The Use of Fuzzy Logic Approach in Evaluation of Subclinic Mastitis

Abstract

This study was carried out with the aim of investigating the possibility of detection of subclinical mastitis in the number of Somatic Cell Count and Electrical Conductivity by using fuzzy logic method in Holstein cows raised in a private operation in the Karapinar district of Konya.

                As a result of the analysis, mean of somatic cell count was 348153 ± 52340 and average of electrical conductivity was 4.23 ± 0.18. Linear regression of electrical conductivity and milk oil to somatic cell count were found to be very important (P <0.01), while the parity was insignificant to the somatic cells count. For the electric conductivity, the effect of the parity, animal group and the protein group was very important (P <0.001) and the effect of the milk fat group was significant (P<0.05). In the analysis according to the fuzzy logic method, the accuracy ratio between the number of somatic cells count and the electrical conductivity was determined as 92.45%.

                As a result, 92% of subclinical mastitis can be correctly detected using the number of somatic cells and electrical conductivity values.