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Determination of the Effect of Somatic Cell Count on Udder Measurements and Subclinical Mastitis with Data Mining Method
Hande Küçükönder1, Fatih Üçkardeş2, Ayhan Ceyhan3 and Mahmut Cinar3
1Faculty of Economics and Administrative Sciences, Bartin University, 74100 Bartin, Turkey; 2Department of Biostatistics and Medical Informatics, Faculty of Medicine, Adiyaman University, 02200 Adiyaman, Turkey; 3Department of Veterinary, Bor Vocational School, Nigde University, 51700 Bor / Nigde, Turkey
*Corresponding author:


In this study, it was aimed to determine the effect of somatic cell count (SCC) on udder measurements and subclinical mastitis in Holstein cows by data mining method. In the study, the udder measurements and the SCC values of milk samples taken monthly from 79 Holstein cows were used. The Bayesian Net, Decision Table and Nearest Neighbors algorithms were used in the classification of the udder measurements, and model validation is determined by the simple validation method. In the study, it has been found that the best classification model was formed according to the Nearest Neighbors algorithm with the accuracy rate of 97.95% [Root Mean Square Error (RMSE):0.07, Mean Absolute Error (MAE):0.01, Root Relative Squared Error- RRSE (%):22.20, Relative Absolute Error -RAE (%): 5.78, Kappa statistic: 0.95]. The effect of udder measurements on subclinical mastitis was found significant for the front teat length (FTL), the distance between rear teats (DBRT), the distance between side teats (DBST), the rear teat height (RTH) (P<0.01) and the rear teat diameter (RTD) (P<0.05).

Key words: Data mining, Holstein cow, SCC, Subclinical mastitis, Udder measurement


ISSN 0253-8318 (Print)
ISSN 2074-7764 (Online)