Evaluation of sound-based detection of rumination in grazing dair y cows

UTSUMI, S.; GALLI, J.; MILONE, D.H.; RUFINER, H.L.; GIOVANINI, L.L.

Otro; ASAS-ADSA Joint Annual Meeting; 2015

Individualized monitoring of rumination time (RT) could be used to guide nutritional recommendations for improved production, health and well-being of dairy cows. One commercial application is the QWES-HR Tag system (HR Tags), which uses a microphone and microprocessor in neck collars for sound-based detection of RT; registered sounds in 12 × 2 h intervals are automatically integrated for estimation of 24 h moving RT, but inaccurate detection or processing of sounds could significantly affect estimations. A study was conducted to compare the automatic detection of RT by HR Tags against observed values obtained by supervised inspection of 24-h soundtracks. The RT of 5 lactating Holstein cows on ryegrass/white clover or orchardgrass/white clover pastures was monitored for 6 non-consecutive days, using 2 sound-based methods (1) HR Tags and, (2) Acoustic Halters, which included a digital recorder and one directional microphone pressed to the animal's forehead (Control). Five halters were used with halters rotated across cows according to a completely randomized design. Cross-validation of HR Tags (24-h and 2-h periods) was conducted by inspection of the root of the mean squared prediction error (RMSPE) and concordance correlation coefficient (CCC) between methods. The HR Tags consistently underestimated RT by 18%, regardless of the period of measurement. Similarly, high RMSPE and low CCC indicated limited accuracy and low precision by HR Tags, which were slightly improved for 24 h evaluations. Further research is needed to improve the automatic sound-based detection of rumination by commercial HR Tags.