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An investigation of machine learning methods applied to genomic prediction in yellow-feathered broilers

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成果类型:
期刊论文
作者:
Liu, Bogong;Liu, Huichao;Tu, Junhao;Xiao, Jian;Yang, Jie;...
通讯作者:
Zhang, HH
作者机构:
[He, Xi; Zhang, Haihan] Hunan Agr Univ, Coll Anim Sci & Technol, Changsha, Hunan, Peoples R China.
[He, Xi; Zhang, Haihan] Hunan Engn Res Ctr Poultry Prod Safety, Changsha, Hunan, Peoples R China.
[Zhang, Haihan] Yuelushan Lab, Changsha 410128, Peoples R China.
Hunan Xiangjia Husb Co Ltd, Changde, Hunan, Peoples R China.
通讯机构:
[Zhang, HH ] H
Hunan Agr Univ, Coll Anim Sci & Technol, Changsha, Hunan, Peoples R China.
语种:
英文
关键词:
Genomic prediction;Machine learning;Broiler;Genomic selection
期刊:
Poultry Science
ISSN:
0032-5791
年:
2025
卷:
104
期:
1
页码:
104489
基金类别:
Major project of agricultural biological breeding, Hunan Poultry Industry Technology System [2023ZD04064]; Hunan Poultry Industry Technology System; China Agriculture Research System of MOF and MARA [CARS-41-Z08]
机构署名:
本校为第一且通讯机构
院系归属:
动物科学技术学院
摘要:
Machine learning (ML) methods have rapidly developed in various theoretical and practical research areas, including predicting genomic breeding values for large livestock animals. However, few studies have investigated the application of ML in broiler breeding. In this study, seven different ML methods—support vector regression (SVR), random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), kernel ridge regression (KRR) and multilayer perceptron (MLP) were empl...

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