Subclinical mastitis prediction in dairy cattle by application of fuzzy logic
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Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
University of Agriculture
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The main purpose of this study was to detect subclinical mastitis in a large sized dairy herd milked using automated milking systems. Recording of data was performed on the private dairy farm Karapinar of the province of Konya, Turkey. A data set of 346 milkings from 170 cows was used. Mastitis alerts were generated via a Fuzzy Logic (FL) model with the input data of lactation rank (current lactation number), milk yield, electrical conductivity, average milking duration and season. The output variable was somatic cell counts obtained from milk samples collected monthly throughout the 15 months of the sampling period. Cattle were judged healthy or infected based on somatic cell counts. The evaluation of the model was carried out according to sensitivity, specificity and error rate. The FL model yielded 82% sensitivity, 74% specificity, and 60% error. Fuzzy logic seems one of the useful tools to develop a detection model for mastitis. With more informative parameters, the error rate can be decreased. © 2015, University of Agriculture. All rights reserved.
Açıklama
Anahtar Kelimeler
Bacterial disease, Dairy cattle, Fuzzy logic, Somatic cell count, Subclinical mastitis
Kaynak
Pakistan Journal of Agricultural Sciences
WoS Q Değeri
Scopus Q Değeri
Q3
Cilt
52
Sayı
4
