Crowd sourcing remote comparative lameness assessments for dairy cattle.

Lameness assessments are rarely conducted routinely on dairy farms and when completed typically underestimate lameness prevalence, hampering early diagnosis and treatment. A well-known feature of many perceptual tasks is that relative assessments are more accurate than absolute assessments, suggesting that creating methods that allow for the relative scoring of which cow is more lame will allow for reliable lameness assessments. Here we developed and tested a remote comparative lameness assessment method: we recruited nonexperienced crowd workers via an online platform and asked them to watch 2 videos side-by-side, each showing a cow walking, and to identify which cow was more lame and by how much (on a scale of -3 to 3). We created 11 tasks, each with 10 video pairs for comparison, and recruited 50 workers per task. All tasks were also completed by 5 experienced cattle lameness assessors. We evaluated data filtering and clustering methods based on worker responses and determined the agreement among workers, among experienced assessors, and between these groups. A moderate to high interobserver reliability was observed (intraclass correlation coefficient, ICC = 0.46 to 0.77) for crowd workers and agreement was high among the experienced assessors (ICC = 0.87). Average crowd-worker responses showed excellent agreement with the average of experienced assessor responses (ICC = 0.89 to 0.91), regardless of data processing method. To investigate if we could use fewer workers per task while still retaining high agreement with experienced assessors, we randomly subsampled 2 to 43 (1 less than the minimum number of workers retained per task after data cleaning) workers from each task. The agreement with experienced assessors increased substantially as we increased the number of workers from 2 to 10, but little increase was observed after 10 or more workers were used (ICC > 0.80). The proposed method provides a fast and cost-effective way to assess lameness in commercial herds. In addition, this method allows for large-scale data collection useful for training computer vision algorithms that could be used to automate lameness assessments on farm.

AI Based Digital Twin Model for Cattle Caring.

In this paper, we develop innovative digital twins of cattle status that are powered by artificial intelligence (AI). The work is built on a farm IoT system that remotely monitors and tracks the state of cattle. A digital twin model of cattle based on Deep Learning (DL) is generated using the sensor data acquired from the farm IoT system. The physiological cycle of cattle can be monitored in real time, and the state of the next physiological cycle of cattle can be anticipated using this model. The basis of this work is the vast amount of data that is required to validate the legitimacy of the digital twins model. In terms of behavioural state, this digital twin model has high accuracy, and the loss error of training reach about 0.580 and the loss error of predicting the next behaviour state of cattle is about 5.197 after optimization. The digital twins model developed in this work can be used to forecast the cattle's future time budget.

Vocal production in postpartum dairy cows: Temporal organization and association with maternal and stress behaviors.

Mammalian vocalizations can encode contextual information in both the spectrographic components of their individual vocal units and in their temporal organization. Here we observed 23 Holstein-Friesian dairy cows immediately after birth during interactions with their calf and when their calf was separated to the other side of a fence line. We investigated whether the vocalizations emitted in these postpartum contexts would vary temporally. We also described the maternal and stress behaviors preceding and following postpartum vocal production using kinematic diagrams and characterized call sequence structure. The kinematic diagrams highlight the disruption of maternal responses caused by calf separation and show that behavioral and vocal patterns varied according to the cows' emotional states and proximity to the calf in both contexts. During calf interactions, cows mainly produced closed-mouth calls simultaneous to licking their calf, whereas an escalation of stress responses was observed during calf separation, with the cows approaching the fence line, becoming alert to the calf, and emitting more mixed and open-mouth calls. Call sequences were similarly structured across contexts, mostly containing repetitions of a single call type, with a mean interval of 0.57 s between calls and a greater cumulative vocalization duration, attributed to an increased number of vocal units per sequence. Overall, calf separation was associated with a greater proportion of calls emitted as a sequence (inverse of single isolated calls), a shorter interval between separate call sequences, and a greater number of vocal units per sequence, compared with calf interactions. These temporal vocal features varied predictably with the high stress expression from cows during calf separation and may represent temporal modulations of emotional expression. Despite the noisy farm soundscape, empirical call type and temporal vocal features were easy to measure; thus, findings could be applied to future cattle studies wishing to analyze vocalizations for on-farm welfare assessments.

