Abstract #T183
Section: Production, Management and the Environment
Session: Production, Management & the Environment II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall B
Session: Production, Management & the Environment II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall B
# T183
An evaluation of technology-recorded rumination and feeding behaviors in dairy heifers.
M. A. Myers*1,2, J. A. Davidson2, M. R. Borchers3, C. M. Bradley2, J. M. Bewley3, 1Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, 2Purina Animal Nutrition Center, Gray Summit, MO, 3Department of Animal and Food Sciences, University of Kentucky, Lexington, KY.
Key Words: rumination, feeding behavior, precision dairy monitoring
An evaluation of technology-recorded rumination and feeding behaviors in dairy heifers.
M. A. Myers*1,2, J. A. Davidson2, M. R. Borchers3, C. M. Bradley2, J. M. Bewley3, 1Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, 2Purina Animal Nutrition Center, Gray Summit, MO, 3Department of Animal and Food Sciences, University of Kentucky, Lexington, KY.
Precision dairy monitoring technologies have become increasingly popular for recording rumination and feeding behaviors in dairy cattle. The objective of this study was to validate the rumination (RM) and feeding time (FT) functions of the CowManager SensOor (Agis, Harmelen, Netherlands) against visual observation. The study was conducted in the Heifer Innovation Unit at the Purina Animal Nutrition Center in Gray Summit, Missouri. The study took place over a 44 d period beginning June 1st, 2016. Holstein heifers (n = 49) were split into 2 groups based on age, diet, and housing type. Group 1 heifers (n = 24) were approximately 2 ± 2.69 mo in age, fed hay and starter, and housed on a straw bedded pack. Group 2 heifers (n = 25) were approximately 17 ± 1.33 mo in age, fed a TMR, confirmed pregnant, and housed in free stalls. Visual observation shifts occurred at hours 1500, 1700, 1900, and 2100, lasting for 1 h. Each heifer was observed for 2, 1h periods with both observation periods occurring on the same day. Visual observations were collected using a satellite-synced watch and a “start” and “stop” time were recorded. Concordance correlations (CCC; epiR package; R Foundation for Statistical Computing, Vienna, Austria) and Pearson correlations (r; CORR procedure; SAS Institute Inc., Cary, NC), were used to calculate association between visual observations and technology-recorded behaviors. The visually observed RM was correlated with the CowManager SensOor (r = 0.63, CCC = 0.55). Visually observed FT was also correlated with the CowManager SensOor (r = 0.88 CCC = 0.72). A difference of technology-recorded data from visual observation was treated as the dependent variable in a mixed linear model (MIXED procedure of SAS). Time of day, age in months, and group were treated as fixed effects. Individual heifers were treated as random and repeated effects. Fixed effects were not significant (P ≥ 0.05) on the difference of SensOor data from visual observation. Based on these results, the CowManager Sensoor was more effective at recording feeding behavior than rumination behavior in dairy heifers.
Key Words: rumination, feeding behavior, precision dairy monitoring