Abstract #T11
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
# T11
Metabolic and digestive disorders affect behavioral and productive parameters of lactating Holstein cows milked with an automatic milking system.
M. L. Stangaferro*1, J. O. Giordano1, 1Cornell University, Ithaca, NY.
Key Words: automation, health monitoring, dairy cow
Metabolic and digestive disorders affect behavioral and productive parameters of lactating Holstein cows milked with an automatic milking system.
M. L. Stangaferro*1, J. O. Giordano1, 1Cornell University, Ithaca, NY.
The objective of this observational retrospective cohort study was to compare behavior and productive parameters of lactating dairy cows that developed metabolic and digestive disorders (MDD; displaced abomasum, ketosis, indigestion and abomasal ulcers) versus cows that did not develop health disorders (Healthy Control; HC) up to 30 DIM. Records were retrieved from 1,995 completed lactations from cows at a commercial farm in central NYcollected by an automatic milking system (AMS) software (Lely T4C) from January 2014 to May 2016. Health event data were collected from DairyComp 305. Data collected up to 30 DIM by the milking unit of the AMS and neck-mounted electronic tags for automated rumination and activity monitoring was summarized daily and included: milk yield (MY), milk fat and protein percentage, milk fat:protein ratio (F:P ratio), body weight (BW), rumination time (RT), physical activity (ACT), and number of milkings per day (NM). Data were analyzed by ANOVA with repeated measurements using PROC MIXED of SAS. All parameters collected by the AMS (explanatory variables) were evaluated from 7 d before to 7 d after diagnosis of MDD (Day of diagnosis = D0). For cows in the HC group, average DIM at MDD diagnosis (9 DIM) was considered as D0. Cows with MDD (n = 275) had reduced RT (P < 0.01; greatest difference on D-1: 162 min/d), ACT (P < 0.01; greatest difference on D0: 163 units/d), MY (P < 0.01; greatest difference on D1: 13.3 kg/d), NM (<0.01; greatest difference on D-1 to D2: 0.8 visit/d), and BW from D-2 to D7 (P < 0.01; greatest difference on D7: 34 kg). Cows with MDD lost 72 kg from D-7 to D7 compared with 38 kg for HC cows (n = 789) in the same period of time. Furthermore, cows in the MDD group had increased milk fat percentage (P < 0.01; greatest difference on D1: 0.8%) and F:P ratio (P < 0.01; greatest difference on D1: 0.34). Milk protein percentage (P < 0.01) was greater from D-5 to D-2, and then lower from D0 to D7 for cows in the MDD than in the HC group. We conclude that cows which developed MDD exhibited changes in behavior and productive parameters around the time of clinical diagnosis. Thus, behavioral and productive parameters could be used to identify cows suffering metabolic and digestive disorders.
Key Words: automation, health monitoring, dairy cow