Activity and rumination of Holstein and crossbred cows in an organic grazing and low-input conventional dairy herd

Reasons for disposal and cull cow value of Holstein cows compared with Holstein, Jersey, Montbéliarde, Normande, and Viking Red crossbred cows

Cull cows from dairy farms in the United States account for 10% of the beef market; however, few studies have evaluated the effects of crossbreeding on reasons for disposal and cull value of dairy cows. The objective of the study was to compare reasons for disposal and cull cow value of Holstein and crossbred cows (n = 1,292) in an experimental dairy herd at the University of Minnesota West Central Research and Outreach Center (Morris, MN). Cows were Holstein (n = 272), 1964 genetic control Holstein (n = 161), 3-breed crossbred cows (n = 538) composed of the Montbéliarde, Viking Red, and Holstein (MVH) breeds, and 3-breed crossbred cows (n = 321) composed of the Normande, Jersey, and Viking Red (NJV) breeds. The 1964 genetic control Holstein cows originated from a design initiated at the University of Minnesota for comparison of the 1964 Holstein and contemporary Holstein cows selected for production across time. Records spanned from January 2010 to December 2023. Reasons for disposal were recorded in PCDart Herd Management Software, and cull value and body weight were obtained from receipts from livestock cull markets. For all cows, the primary reasons for disposal were as follows: reproduction (44.4%), mastitis (18%), other reasons (14.6%), death (10.3%), dairy purposes (8.4%), and low production (4.3%). Independent variables for statistical analysis of cull value were the fixed effects of body weight at time of culling, DIM at culling (0-49 DIM, 50-99 DIM, 100-149 DIM, 150-199 DIM, 200-249 DIM, 250-299 DIM, 300-350 DIM, and >350 DIM), year (2010-2023), season (spring, summer, autumn, winter), parity (1, 2, 3, 4, 5+), primary reason for culling, breed group, and sire breed group nested within breed group. Least squares means for body weight at culling was 558 kg for Holsteins, 543 kg for 1964 Holsteins, 551 kg for MVH crossbred cows, and 499 kg for NJV crossbred cows. For the analysis across time, 2014 had the highest cull value ($1,126.98), and 2020 had the lowest gross cull value ($515.21). Cows culled at greater than 300 DIM had the highest cull value and cows culled at less than 50 DIM had the lowest cull value. Cows culled during the spring and summer had higher cull value compared with cows culled during the autumn and winter. The Holstein cows ($730.04) had lower gross value compared with 1964 Holsteins ($804.38) cows and MVH ($767.39) cows. The NJV ($771.39) cows were not different from crossbreds sired by Montbéliarde, Viking Red, and Holstein bulls. Results for comparisons of breed group are from one experimental herd, so inferences to the wider dairy cow population should be undertaken with caution. In summary, dairy producers may receive greater cull value from crossbred cows compared with Holstein cows.

Validation of a methodology for characterization of rumination, lying, standing, and performing non-nutritive oral behaviors and behavioral patterns in Holstein dairy calves

Calf behavior is closely related to its early growth, production performance, and health performance. Continuous behavior recording is the most accurate but also time-consuming method used for monitoring animal behaviors, so the instantaneous sampling method is often adopted to minimize the time required to quantify behavioral observations in animal studies. Moreover, the optimal sampling intervals required to yield accurate information for estimating Holstein dairy calves' behaviors are still unknown. Our primary objective was to determine the most optimal sampling intervals for monitoring behaviors of Holstein dairy calves during preweaning and weaning periods to improve efficiency while maintaining reliability. The secondary objective was to describe their behavioral patterns. Rumination, lying, standing, and non-nutritive oral behavior (NNOB) data of 18 calves (observation time: 360 h/calf, 6,480 h in total) were continuously recorded for 15 d (3 d at 1, 3, 6, 9, and 12 wk of age). The continuous behavioral data were compared with instantaneous sampling at 5 s, 10 s, 15 s, 30 s,1 min, 3 min, 5 min, 10 min, 15 min, 30 min, and 60 min intervals. Sampling intervals were considered accurate if they met 4 criteria: coefficient of determination ≥0.90 (i.e., strongly related to true values), slope = 1, intercept = 0 (i.e., they did not over- or underestimate true values), and relative error <10%. The most optimal sampling interval was considered the highest sampling interval among the 11 sampling intervals that meet the criteria for accurate monitoring. As expected, the strength of the linear relationship between the continuous recording and instantaneous sampling decreased as the sampling intervals increased. The results varied across the different behaviors, with rumination, lying, standing, and NNOB being reliable at instantaneous recordings of 3 min, 10 min, 10 min, and 1 min for the preweaning period (1, 3, and 6 wk of age) and 10 min, 10 min, 15 min, and 3 min for the postweaning period (9 and 12 wk of age). In terms of behavioral patterns, lying time decreased, whereas rumination, standing, and NNOB time increased with age. After weaning, no significant changes in time spent performing these behaviors. Additionally, the rumination behavioral pattern becomes stable after wk 6 with decreasing after the morning feeding and occurring mainly in the morning. In conclusion, instantaneous sampling is a reliable method for monitoring the behaviors of dairy calves, but the optimal sampling intervals should be selected based on different ages and management conditions.

