Abstract #T41
Section: Animal Health
Session: Animal Health II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall B
Session: Animal Health II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall B
# T41
Impact of culling for SCC, milk revenue, and estimated breeding values on herd performance.
K. Kaniyamattam*1, A. De Vries3, L. W. Tauer2, Y. T. Grohn1, 1Section of Epidemiology, College of Veterinary Medicine, Cornell University, Ithaca, NY, 2Charles H. Dyson School of Applied Economics and Management, Cornell University, Ithaca, NY, 3Department of Animal Sciences, University of Florida, Gainesville, FL.
Key Words: Bulk Tank SCC, modeling, profit
Impact of culling for SCC, milk revenue, and estimated breeding values on herd performance.
K. Kaniyamattam*1, A. De Vries3, L. W. Tauer2, Y. T. Grohn1, 1Section of Epidemiology, College of Veterinary Medicine, Cornell University, Ithaca, NY, 2Charles H. Dyson School of Applied Economics and Management, Cornell University, Ithaca, NY, 3Department of Animal Sciences, University of Florida, Gainesville, FL.
Our objective was to compare the economic, genetic and technical performance of a dairy herd implementing 6 different voluntary culling strategies for lowering bulk tank somatic cell count (BTSCC) with simultaneous maximization of milk revenues over a period of 15 yr. An existing stochastic dynamic dairy simulation model with 12 correlated genetic traits included in the 2014 lifetime net merit index ($NM) was used. The phenotypic performance of each animal’s 12 traits, (for example, daily SCC) was affected by their respective genetic and environmental component, along with a standard phenotypic function. Estimated breeding values (EBV) with genomic reliabilities were simulated for each animal, based on which selection and culling decisions were made. Genetic trends for sires in the model were similar to 15 yr projected trends for US Holsteins. In all 6 strategies simulated, surplus heifers born in the herd were culled based on lowest $NM to maintain a herd size of 1,000 milking cows. Whenever there was an incoming heifer, the lowest ranking cow was culled following 1 of these 6 strategies: I) daily SCC (highest phenotypic SCC), II) weighted average of SCC (highest moving average of SCC until day of culling), III) daily milk revenues (lowest milk revenues), IV) weighted average of milk revenues (lowest moving average of milk revenues until day of culling), V) EBV of SCS (highest SCS), and VI) EBV of $NM (lowest $NM), respectively. The 15 yr simulation results showed that the genetic performance of all the 6 strategies did not differ for the $NM trait. The true breeding value of the milk, fat and protein showed a difference of 120 kg, 3.9 kg and 3.6 kg, respectively, in year 15 between strategies IV and I. The phenotypic milk production, average BTSCC and profit per cow per yr differed by 108 kg, 10,920 cells/mL and $20, respectively, in yr 15 between strategies IV and I. The cumulative 15-year net present value of return per cow was −$190, $16, $30, −$736 and $52 higher than strategy I for strategies II, III, IV, V and VI, respectively. Hence, we conclude that culling the cows with the lowest EBV of $NM is economically the best strategy to lower BTSCC, with simultaneous maximization of milk revenues.
Key Words: Bulk Tank SCC, modeling, profit