2011Unpublished venueRequires access

Performance Characteristics and Prediction of Bodyweight using Linear Body Measurements in Four Strains of Broiler Chicken

I. Udeh, G. Ukughere

Open publisher page 6 citations

Abstract

The objectives of this study were to co mpare the performance characteristics of four strains of broiler chicken from 2 to 8 weeks of age and predi ct body weight of the broilers using l inear body measurements. The four strains of b roiler chicken used were Anak, Arbor Acr e, Ross and M arshall. The parameters recorded were bodyweight, weight gain, total feed intake, feed conversion ratio, mortality and some linear body measurements (body length, body width, breast width, drumstick length, shank length, thigh length and wing length). Prediction equations relating body weight to linear body measurements at 2 and 8 weeks of age were established for the four strains of broilers using multiple regression method. The results indicated similarity in body weight at 8 weeks, weight gain and feed conversion ratio among Anak, Arbor Acre and Ross broilers. They were however, significantly (p<0.01) superior to Marshal in all these t raits. The regression analysis were highly significant (p< 0.001) for the two age periods and in all the strains. T he coefficient of multiple determinants (R 2 ) were more than 50% in most of the groups indicating that the prediction equations obtained in this study could be used to predict body weight of broilers.

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What this paper is about

The objectives of this study were to co mpare the performance characteristics of four strains of broiler chicken from 2 to 8 weeks of age and predi ct body weight of the broilers using l inear body measurements. The four strains of b roiler chicken used were Anak, Arbor Acr e, Ross and M arshall. The parameters recorded were bodyweight, weight gain, total feed intake, feed conversion ratio, mortality and some linear body measurements (body length, body width, breast width, drumstick length, shank length, thigh length and wing length). Prediction equations relating body weight to linear body measurements at 2 and 8 weeks of age were established for the four strains of broilers using multiple regression method. The results indicated similarity in body weight at 8 weeks, weight gain and feed conversion ratio among Anak, Arbor Acre and Ross broilers. They were however, significantly (p<0.01) superior to Marshal in all these t raits. The regression analysis were highly significant (p< 0.001) for the two age periods and in all the strains. T he coefficient of multiple determinants (R 2 ) were more than 50% in most of the groups indicating that the prediction equations obtained in this study could be used to predict body weight of broilers.

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Available abstract

The objectives of this study were to co mpare the performance characteristics of four strains of broiler chicken from 2 to 8 weeks of age and predi ct body weight of the broilers using l inear body measurements. The four strains of b roiler chicken used were Anak, Arbor Acr e, Ross and M arshall. The parameters recorded were bodyweight, weight gain, total feed intake, feed conversion ratio, mortality and some linear body measurements (body length, body width, breast width, drumstick length, shank length, thigh length and wing length). Prediction equations relating body weight to linear body measurements at 2 and 8 weeks of age were established for the four strains of broilers using multiple regression method. The results indicated similarity in body weight at 8 weeks, weight gain and feed conversion ratio among Anak, Arbor Acre and Ross broilers. They were however, significantly (p<0.01) superior to Marshal in all these t raits. The regression analysis were highly significant (p< 0.001) for the two age periods and in all the strains. T he coefficient of multiple determinants (R 2 ) were more than 50% in most of the groups indicating that the prediction equations obtained in this study could be used to predict body weight of broilers.

Key concepts: Broiler, Body weight, Animal science, Linear regression, Biology, Regression analysis, Feed conversion ratio, Weight gain

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