This observational field study examined the effect of changes in shadow contrasts on the floor and noise on balking behavior during handling. Seventy-four Bos taurus beef cattle were observed during handling at a small abattoir. Shadow contrast type (none, soft, sharp) was recorded during three stages of handling (unloading, lairage to single-file alley and into stun box). Cattle balking behavior (stop, put head down, back up) and aversive handling (electric prod, tail twist) were recorded for each shadow contrast type and the presence or absence of a noisy rendering truck. Sharp contrast shadows increased balking behavior compared to soft contrast shadows or none during unloading (X² = 12.4, P < 0.001). The noisy truck increased balking behavior during handling from the lairage holding pens to the single-file alley (P < 0.001) and during movement into the stun box (P = 0.001). Sharp contrast shadows on the floor from lighting changes and noise from the truck increased balking behavior in cattle.

Computer vision systems have emerged as a potential tool to monitor the behavior of livestock animals. Such high-throughput systems can generate massive redundant data sets for training and inference, which can lead to higher computational and economic costs. The objectives of this study were (1) to develop a computer vision system to individually monitor detailed feeding behaviors of group-housed dairy heifers, and (2) to determine the optimal frequency of image acquisition to perform inference with minimal effect on feeding behavior prediction quality. Eight Holstein heifers (96 ± 6 d old) were housed in a group and a total of 25,214 images (1 image every second) were acquired using 1 RGB camera. A total of 2,209 images were selected and each animal in the image was labeled with its respective identification (1-8). The label was annotated only on animals that were at the feed bunk (head through the feed rail). From the labeled images, 1,392 were randomly selected to train a deep learning algorithm for object detection with YOLOv3 ("You Only Look Once" version 3) and 154 images were used for validation. An independent data set (testing set = 663 out of the 2,209 images) was used to test the algorithm. The average accuracy for identifying individual animals in the testing set was 96.0%, and for each individual heifer from 1 to 8 the accuracy was 99.2, 99.6, 99.2, 99.6, 99.6, 99.2, 99.4, and 99.6%, respectively. After identifying the animals at the feed bunk, we computed the following feeding behavior parameters: number of visits (NV), mean visit duration (MVD), mean interval between visits (MIBV), and feeding time (FT) for each heifer using a data set composed by 8,883 sequential images (1 image every second) from 4 time points. The coefficient of determination (R²) was 0.39, 0.78, 0.48, and 0.99, and the root mean square error (RMSE) were 12.3 (count), 0.78, 0.63, and 0.31 min for NV, MVD, MIBV, and FT, respectively, considering 1 image every second. When we moved from 1 image per second to 1 image every 5 (MIBV) or 10 (NV, MDV, and FT) s, the R² observed were 0.55 (NV), 0.74 (MVD), 0.70 (MIBV), and 0.99 (FT); and the RMSE were 2.27 (NV, count), 0.38 min (MVD), 0.22 min (MIBV), and 0.44 min (FT). Our results indicate that computer vision systems can be used to individually identify group-housed Holstein heifers (overall accuracy = 99.4%). Based on individual identification, feeding behavior such as MVD, MIBV, and FT can be monitored with reasonable accuracy and precision. Regardless of the frequency for optimal image acquisition, our results suggested that longer time intervals of image acquisition would reduce data collecting and model inference while maintaining adequate predictive performance. However, we did not find an optimal time interval for all feeding behavior; instead, the optimal frequency of image acquisition is phenotype-specific. Overall, the best R² and RMSE for NV, MDV, and FT were achieved using 1 image every 10 s, and for MIBV it was achieved using 1 image every 5 s, and in both cases model inference and data storage could be drastically reduced.

Our objectives were to evaluate the effect of stationary brush quantity on brush use and competition in weaned dairy heifers naïve to brushes. Sixty-three Holstein heifers (95 ± 5.7 days old) were housed in groups of eight (with the exception of 1 group of 7) with two or four stationary brushes (n = 4 groups/treatment). Brush-directed behaviors of grooming, oral manipulation, and displacements were recorded continuously for all heifers 0–6, 18–24, 120–126 and 138–144 h after brush exposure. Linear mixed models were used to evaluate the effects of brush quantity and exposure duration. Total brush use and competition were not affected by brush quantity, but heifers with access to more brushes used them for longer bouts, suggesting greater opportunity for uninterrupted use. Total brush use was greater in the first and final 6 h observation periods, which was driven by the greatest duration of oral manipulation and grooming in those respective periods. The continued use of brushes by all heifers in the final period indicates the importance of providing appropriate outlets for these natural behaviors to promote animal welfare. The effect of brush quantity on bout characteristics suggests that brush use was less restricted with four compared to two brushes per eight heifers.

