Phenotypic Characterization of Indigenous Goat Types in West Gojjam Zone, Amhara National Regional State, Ethiopia

Bekalu Muluneh, Kefelegn Kebede, Yoseph Mekasha


The study was carried out in Bahirdar Zuria, Yilmana Densa and Gonji Kolela districts of Western Gojjam zone of Amhara National Regional State. The objectives of the study were to undertake phenotypic characterization of indigenous goat type found in the study area under farmers’ management condition and to develop equation for prediction of body weight by using linear body measurements. A total of 600 goats were sampled randomly for characterization of phenotypic traits. Data were gathered through field observations and linear body measurements of sample populations. The Sampled goats were identified by sex, age and district. The most dominant coat color patterns in the sampled populations were plain and patchy with the most frequently observed coat color type being brown and fawn followed by white. Sex of animals had significant effect on all of the body measurements, except ear length, tail length and horn length. District effect was not significant (p>0.05) for all of the body measurements. Dentition classes of animals contributed significant differences to body weight and most of the linear body measurements. The result of the multiple regression analysis showed that chest girth explained more variation than any other linear body measurements in both does (88%) and bucks (91%). The prediction of body weight could be based on regression equation y = -40.35 + 0.65x for female sample population and y = -33.71 + 0.82x for male sample goat population where y and x are body weight and chest girth, respectively. Most of the body measurements of goats were affected by sex and dentition class differently, whereas district effect was not apparent across all of the body measurements. Further characterization of goats in the study area at molecular level should be done.

Keywords: Body weight, characterization, indigenous, linear body measurement,   regression

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ISSN (Paper)2224-3208 ISSN (Online)2225-093X

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