Precision technologies to improve dairy grazing systems

Pasture-based dairy herds continue to grow around the world as demand increases for sustainable farming practices. Grazing dairy farmers may benefit from the utilization of precision dairy technologies because these technologies have the potential to improve animal welfare, increase farm efficiency, and reduce costs. Precision dairy technologies have provided novel information about activity, rumination, and grazing behavior of various breeds in pasture-based systems. Previous research with wearable technologies has indicated that rumination, eating, and no activity have moderate to high correlations (r = 0.65 to 0.88) with visual observation; however, activity may be difficult to record in grazing herds. However, many grazing dairy farmers around the world are using activity monitors with generally positive success. Grazing is a complex behavior to define because cows may walk to an area and stop to eat or continuously walk and take bites of grass from the pasture. Wearable technologies can detect whether a cow is grazing with reasonable accuracy. However, the challenge is to determine pasture intake as bite rate and bite size because these can vary as the pasture is grazed to a low residual height. Nevertheless, grazing behavior data collected with wearable technologies was highly correlated (r = 0.92 to 0.95) with visual observations. Grazing is a behavior that should continue to be explored, especially with precision dairy technologies. As healthy and productive pastures are integral to grazing systems, accurate forage biomass measurements can improve efficiency and production of pastured dairy cows. However, few farms use technology to determine forage availability. Therefore, using dairy technologies to monitor forage dry matter from pasture may provide a potential benefit for grazing-based dairy farms. Current satellite technology with the normalized difference vegetation index and electronic rising plate meters may provide new technologies for farms to monitor forage biomass and fine-tune grazing within pastures. In the future, pasture-based dairy farms may rely on virtual fencing, drones to detect animal health issues and forage availability, and autonomous vehicles to move cattle and to detect weeds on pasture.

Health Treatment Cost of Holsteins in Eight High-Performance Herds

Health treatments of Holstein cows (n = 2214) were recorded by the owners of eight high-performance dairy herds in Minnesota. Cows calved from March 2008 to October 2015, and 14 types of health treatments were uniformly defined across the herds. Specific types of health treatment were subsequently assigned a cost based on the mean veterinary cost obtained from the veterinary clinics that serviced the eight herds. A fixed labor cost for time (USD 18/h) associated with specific types of health treatment was determined based on interviews with the herd owners and was added to the veterinary cost. Health treatment cost was then partitioned into five health categories: mastitis (including mastitis diagnostic test), reproduction (cystic ovary, retained placenta, and metritis), lameness (hoof treatments), metabolic (milk fever, displaced abomasum, ketosis, and digestive), and miscellaneous (respiratory, injury, and other). Lactations of cows were divided into six intervals that corresponded with stage of lactation based on days in milk. The first interval of lactation was 30 days in length, followed by four intervals of 60 days each, and the final interval started on day 271 and had variable length because it continued to the end of lactation and included the dry period. Health treatment cost was summed within each interval of lactation and subsequently across lactations by parity. Statistical analysis by parity included the fixed effects of herd, interval, and the interaction of herd and interval, with interval regarded as a repeated measure of cows. Health treatment cost was highest during the first interval for all five parities of cows and ranged from USD 22.87 for first parity to USD 38.50 for fifth parity. Reproduction treatment cost was about one-half of the total health treatment cost during the first interval in all five parities. Metabolic treatment cost during the first interval ranged from USD 3.92 (in first parity) to USD 12.34 (in third parity). Compared to the other health categories, mastitis treatment cost was most evenly distributed across intervals of lactation in all parities. Lameness treatment cost was highest during mid- or late-lactation across parities and reflected the time when cows received routine hoof trimming. Additionally, treatment cost across health categories was summed across intervals of lactation for each cow, and the total health cost of cows varied substantially from herd to herd and ranged from USD 23.38 to USD 74.60 for first parity and usually increased with parity.

The impact of using different ancestral reference populations in assessing crossbred population admixture and influence on performance