Short-term liveweight changes of dairy cows measured by stationary and walk-over weighing scales.

Monitoring and detecting individual cows' liveweight (LW) and liveweight change (LWC) are important for estimation of nutritional requirements and health management, and could be useful to measure short-term feed intake, water consumption, defecation, and urination. Walk-over weighing (WOW) systems can facilitate measurements of LW for these purposes, providing automated LW recorded at different times of the day. We conducted a field study to (1) quantify the contribution of feed and water intake, as well as urine and feces excretions, to short-term LWC and (2) determine the feasibility of stationary and WOW scales to detect subtle changes in LW as a result of feed and water intake, urination, and defecation. In this experiment, 10 cows walked through a WOW system and then stood individually on a stationary scale collecting weights at 10 and 3.3 Hz, respectively. Cows were offered 4 kg of feed and 10 kg of water on the stationary scale. For each animal, LW before and after eating and drinking was then calculated using different approaches. Liveweight change was calculated as the difference between the initial and final LW before and after eating and drinking for each statistical measure. The weights of feed intake, water consumption, urination, and defecation were measured and used as predictors of LWC. Urine and feces were collected from individual cows while the cow was on the scale, using a container, and weighed separately. The agreement between LWC measured using either stationary or WOW scales was assessed to determine the sensitivity of the scales to detect subtle changes in LW using the coefficient of determination (R2), Lin's concordance correlation coefficient (CCC), and mean bias. The prediction model showed that most of the regression coefficients were not significantly different from +1.0 for feed and water, or -1.0 for urine and feces. The R2 and CCC values demonstrated a satisfactory agreement between calculated and stationary LWC and values ranged from 0.60 to 0.92 and 0.71 to 0.94, respectively. A moderate agreement was achieved between calculated and automated LWC with R2 and Lin's CCC values of 0.45 to 0.63 and 0.60 to 0.74, respectively. Therefore, results demonstrated that new algorithms and data processing methods need to be continuously explored and improved to obtain accurate measurements of LW to measure changes in LW, especially from WOW scales.

Functional brain networks involved in lexical decision.

Functional magnetic resonance imaging (fMRI)5 studies on lexical decision (LD)6 attempting to isolate the brain network underlying access to lexical representations can be confounded by attentional and response processes. However, manipulating the "wordlikeness" of the LD stimuli can facilitate functional interpretation of each emerging brain network, providing principles for separation of attentional demand from linguistic processing. This is because activation of difficult-to-access lexical representations (for obscure real words), and avoidance of interfering word properties (for wordlike non-words), are both generally attentionally demanding. Therefore, congruent patterns of activation would be predicted for general-attention-responsive networks, but opposing patterns for language-responsive networks. 59 healthy adults performed a LD task, and multidimensional functional connectivity analysis was used to extract three functional brain networks. A linguistic processing network (LPN) was separated from attention/response networks anatomically (LPN included Broca's and Wernicke's areas), but also temporally by showing reduced activation for the most attentionally demanding condition (i.e., wordlike non-words). This demonstrated that during LD in fMRI a network involved in linguistic processing can be disentangled from attention- and response-specific networks, using a combination of experimental design and multidimensional analysis methods.

Protective Effects of Exercise on Cognition and Brain Health in Older Adults.

Accelerated trajectories of cognitive decline in older adults may increase the risk of developing Alzheimer disease and related dementias (ADRD). Physical activity has potential modifying effects on these changes that could prevent or delay ADRD. This review explores the hypothesis that multiple, mutually complimentary, and interacting factors explain the positive association between exercise and the optimization of cognition in older adults.

Short communication: The effect of temperature-humidity index on milk yield and milking frequency of dairy cows in pasture-based automatic milking systems.

