Abstract #221
Section: Production, Management and the Environment (orals)
Session: Production, Management, and the Environment 2
Format: Oral
Day/Time: Monday 2:30 PM–2:45 PM
Location: Room 204
Session: Production, Management, and the Environment 2
Format: Oral
Day/Time: Monday 2:30 PM–2:45 PM
Location: Room 204
# 221
Association of management practices, housing, milking speed and robot visits with milk production per cow on free-flow automatic milking system farms.
M. Peiter*1, E. Irwin2, B. Groen3, J. A. Salfer4, M. I. Endres1, 1Department of Animal Science, University of Minnesota, St. Paul, MN, 2Department of Animal Science, Iowa State University, Ames, IA, 3Form-A-Feed, Stewart, MN, 4University of Minnesota Extension, St. Cloud, MN.
Key Words: automatic milking system, management, housing
Association of management practices, housing, milking speed and robot visits with milk production per cow on free-flow automatic milking system farms.
M. Peiter*1, E. Irwin2, B. Groen3, J. A. Salfer4, M. I. Endres1, 1Department of Animal Science, University of Minnesota, St. Paul, MN, 2Department of Animal Science, Iowa State University, Ames, IA, 3Form-A-Feed, Stewart, MN, 4University of Minnesota Extension, St. Cloud, MN.
Automatic milking systems (AMS) are common in Europe and have grown in popularity recently in the USA. The objective of this study was to investigate the association between management practices, housing, milking speed and robot visits with milk production/cow on free-flow cow traffic farms. We visited 36 AMS (Lely Astronaut, Lely, the Netherlands) farms in Minnesota and Wisconsin over the summer of 2018. Producers answered a survey about general farm management practices and barn characteristics. In addition, we collected retrospective daily data from the AMS software. We used data for the 30 d (1,080 daily averages) before the farm visit to evaluate the association of management and housing factors with milk production/cow (kg/d). The MIXED procedure of SAS 9.4 (SAS Institute, Inc., Cary, NC) was used to analyze the data. Backward stepwise elimination was used to remove nonsignificant factors until all remaining factors had a P < 0.05 in the final model. Farm was used as random effect. Average milk production/cow was 37.6 (±4.4) kg/d. Results from the multivariable analysis are presented as least squares means (±SE). Amount of daily concentrate offered in the robot was associated with increased milk production/cow. For every additional kg of concentrate offered, cows increased milk production by 1.3 (±0.2) kg/d. Successful milkings and refusals were also associated with daily milk production/cow. For each 1-unit increase in milkings/d, cows produced 8.9 (±0.3) kg more milk/d. Conversely, refusals had a negative association with milk production. For each unit increase in refusals, there was a decrease in milk production of 0.4 (±0.1) kg. As expected, higher milking speed resulted in higher milk production. For each additional kg of milk milked per minute, milk production per day increased by 4.2 (±0.2) kg. Milking time (sec) was also associated with higher milk production (0.06 (±0.003) kg/d), potentially a result of proportion of high producing cows in the herd. Results indicate that feeding practices and cow visit behavior can influence cow productivity in AMS.
Key Words: automatic milking system, management, housing