TY  - JOUR
T1  - Morphological Characterization of IndigenousArsi-Bale Sheep in the Oromia Regional State,
Ethiopia
AU - Mamo, Birhanu AU - Wakeyo, Oli 
JO  - Agricultural Journal
VL  - 15
IS  - 4
SP  - 71
EP  - 77
PY  - 2020
DA  - 2001/08/19
SN  - 1816-9155
DO  - aj.2020.71.77
UR  - https://makhillpublications.co/view-article.php?doi=aj.2020.71.77
KW  - breeds
KW  -linear body measurement
KW  -qualitative character
KW  -phenotypic characterization
KW  -Arsi-Bale sheep
AB  - Description of the physical characteristics of
livestock breeds is very important for developing a
breeding strategy in a particular production system. Arsi-
Bale sheep are among the potential breeds of Ethiopia
reared in the mixed crop and livestock production system
of Oromia Ethiopia. This research was conducted to
characterize the morphological features of Arsi-Bale
sheep in an attempt to develop a breeding strategy that
suits the production system of the area. A total of 777
sheep were characterized for different morphological
features. Most 503 of the sheep in the flock were females
and 274 were male sheep of four and above dentition
classes. Browncoat colour was abundant (34%) and
60.7% of the colour pattern was plain. Arsi-Bale sheep
were long fat-tailed (87.9%) and hairy (73.7%). The
overall least square mean body weight was 25.9±0.2 kg
and was affected by sex and age of sheep. The mean chest
depth (26.85±0.3),heart girth (68.8 ± 0.4 cm), body length
(41.6±0.4cm), horn length (7.4±0.2 cm) and tail
circumference(18.4±0.1cm) were also affected by sex and
dentition. Positive and significant correlations were
obtained between body weight and other linear body
measurements. The highest correlation coefficient was
between body weight and chest depth. The positive and
significant correlation of weight with linear body
measurements indicates that linear body measurements
can be used as a marker to estimate weight for different
purposes. For breeding and selection purposes, since,
there is a need to be more precise use of models involving
more number of variables is important.
ER  -