Application of Regression Tree Methodology in Predicting the Body Weight of Uda Sheep
This study aimed at evaluating the relationship between body weight and nine morphometric traits (withers height,rump height, body length, face length, rump length, chest circumference, head width, shoulder width and rumpwidth) of Uda sheep using regression tree technique. The data for the study wer...
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Agroprint Timisoara
2012-10-01
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doaj-785738d4fd6f4f52b0476caa660690822020-11-25T03:57:10ZengAgroprint TimisoaraScientific Papers Animal Science and Biotechnologies1841-93642344-45762012-10-01452484490356Application of Regression Tree Methodology in Predicting the Body Weight of Uda SheepAbdulmojeed Yakubu0Nasarawa State University, Keffi, Department of Animal Science, Shabu-Lafia Campus, LafiaThis study aimed at evaluating the relationship between body weight and nine morphometric traits (withers height,rump height, body length, face length, rump length, chest circumference, head width, shoulder width and rumpwidth) of Uda sheep using regression tree technique. The data for the study were generated from 499 Uda ramsrandomly selected from different herds in Nasarawa State, north-central Nigeria. Pearson’s moment correlation (r)between body weight and morphometric traits ranged from moderate to high values (r = 0.43-0.76; P≤0.01). Basedon the importance of the independent variables in predicting the body weight of sheep, five body measurementsnamely; chest circumference, shoulder width, rump width, body length and face length were found to be moreefficient. Thus, they were the variables entered to obtain the optimal regression tree. Among these five variables,chest circumference was found to be the primary splitting variable; and together with face length accounted for about62% of the variation in body weight. The regression tree analysis indicated that animals with chest circumference >87.45cm or ≤ 94.05cm and face length > 28.85cm could be expected to have higher body weights. This informationcould be exploited by livestock producers for management, selection and genetic improvement of Uda sheep.http://spasb.ro/index.php/spasb/article/view/432body measurementbody weightcorrelationtree regressionuda sheep |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Abdulmojeed Yakubu |
spellingShingle |
Abdulmojeed Yakubu Application of Regression Tree Methodology in Predicting the Body Weight of Uda Sheep Scientific Papers Animal Science and Biotechnologies body measurement body weight correlation tree regression uda sheep |
author_facet |
Abdulmojeed Yakubu |
author_sort |
Abdulmojeed Yakubu |
title |
Application of Regression Tree Methodology in Predicting the Body Weight of Uda Sheep |
title_short |
Application of Regression Tree Methodology in Predicting the Body Weight of Uda Sheep |
title_full |
Application of Regression Tree Methodology in Predicting the Body Weight of Uda Sheep |
title_fullStr |
Application of Regression Tree Methodology in Predicting the Body Weight of Uda Sheep |
title_full_unstemmed |
Application of Regression Tree Methodology in Predicting the Body Weight of Uda Sheep |
title_sort |
application of regression tree methodology in predicting the body weight of uda sheep |
publisher |
Agroprint Timisoara |
series |
Scientific Papers Animal Science and Biotechnologies |
issn |
1841-9364 2344-4576 |
publishDate |
2012-10-01 |
description |
This study aimed at evaluating the relationship between body weight and nine morphometric traits (withers height,rump height, body length, face length, rump length, chest circumference, head width, shoulder width and rumpwidth) of Uda sheep using regression tree technique. The data for the study were generated from 499 Uda ramsrandomly selected from different herds in Nasarawa State, north-central Nigeria. Pearson’s moment correlation (r)between body weight and morphometric traits ranged from moderate to high values (r = 0.43-0.76; P≤0.01). Basedon the importance of the independent variables in predicting the body weight of sheep, five body measurementsnamely; chest circumference, shoulder width, rump width, body length and face length were found to be moreefficient. Thus, they were the variables entered to obtain the optimal regression tree. Among these five variables,chest circumference was found to be the primary splitting variable; and together with face length accounted for about62% of the variation in body weight. The regression tree analysis indicated that animals with chest circumference >87.45cm or ≤ 94.05cm and face length > 28.85cm could be expected to have higher body weights. This informationcould be exploited by livestock producers for management, selection and genetic improvement of Uda sheep. |
topic |
body measurement body weight correlation tree regression uda sheep |
url |
http://spasb.ro/index.php/spasb/article/view/432 |
work_keys_str_mv |
AT abdulmojeedyakubu applicationofregressiontreemethodologyinpredictingthebodyweightofudasheep |
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