Dairy Cattle Culling Patterns, Explanations, and Implications

Abstract

Culling patterns in the Upper Midwest and Northeast regions were examined from Dairy Herd Improvement records from 1993 through 1999. There were 7,087,699 individual cow lactation observations of which 1,458,936 were complete. A probit regression model was used to determine how individual cow and herd characteristics affected the likelihood of a cow being culled. The model predicted whether individual cows were culled each month. With a combination of observable cow and herd characteristics, as well as variables to capture state, year, and farm effects, the model was able to explain, with a 79.5 and 79.9% accuracy rate, individual cow cull decisions in the Upper Midwest and Northeast regions, respectively. Summer (−11.5% in the Upper Midwest;−6.4% in the Northeast) and fall (−18.7% in the Upper Midwest;−7.9% in the Northeast) calving vs. spring calving, higher than average milk production (−1.7% per hundredweight in the Upper Midwest;−0.5% in the Northeast), higher than average protein content (−0.2% per additional percentage milk protein in the Upper Midwest;−0.1% in the Northeast), higher milk production persistency (−2.1% per additional percent persistent in the Upper Midwest;−1.8% in the Northeast), and expansion (during the early years following the expansion) were associated with a reduced likelihood of a cow being culled. Lower than average fat content (0.04% per additional percentage butterfat in the Upper Midwest; 0.02% in the Northeast), and higher than average somatic cell count (8.8% for each unit increase in somatic cell count score in the Upper Midwest; 7.8% in the Northeast) were associated with an increased likelihood of a cow being culled. The study results are useful in describing patterns of culling and relating them to cow, herd, geographic, and time variables and can act as a benchmark for producers.