Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree method
<p>Egg quality traits are features of eggs that influence the general quality of the egg. This study aimed to establish models for the prediction of albumen weight and yolk weight in Potchefstroom Koekoek and Lohmann Brown layers with a classification and regression tree (CART) decision method...
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| Language: | English |
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Copernicus Publications
2025-06-01
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| Series: | Archives Animal Breeding |
| Online Access: | https://aab.copernicus.org/articles/68/365/2025/aab-68-365-2025.pdf |
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| author | V. R. Hlokoe T. L. Tyasi V. G. Mbazima |
| author_facet | V. R. Hlokoe T. L. Tyasi V. G. Mbazima |
| author_sort | V. R. Hlokoe |
| collection | DOAJ |
| description | <p>Egg quality traits are features of eggs that influence the general quality of the egg. This study aimed to establish models for the prediction of albumen weight and yolk weight in Potchefstroom Koekoek and Lohmann Brown layers with a classification and regression tree (CART) decision methods. The Pearson's correlation findings displayed that the albumen weight had a positively high remarkable (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) association with the egg weight, egg width and yolk weight, while yolk weight had a positively high significant (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) relationship with the egg weight and albumen weight in Potchefstroom Koekoek. In Lohmann Brown, the albumen weight had a positively high remarkable (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) association with the egg weight, egg width and egg length, while yolk weight had a positively high significant (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) relationship with the egg weight, egg width and egg length. The CART method produced good models for predicting the albumen weight, with <span class="inline-formula"><i>R</i><sup>2</sup></span> of 0.94 and 0.96, and yolk weight, with <span class="inline-formula"><i>R</i><sup>2</sup></span> of 0.93 and 0.92, in Potchefstroom Koekoek and Lohmann Brown layers, respectively. The egg weight was shown to be the best leading predictor of albumen and yolk weight in both breeds. This study suggests that CART decision methods might assist in determining the breed standards of Lohmann Brown and Potchefstroom Koekoek chicken breeds in order for breeding programmes to improve their egg production. In conclusion, albumen weight and yolk weight can be improved best with enhancement of the egg weight.</p> |
| format | Article |
| id | doaj-art-48a112c28183456bb2c778e9b8df8d52 |
| institution | OA Journals |
| issn | 0003-9438 2363-9822 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Archives Animal Breeding |
| spelling | doaj-art-48a112c28183456bb2c778e9b8df8d522025-08-20T02:24:07ZengCopernicus PublicationsArchives Animal Breeding0003-94382363-98222025-06-016836537610.5194/aab-68-365-2025Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree methodV. R. Hlokoe0T. L. Tyasi1V. G. Mbazima2Department of Agricultural Economics and Animal Production, University of Limpopo, Private Bag X1106, Sovenga 0727, Limpopo, South AfricaDepartment of Agricultural Economics and Animal Production, University of Limpopo, Private Bag X1106, Sovenga 0727, Limpopo, South AfricaDepartment of Biochemistry, Microbiology & Biotechnology, University of Limpopo, Private Bag X1106, Sovenga 0727, Limpopo, South Africa<p>Egg quality traits are features of eggs that influence the general quality of the egg. This study aimed to establish models for the prediction of albumen weight and yolk weight in Potchefstroom Koekoek and Lohmann Brown layers with a classification and regression tree (CART) decision methods. The Pearson's correlation findings displayed that the albumen weight had a positively high remarkable (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) association with the egg weight, egg width and yolk weight, while yolk weight had a positively high significant (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) relationship with the egg weight and albumen weight in Potchefstroom Koekoek. In Lohmann Brown, the albumen weight had a positively high remarkable (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) association with the egg weight, egg width and egg length, while yolk weight had a positively high significant (<span class="inline-formula"><i>P</i><i><</i>0.01</span>) relationship with the egg weight, egg width and egg length. The CART method produced good models for predicting the albumen weight, with <span class="inline-formula"><i>R</i><sup>2</sup></span> of 0.94 and 0.96, and yolk weight, with <span class="inline-formula"><i>R</i><sup>2</sup></span> of 0.93 and 0.92, in Potchefstroom Koekoek and Lohmann Brown layers, respectively. The egg weight was shown to be the best leading predictor of albumen and yolk weight in both breeds. This study suggests that CART decision methods might assist in determining the breed standards of Lohmann Brown and Potchefstroom Koekoek chicken breeds in order for breeding programmes to improve their egg production. In conclusion, albumen weight and yolk weight can be improved best with enhancement of the egg weight.</p>https://aab.copernicus.org/articles/68/365/2025/aab-68-365-2025.pdf |
| spellingShingle | V. R. Hlokoe T. L. Tyasi V. G. Mbazima Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree method Archives Animal Breeding |
| title | Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree method |
| title_full | Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree method |
| title_fullStr | Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree method |
| title_full_unstemmed | Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree method |
| title_short | Prediction of internal egg quality traits of Potchefstroom Koekoek and Lohmann Brown layers using classification and regression tree method |
| title_sort | prediction of internal egg quality traits of potchefstroom koekoek and lohmann brown layers using classification and regression tree method |
| url | https://aab.copernicus.org/articles/68/365/2025/aab-68-365-2025.pdf |
| work_keys_str_mv | AT vrhlokoe predictionofinternaleggqualitytraitsofpotchefstroomkoekoekandlohmannbrownlayersusingclassificationandregressiontreemethod AT tltyasi predictionofinternaleggqualitytraitsofpotchefstroomkoekoekandlohmannbrownlayersusingclassificationandregressiontreemethod AT vgmbazima predictionofinternaleggqualitytraitsofpotchefstroomkoekoekandlohmannbrownlayersusingclassificationandregressiontreemethod |