Volume 60 (2010) Issue: 2010 No#5-6

The evaluation of fat to protein ratio in milk as an indicator of calving to conception interval in dairy cows using various biostatistical methods

Author(s): Podpečan O, Mrkun J, Zrimšek Petra

Keywords:calving to conception interval, correlation coefficient, dairy cows, fat to protein ratio, ROC analysis, survival analysis

The effect of fat to protein ratio (FPR) in milk for the prediction of calving to conception interval (CC) in dairy cows is evaluated using different biostatistics' methods. Spearman rank correlation coefficient, a non-parametric alternative to the Pearson correlation coefficient was used to determine the correlation between reproductive parameters of the herd and the milk data record. In the time interval of 60 to 90 days postpartum the highest correlation was found between FRP and CC (r=0.415, p<0.05). FPR was diagnostically evaluated using ROC (receiver operating characteristics) analysis which is based on completed 2x2 tables. A complete ROC analysis, including the area under the curve (AUC), provides an index of accuracy by demonstrating the limits of FPR's ability to discriminate between cows with different CC interval. The optimal cut-off value of FPR at 1.34 provided the best discrimination power according to CC of 120 days. A cut-off value of FPR at 1.1 was selected to enable over 90% correct identification of cows with CC below 120 days. On the other hand, cows with FPR above 1.44 were over 90% correctly identified as cows with CC above 120 days. Kaplan-Meier survival curves show a significant difference in CC between cows with FPR lower and upper of 1.34. CC lower than 120 days was observed in 80%of cows with FPR lower than 1.34 and only in 40% of cows with FPR higher than 1.34. The FPR has been shown to be of benefit in the prediction of reproductive efficiency in dairy cows.

My account



ISSN: 0567-8315

eISSN: 1820-7448

Journal Impact Factor 2019: 0.693

5-Year Impact Factor: 0.629

Indexing: Thomson Reuters/Science Citation Index Expanded, Zoological Record, Biosis Previews, Web of Science, Journal Citation Reports, Google Scholar, SCIndeks, KoBSON, Genamics, Journal Seek, Research Gate, DOAJ, Journal Rate, SJR – SCImago Journal & Country Rank, WorldCat, Academic Journals Database, Medical Journals Links, MedSci, Pubget