Crossbreeding is a process in which animals from different breeds are mated together. The animals produced will exhibit a combination of both additive and non-additive genetic improvement from parental breeds that increase heterozygosity and negate inbreeding depression. However, crossbreeding may also break up the unique and often beneficial gene combinations in parental breeds, possibly reducing performance potential as the benefits of heterosis depends on the type of crossbreeding systems used and heritability of the traits. This effect of crossbreeding, especially on the genome architecture, is still poorly understood with respect to 3-breed crossbreeding systems. Thus, this study examined variation in genomic ancestry estimations relative to pedigree-based estimations and correlated breed composition to key production and health traits. Two rotational crossbred populations, referenced as ProCROSS and Grazecross were assessed and totaled 607 crossbred cattle. ProCROSS is a product of rotational crossbreeding of Viking Red (VKR), Holstein (HOL), and Montbeliarde (MON). In contrast, Grazecross consists of Viking Red (VKR), Normande (NOR), and Jersey (JER). Both breeding programs were aimed at capitalizing on the positive effect of heterosis. The VKR is a marketing term for Swedish Red, Danish Red, and Finnish Ayrshire breed which complicated breed determination. Therefore, genomic breed composition estimates were compared using two different representations of VKR, one of which was based on parents used in the crossing system and a second based on genotypes from the ancestral breeds that comprise VKR. Variation of breed composition estimates were assessed between pedigree and genome-based predictions. Lastly, Genomic estimations were correlated with production and health traits by comparing extreme performance groups to identify the relationship between breed ancestry and performance. With the exception of the JER breed composition in Grazecross, all other estimates of the purebred contribution to the ProCROSS and Grazecross showed a significant difference in their genomic breed estimation when using the VKR ancestral versus the VKR parental reference populations for admixture analysis. These observations were expected given the different relationship of each VKR representation to the crossbred cattle. Further analysis showed that regardless of which VKR reference population was used, the degree of MON and HOL breed composition plays a significant role in milk and fat production in ProCROSS, while the degree of VKR and NOR ancestry were related to improved health performance in Grazecross. In all, identifying the most appropriate and informative animals to use as reference animals in admixture analysis is an important factor when interpreting results of relationship and population structure, but some degree of uncertainty exists when assessing the relationship of breed composition to phenotypic performance.

Using rumination time to manage health and reproduction in dairy cattle: a review

Early detection of disease is the key to successful management of the dairy cattle which leads to timely treatment and prevention of costs associated with prolonged treatment and reduced milk yield. Electronic systems that allow for monitoring of physiological parameters like rumination, are now commercially available. This review paper discusses different aspects of rumination time that could be used to monitor the health and reproduction of dairy cattle. This review paper explored different areas where rumination time could be utilized in monitoring dairy cattle at calving, during the estrus period, during heat stressed conditions, and to detect diseases and transition cow disorders. In conclusion, rumination time could be used as an indicator of the health status in dairy cattle.

Evaluation of the RumiWatch system as a benchmark to monitor feeding and locomotion behaviors of grazing dairy cows

Direct visual observation is a common method for validation of animal behavior technologies; however, visual observations are time consuming and subject to human error. The objective of this study was to evaluate the RumiWatch system (Itin and Hoch GmbH, Liestal, Switzerland), which is composed of a noseband sensor and a pedometer, for monitoring feeding and locomotion behaviors of grazing dairy cows, to determine its accuracy for use as a benchmark in validation studies. The study was conducted at the University of Minnesota West Central Research and Outreach Center in Morris, Minnesota, from May to June 2018. Two experiments were conducted and validated: (1) feeding and locomotion behaviors and (2) rumination cycle and grazing bites. Lactating crossbred dairy cows (n = 12) were offered pasture for 22 h/d, and cows were milked twice daily. Visual observations were recorded by 3 observers with the Pocket Observer app (Noldus Information Technology, Leesburg, VA). The first experiment determined agreement for visual observations and the RumiWatch noseband sensor and pedometer from 144 h of feeding and locomotion behaviors. The second experiment determined agreement for visual observations and the RumiWatch noseband sensor from 17.75 h of rumination cycle and grazing bites. Pearson correlations evaluated associations for visual observations, and the RumiWatch noseband sensor and pedometer and were 0.84 for rumination, 0.76 for grazing, 0.39 for drinking, 0.57 for other activities, 0.83 for standing, 0.91 for lying, and 0.38 for walking. Correlations for visual observations and rumination cycle and grazing bites were -0.13 and 0.47, respectively. The RumiWatch system evaluated rumination, grazing, standing, and lying behaviors with high precision and accuracy, and the RumiWatch system may be used as a benchmark instead of visual observation to validate animal behavior technologies.

Estrous detection with an activity and rumination monitoring system in an organic grazing and a low-input conventional dairy herd

The objective of this study was to evaluate estrous detection using a physical activity and rumination monitoring system in a seasonal calving organic grazing (GRAZ) and a low-input conventional (ZEROGRAZ) dairy herd. The study was conducted from June 2014 to August 2017. During each breeding season, physical activity and rumination were monitored electronically using an activity and rumination monitoring system (HR-LD tags; SCR Engineers Ltd., Netanya, Israel). Signals resulting from the activity and rumination monitoring system for individual cows were used to determine consistency of the values using this system with the breeding date of cows. Breeding dates were determined using Estrotect^TM patches. The study included 1,463 breeding dates from 531 cows. Within the GRAZ herd, during the summer breeding season the monitoring system was less sensitive for estrous detection (33.8 %) than during the winter breeding season (79.8 %).The activity and rumination monitoring system had a sensitivity of 56.7 %, specificity of 99.3 % and positive predictive value of 59.8 % for the GRAZ herd, and sensitivity of 70.1 %, specificity of 99.2 % and positive predictive value of 66.3 % for the ZEROGRAZ herd. For cows that were determined to be pregnant and subsequently calved as a result of the mating, the sensitivity for estrous detection was slightly greater for the GRAZ (60.7 %) and ZEROGRAZ (72.5 %) herds. The activity and rumination monitoring system evaluated in this study has potential for estrous detection in grazing herds during the winter breeding season and in small-input dairy herds during both, winter and summer breeding seasons.