is also a conspicuous practice that allows
breeders to showcase their prestige and social status. Festivals,
community gatherings, and religious celebrations such as Eid al–Adha
provide opportunities to exhibit these exceptionally high–quality
animals, thereby strengthening social bonds and respect within the
community [26].
_____________________________________________________________________________Revista Cientifica, FCV-LUZ / Vol. XXXIV, rcfcv-e34496
9 of 10
CONCLUSION
The data on the morphological characteristics of sheep in the
studied region reveal significant diversity, suggesting specific
adaptations to different local environments and lifestyles. This
morphological diversity is a valuable asset for herd resilience in the
face of changing environmental challenges and selective pressures.
In–depth analysis of individuals, particularly through techniques
such as Principal Component Analysis (PCA) and Hierarchical
Cluster Analysis (HCA), highlights the presence of distinct groups
of sheep based on their morphological characteristics. These results
underscore the importance of genetic variability within sheep
populations, as well as the inuence of human selection in shaping
these traits. Indeed, the diversity observed in the herds reects a
complex interplay of biological, environmental, and economic factors.
Conicts of interest
The authors declare no conict of interest
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