Prediction of health disorders in dairy cows monitored with collar based on Binary logistic analysis
文献类型： 外文期刊
作者： Zhou, Xiaojing 1 ; Xu, Chuang 2 ; Zhao, Zixuan 2 ; Wang, Hao 3 ; Chen, Mengxing 2 ; Jia, Bin 3 ;
作者机构： 1.Heilongjiang Bayi Agr Univ, Coll Sci, Dept Informat & Comp Sci, Xinyang Rd, Daqing, Heilongjiang, Peoples R China
2.Heilongjiang Bayi Agr Univ, Coll Anim Sci & Vet Med, Heilongjiang Prov Key Lab Prevent & Control Bovine, Xinyang Rd, Daqing, Heilongjiang, Peoples R China
3.Heilongjiang Acad Agr Sci, Anim Husb & Vet Branch, Qiqihar, Heilongjiang, Peoples R China
关键词： disorders; binary logistic regression; prediction; rumination; activity; milk yield
期刊名称：ARQUIVO BRASILEIRO DE MEDICINA VETERINARIA E ZOOTECNIA （ 影响因子：0.4； 五年影响因子：0.4 ）
ISSN： 0102-0935
年卷期： 2023 年 75 卷 3 期
页码：
收录情况： SCI
摘要： The objective of this study was to analyze data on physical activity and rumination time monitored via collars at the farm coupled with milk yield recorded by the rotary milking system to predict cows based on several disorders using the binary Logistic regression conducted with R software. Data for metritis (n=60), mastitis (n=98), lameness (n=35), and digestive disorders (n=52) were collected from 1,618 healthy cows used to construct the prediction model. To verify the feasibility and adaptability of the proposed method, we analyzed data of cows in the same herd (herd 1) not used to construct the model, and cows in another herd (herd 2) with data recorded by the same type of automated system, and led to detection of 75.0%, 64.2%, 74.2%, and 76.9% animals in herd 1 correctly predicted to suffer from metritis, mastitis, lameness, and digestive disorders, respectively. For cows in herd 2, 66.6%, 58.8%, 80.7%, and 71.4% were correctly predicted for metritis, mastitis, lameness, and digestive disorders, respectively. Compared with traditional clinical diagnoses by farm personnel, the algorithm developed allowed for earlier prediction of cows with a disorder.
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