Advances in Animal and Veterinary Sciences

Research Article
Adv. Anim. Vet. Sci. 8(4): 354-359
Http://dx.doi.org/10.17582/journal.aavs/2020/8.4.354.359
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Thobela Louis Tyasi1*, Kgotlelelo Maaposo Makgowo1, Kwena Mokoena1, Lebo Trudy Rashijane1, Madumetja Cyril Mathapo1, Lebogang William Danguru1, Kagisho Madikadike Molabe1, Paul Mogowe Bopape1, Nhlakanipho Divine Mathye1, Dannis Maluleke1, Busisiwe Gunya1, Masibonge Gxasheka2

1School of Agricultural & Environmental Sciences, Department of Agricultural Economics and Animal Production, University of Limpopo, Private Bag X1106, Sovenga 0727, Limpopo, South Africa; 2School of Agricultural & Environmental Sciences, Department of Plant Production, Soil Science & Agricultural Engineering, University of Limpopo, Private Bag X1106, Sovenga 0727, Limpopo, South Africa.

Abstract | Classification and regression tree analysis is a powerful statistical technique which helps to determine the most important variables in a particular dataset and helps to create a model. The study was conducted to identify linear body measurement traits (beak length, body length, keel length, chest circumference, toe length, body girth, shank length, back length, shank circumference and wing length) which could be employed in developing an effective prediction equation for body weight of Potchefstroom Koekoek laying hens. Eighty Potchefstroom Koekoek laying hens at twenty two weeks old were used. Pearson’s correlation together with classification and regression tree (CRT) methods were used for analysis. Descriptive statistics indicated that mean of body weight was 1.50 kg. Correlation findings revealed that body weight was positively significantly correlated (P < 0.05) with beak length (r = 0.23) and toe length (r = 0.21), respectively. CRT results demonstrated that beak length, wing length and back length play an important role in the body weight of Potchefstroom Koekoek laying hen chickens. This study suggests that body weight of laying hens could be estimated by some linear body measurement traits. The models established in the current study might be employed by chicken farmers when making selection during breeding to improve body weight. However, further studies need to be done to validate the use of classification and regression tree analysis in prediction of body weight from linear body measurement traits of chickens.

Keywords | Back length, Beak length, Body measurements, Correlation, Wing length