Location: Forage-animal Production ResearchTitle: Automated system for characterizing short-term feeding behavior and real-time forestomach motility in cattle
|EGERT-MCLEAN, AMANDA - University Of Kentucky|
|SAMA, MICHAEL - University Of Kentucky|
|MCLEOD, KYLE - University Of Kentucky|
|KRISTENSEN, NIELS - Seges|
|HARMON, DAVID - University Of Kentucky|
Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/30/2019
Publication Date: 10/11/2019
Citation: Egert-Mclean, A.M., Sama, M.P., Klotz, J.L., McLeod, K.R., Kristensen, N.B., Harmon, D.L. 2019. Automated system for characterizing short-term feeding behavior and real-time forestomach motility in cattle. Computers and Electronics in Agriculture. 167:105037. https://doi.org/10.1016/j.compag.2019.105037.
Interpretive Summary: Cattle exhibit differing feeding patterns throughout the feeding cycle that can influence the ruminal environment. Changes in motility of the reticulo-rumen have been associated with alterations in feed intake and feeding behavior. Particularly, rumen motility can influence passage rate of contents, and thereby, has potential to alter feed intake. Yet, the literature rarely investigates feeding behavior, ruminal motility, and ruminal pH in the same experiment. This work developed and validated a system that allowed simultaneous observation of feeding behavior and reticulo-rumen motility in cattle. This system was used to evaluate changes in feeding behavior and motility in cattle that are stepped up from a moderate to high corn-based concentrate diet, similar to what is done in a feedlot. This process can result in a lower rumen pH that can cause lower feed intake and motility. The results observed were within the range of other published studies using other established methodologies. The methodologies developed and validated in this work will benefit researchers interested in ruminant physiology and feeding behavior.
Technical Abstract: The objectives of this study were to develop instrumentation for measuring feed intake and forestomach motility for individually housed cattle and create data analysis algorithms to characterize feeding behavior and reticuloruminal contractions. Feed bunks were mounted onto S-beam load cells and suspended outside the animal stalls. Load cells were connected to a data logger which recorded bunk weight at 1-min intervals. Thus, periods of feed disappearance from the bunk could be equated to meals. A meal detection script was developed in MATLAB to import the weight data, filter the weight to reduce noise, detect meals by evaluating the difference between consecutive measurements, and export the meal start time, duration, and size of each meal. Validation of the meal detection script resulted in a combined error rate of 1.8%. A water-filled (2 L) balloon attached to a catheter was placed into the ventral sac of the rumen through the rumen cannula and connected to a disposable pressure transducer. The transducers were connected to a PowerLab data acquisition system via bridge amplifiers, and the ruminal pressure signal was visualized in real-time using LabChart computer software. A script was prepared in MATLAB for filtering pressure data, detecting contractions using the findpeaks function within the Signal Processing Toolbox of MATLAB, and evaluating contraction amplitude, duration, and frequency. Validation of the ruminal contraction script resulted in a combined error rate of 4%. After successful validation of the algorithms, an experimental application of these systems characterized meals and ruminal contractions for 8 animals in response to an increase in grain in the diet. Animals were switched from a 70% to a 90% concentrate diet. This trial produced average daily results for feeding behavior and ruminal motility that were within the range of other published studies. With the low error rate and biologically acceptable values, the instrumentation and data analysis algorithms are appropriate means of characterizing feeding behavior and ruminal motility. These systems and algorithms could have important applications for ruminant physiology and behavior research.