Abstract #319

# 319
Validation of an accelerometer to monitor rumination, eating and activity in an organic grazing dairy herd.
G. Pereira*1, B. Heins1, M. Endres2, 1University of Minnesota, West Central Research and Outreach Center, Morris, MN, 2University of Minnesota, Department of Animal Science, St.Paul, MN.

The objective of this study was to validate an accelerometer (CowManager SensOor, Agis Automatisering BV, Harmelen, the Netherlands) by direct visual observation in an organic grazing dairy herd. The sensor detects and identifies ear movements and through algorithms can classify data as ruminating, eating, resting or active behaviors. Pasture-based lactating Holstein and crossbred cows (n = 24) were observed for 12 h each by a single trained observer who recorded cow behaviors every min for 6 h/day. The study was conducted at the University of Minnesota West Central Research and Outreach Center organic dairy in Morris, Minnesota from June to September 2016. Direct visual observation was compared with CowManager sensor data during June and July 2016 (early summer; before a software system update) and during August and September 2016 (late summer; after a software system update) having each minute classified with only one of the following categories: ruminating, eating, resting or activity. Pearson correlations and concordance correlation coefficient (PROC CORR of SAS), bias correction factors (Cb), location shift (V) and scale shift (μ) (epiR package of R software) evaluated associations between sensor data and direct visual observations. Furthermore, pasture fly counts of horn, face and stable flies were used to evaluate associations with sensor data. Correlations between CowManager sensor and visual observations for all 4 behaviors were greater for late summer compared with early summer. For late summer, visual observation correlations were mostly moderate to high (0.72, P < 0.01 for ruminating; 0.88, P < 0.01 for eating; 0.65, P < 0.01 for resting; 0.20, P < 0.01 for activity) compared with sensor data. The active behavior was the most associated with and affected by pasture fly populations (0.22; P < 0.01). The results suggest the CowManager sensor may accurately monitor rumination and eating behavior of grazing dairy cattle. However, it appears that sensor accuracy may be affected by the fly pressure in grazing dairy cattle.

Key Words: precision technology, grazing, rumination