Comparison of feeding behavior between black and red Angus feeder heifers

The objective of this study was to compare feeding behavior between red and black Angus heifers during a 161-d finishing period as a potential explanation for performance differences. Sixty-eight single-sourced purebred red (n = 35) and black (n = 33) Angus heifers, leptin genotype TT, and average starting weight 360 kg (±19 kg) were used. Heifers were randomly and equally allocated into one of two feedlot pens, equipped with five feed bunks that recorded feeding behavior. Individual time spent at the feed bunk, interval between feeding events, feed intake, and meal frequency were recorded daily, and eating rate was calculated. Heifers were fed a barley-based diet (>75% concentrate). After 161 d, at the end of the feeding period, feedlot performance was calculated as average daily gain (ADG) and gain to feed conversion rate. Additionally, carcass data were obtained from the abattoir. Overall, black Angus heifers ate more, spent more time at the feed bunk, and had more meals compared with red Angus (P < 0.001). Red Angus heifers had better gain to feed ratios (P < 0.02) and significantly more red heifers were assigned to Canadian yield category 1 (≥59% lean meat) compared with black heifers (P = 0.02), whereas black heifers had higher back fat thickness throughout the study (P ≤ 0.04). All other performance parameters (ADG and carcass weight) were not different.

Technical note: Evaluation of a system for monitoring individual feeding behavior and activity in beef cattle

Behavioral observations are important to detect illness in beef cattle. However, traditional observation techniques are time and labor intensive and may be subjective. The objective was to validate a system for monitoring individual feeding behavior and activity in beef cattle (Fedometer [FEDO]; ENGS, Rosh Pina, Israel). Sixteen steers (initial BW ± SD = 326 ± 46 kg) were fitted with data loggers (FEDO) on their left front leg and housed in a pen with a feedbunk equipped with an antenna emitting an electromagnetic field that reached 30 ± 2 cm in front of the feedbunk. Feedbunk attendance (duration of visit and frequency of meals) measured by FEDO was compared with live observations (27 observational periods lasting between 72 and 240 min; mean 126 min). Lying time and frequency of lying bouts were compared with previously validated accelerometers fitted to the hind leg (10 steers equipped for 10 to 12 d; HOBO Pendant G Acceleration Data Logger [HOBO]; Onset Computer Corporation, Pocasset, MA). Step counts were compared with video recordings (15 observations for 6-min intervals in 6 steers). Concordance correlation coefficients (CCC), accounting for repeated measures, and limits of agreement were computed. Comparison between FEDO and observed time at the feedbunk yielded a CCC of 0.98 (95% confidence interval [CI] 0.97-0.99). All 68 meal events observed were recorded by FEDO. However, FEDO recorded 4 meal events during the 27 observational periods that were not observed. Lying time measured by HOBO and FEDO were highly correlated (CCC = 0.98; 95% CI 0.97-0.99). However, frequency of lying bouts measured by FEDO was only moderately correlated to HOBO (CCC = 0.71; 95% CI 0.63-0.77); FEDO underestimating the number of lying bouts (on average, 0.4 fewer bouts per 6 h). Step count by FEDO was moderately correlated to video observations (CCC = 0.75; 95% CI 0.49-0.89); FEDO overestimating the number of steps (on average, 5 more steps per 6 min). In conclusion, the FEDO system accurately measured duration of feedbunk attendance, frequency of meals, and lying time. However, it overestimated the number of steps and underestimated the frequency of lying bouts.

Feeding behavior as an early predictor of bovine respiratory disease in North American feedlot systems

Bovine respiratory disease (BRD), which can cause substantial losses for feedlot operations, is often difficult to detect based solely on visual observations. The objectives of the current study were to determine a BRD case identification based on clinical and laboratory parameters and assess the value of feeding behavior for early detection of BRD. Auction-derived, mixed-breed beef steers (n = 213) with an average arrival weight of 294 kg were placed at a southern Alberta commercial feedlot equipped with an automated feed bunk monitoring system. Feeding behavior was recorded continuously (1-s intervals) for 5 wk after arrival and summarized into meals. Meals were defined as feeding events that were interrupted by less than 300 s nonfeeding. Meal intake (g) and meal time (min) were further summarized into daily mean, minimum, maximum, and sum and, together with frequency of meals per day, were fit into a discrete survival time analysis with a conditional log-log link. Feedlot staff visually evaluated (pen-checked) health status twice daily. Within 35 d after arrival, 76% (n = 165) of the steers had 1 or more clinical signs of BRD (reluctance to move, crusted nose, nasal or ocular discharge, drooped ears or head, and gaunt appearance). Whereas 41 blood samples could not be processed due to immediate freezing, for 124 of these steers, complete and differential blood cell count, total serum protein, plasma fibrinogen, serum concentration of haptoglobin (HP), and serum amyloid A (SAA) were determined. The disease definition for BRD was a rectal temperature ≥ 40.0°C, at least 2 clinical signs of BRD, and HP > 0.15 mg/mL. It was noteworthy that 94% of the 124 steers identified by the feedlot staff with clinical signs of BRD had HP > 0.15 mg/mL. An increase in mean meal intake, frequency, and mean inter-meal interval was associated with a decreased hazard for developing BRD 7 d before visual identification (P < 0.001). Furthermore, increased mean mealtime, frequency, and mean inter-meal interval were associated with a decreased BRD hazard up to 7 d before feedlot staff noticed clinical symptoms (P < 0.001). In conclusion, mean intake per meal as well as mean meal time and frequency of meals could be used to predict the hazard of BRD in feedlot cattle 7 d before visual detection and could be considered in commercial feedlot settings once a predictive algorithm has been developed.