RT Journal
T1 PREDICTION OF 305 DAYS MILK YIELD FROM EARLY RECORDS IN DAIRY CATTLE USING ON FUZZY INFERENCE SYSTEM
A1 O. Gorgulu
JF Journal of Animal and Plant Sciences
JO JAPS
SN 1018-7081
VO 28
IS 4
SP 996
OP 1001
YR 2018
FD 2018/08/01
DO DOI NA
AB In the present investigation, Adaptive Neuro Fuzzy Inference System (ANFIS) was implemented to predict 305 d milk yield using partial lactation records of Jersey dairy cattle. The input variables for the system in the study were age, lacta- tion number and milk yields for the first three test-days. The output variable from the system was 305 d milk yield. AN- FIS results related to the milk yields were compared with observed values. Three criteria considered in order to control the reliability of system predictions were the ratio of mean, determination coefficient, and root mean square error. In addition to, the accuracies of ANFIS were compared using the absolute difference between the observed and predicted 2 305 d milk yield. R , RMSE, and RoM values are in the acceptable range. As a conclusion, ANFIS predictions at the beginning of the lactation are related closely to the observed 305 d-lactation yield. The results indicated that ANFIS can be successfully applied for 305 d milk yield early prediction. put using fuzzy logic which then offers a base from which
K1 ANFIS, dairy cow, Fuzzy logic, Inference System, 305d lactation yield
PB Pakistan Agricultural Scientists Forum
LK https://thejaps.org.pk/AbstractView.aspx?mid=2018-JAPS-406