The purpose of this study was to investigate the effects of perioperative administration of oral meloxicam prior to and following the application of caustic paste to disbud neonatal dairy calves. Sixty-one 3–4-d-old Holstein heifer calves were randomly assigned to one of four treatment groups of 15–16 calves. The treatment groups were: 1) M1, caustic paste disbudding and oral meloxicam (45 mg) with a placebo 24 h later; 2) M2, treatment M1 followed by a second 45-mg dose of meloxicam 24 h later instead of placebo; 3) CONTROL, treatment M1 with placebo in place of meloxicam; and 4) SHAM, sham disbudding with placebo in place of meloxicam. Infrared thermography was used to quantify eye and horn bud temperatures. Pressure algometry was used to measure Mechanical nociceptive threshold (MNT) surrounding the horn bud. Average daily gain and body weight (BW) were obtained by weighing each animal throughout the study and calculating the changes over time. Plasma was collected and analyzed for cortisol and substance P concentrations. Substance P and cortisol decreased in all animals over time, regardless of treatment. Mean plasma substance P concentration across all time points was greater (P < 0.05) in the SHAM group than M1 or M2 but not different (P > 0.05) than the CONTROL group. The MNT and ocular temperatures decreased over time across all treatments (P < 0.05). Mean BW increased over time across all treatments (P < 0.05). A significant interaction (P < 0.05) between treatment and sampling time was observed at 12 h following treatment application for both mean horn bud temperature and the ratio between horn bud and ocular temperature. Overall, the results of this study suggest that meloxicam administration at a dose of 45 mg per animal may have limited influence as the primary modulator of pain and inflammatory response in calves that have been disbudded with caustic paste at 3 d of age.

Hair cortisol is a novel biomarker of chronic stress. The objective of this study was to determine the effect of hair color and length, as well as, animal age on hair cortisol concentration in beef feedlot steers. Nineteen beef crossbred steers used for nutrition research and housed in a small feedlot setting were used for this study. Seven of the steers (680 ± 4.5 kg; ~9 years of age) were fitted with ruminal fistulas and duodenal cannulas. The other 12 steers (473 ± 3.1 kg; ~2.5 years of age) were fitted with only ruminal fistulas. Hair samples from each steer were collected throughout a period of 6 weeks from six different areas and analyzed for cortisol concentrations. One pre-determined area was shaved each week for 5 weeks (Weeks 1–5). During week 6, all five, previously shaved areas and an additional area was shaved to collect hair samples of various lengths. Hair length was recorded prior to the collection of each hair sample. Only data from the last week (Week 6) of collection were included in the analyses. Steers were categorized into one of three groups: old with black hair (OB, n = 3); old with white hair (OW, n = 3); young with black hair (YB, n = 12). Older steers exhibited greater hair cortisol concentrations than younger steers (P < 0.001). Hair cortisol concentration was not impacted by duration of growth (P = 0.33). Cortisol concentrations exhibited a weak, positive correlation with hair length (r = 0.33, P-value = 0.01). The average hair growth per week of beef steers in the winter months was calculated to be 0.90 mm. Further research should be performed to improve our understanding of the effect of hair characteristics, sampling methodologies and analysis techniques on hair cortisol concentrations.

Social dynamics in group-housed animals can have important impacts on their welfare, feed efficiency, and production potential. Our objectives were to: 1) evaluate the effects of parity and social grouping on competition behavior, feeding patterns, and feed efficiency, and 2) investigate cow-level relationships between competition and feeding behavior, production, and feed efficiency. Fifty-nine Holstein cows (144.5 ± 21.8 starting DIM, mean ± SD) were housed in a freestall pen with 30 Roughage Intake Control (RIC) bins. We evaluated the effects of parity [primiparous (PR, n = 29) vs. multiparous (MU, n = 30)] and group composition at the feed bunk [same-parity (SM, n = 39) vs. mixed-parity (MX, n = 20, 50% of each parity)] with a 2 × 2 factorial design (SM-MU: n = 20; SM-PR: n = 19; MX-MU: n = 10; MX-PR: n = 10) on competition behavior, feeding patterns, and feed efficiency. Within the pen, groups of 9 to 10 cows were considered subgroups and assigned to treatments defined by sets of 5 assigned bins (2:1 stocking density). Feed bunk competition and feeding patterns were recorded via continuous video in the first hour after morning feed delivery and 24-h RIC data, respectively. Residual feed intake (RFI) was calculated as the difference between predicted and observed dry matter intake (DMI) after accounting for known energy sinks. Linear models were used to evaluate the effects and interactions of parity and group composition on competition, feeding behavior, and feed efficiency. Within-cow correlations were performed between competition, feeding behavior, and RFI. Cows in MX, compared with SM, were involved in more competitive interactions [mean (95% CI): competitive contacts: 11.5 (8.1,16.3) vs. 7.2 (5.5,9.3) events; displacements: 4.0 (3.0,5.3) vs. 2.1 (1.7,2.7) events, and replacements: 3.5 (2.6,4.7) vs. 1.9 (1.5,2.5) events]. Cows in MX vs. those in SM had more bunk visits/meal [ 4.3 (3.9, 4.8) vs. 3.7 (3.4, 3.9) visits/meal] and longer meals (31.2 vs. 27.4 ± 0.9 min/meal) and tended to have higher RFI (0.41 ± 0.3 vs. -0.21 ± 0.2) and were therefore less feed efficient. Multiparous vs. PR cows had greater DMI per day (29.3 ± 0.6 vs. 25.5 ± 0.4 kg/d) and per meal [4.2 (4.0, 4.4) vs. 3.4 (3.2, 3.6) kg/meal], faster eating rates [0.14 (0.13, 0.15) vs. 0.12 (0.11, 0.13) kg/min], and fewer bunk visits/d [26.6 (24.0, 29.4) vs. 32.8 (29.7, 35.9)]. Regardless of grouping or parity, cows with shorter latencies to first visit the bunk after feed delivery were involved in more competition and tended to be less feed efficient. Overall, individual cow- and group-level relationships among competition, feeding behavior, and feed efficiency play an important role in feed bunk social dynamics. At a competitive 2:1 stocking density, mixed-parity groups for lactating cows may have potentially negative animal welfare and feed efficiency implications that should be considered when selecting grouping strategies on the farm.