Hot weather is known to negatively affect cow performance primarily through reduced feed intake and milk yield. However, little information is available on how it affects cow milk yield and milking frequency in automatic milking systems (AMS). Milking data were collected from 6 pasture-based AMS farms in Australia to assess the effect of temperature-humidity index (THI) on milk yield and milking frequency. Daily measures of average milk yield per cow and average milking frequency per cow during December to February (Australian summer) were assessed for associations with maximum, minimum, and average THI from d 0, -1, -2, and -3 in relation to the milking data. Average daily milk yield per cow was negatively associated with an increasing maximum, minimum, and average THI (-0.11, -0.08, and -0.15 kg/THI unit increase, respectively) on the collection day and up to 3 d prior. The average daily milking frequency was negatively associated with maximum THI on 1 d (-0.003/THI unit increase) and 2 d (-0.003/THI unit increase) before collection. Our results show that high THI conditions were negatively associated with milking frequency and milk yield in a pasture-based AMS and that research into management and infrastructure (cow cooling) in these systems is warranted to reduce production losses.

Average Temperature as a Marker of Lymphoma-Associated HLH.

METHODS: This retrospective analysis aimed to assess whether a 12-hour mean temperature (measured around either diagnosis of HLH or peak ferritin value) has value as a quick and simple diagnostic test for HLH in people with lymphoproliferative disease (LPD). Hospital records from 2018 to 2022 were retrospectively screened for patients with LPD and peak ferritin during admission to hospital >3000ng/mL. Patients were grouped as either HLH or non-HLH after consensus discussion at a multi-disciplinary meeting with access to full, detailed patient records and H-scores. RESULTS: The total cohort of 23 patients consisted of 12 with HLH and 11 grouped as non-HLH. 12-hour mean temperature at HLH diagnosis was 38.6 °C in the HLH cohort and 37.5 °C measured at the point of peak ferritin measurement in non-HLH groups. It was also positively correlated with HLH status (P = 0.001) and showed high retrospective sensitivity and specificity for HLH above 37.7 °C. CONCLUSION: These results demonstrate that a 12-hour mean temperature may add value and diagnostic certainty to the first-line investigations for HLH associated with LPD. The moderately high sensitivity and specificity achieved with this dataset supports the need for further research into whether the test retains validity in larger patient groups.

The Impact of Abrupt and Fenceline-Weaning Methods on Cattle Stress Response, Live Weight Gain, and Behaviour.

The impact of abrupt (AB) and fenceline (FL) weaning methods on cattle stress response, live weight gain, and behaviour were determined across 14 days. Thirty-two cow-calf pairs were fitted with ear tag sensors (to continuously record behaviour) and allocated to two weaning treatments. After separation, FL calves were maintained in a pen adjacent to the FL cow paddock. The AB calves were transported to a pen removing all contact with the cows. After 7 d, FL cows were transported away from all calf pens. Body weights and salivary samples were collected for all animals on experimental days 0, 7, and 14. Fenceline-weaned calves had a greater duration of rest and rumination with reduced high activity across the first 3 days after separation as compared to abruptly weaned calves in line with the greater occurrences of pacing observed for AB calves. Fenceline-separated cows had greater levels of rest across the first 7 days but similar levels of rumination compared to abruptly separated cows. Fenceline-separated cow activity levels tended to be greater and eating levels were similar across the first three days. Body weight (BW) and cortisol concentrations were similar for AB and FL cattle, but FL cows had lower overall weight gain than the abrupt cows likely due to reduced eating time on days four to seven. Together, these results suggest that calves be fenceline-weaned for three days followed by total separation.

Ruminant Production from Napier Grass (Pennisetum purpureum Schum): A Review.

Napier grass (Pennisetum purpureum Schumach) supports a significant proportion of animal production in subtropical and tropical regions, but its quality is low and when offered alone, results in low ruminant production. Shifting the management of Napier grass towards a higher-quality feed increased milk yield and liveweight gain for small, mature cattle without supplementation. This review highlights the opportunity for further increases in milk and meat production for differing classes of livestock in the tropics and subtropics by improving the nutritive value of Napier grass using new best management practice flowing on to improve food security for the millions of people in these regions.

Behavioral responses to cow and calf separation: separation at 1 and 100 days after birth.

OBJECTIVE: The aim was to compare the behavioral response to full separation of cows and calves maintained together for 100 days or 24 h. METHODS: Twelve Holstein-Friesian cow-calf pairs were enrolled into either treatment or industry groups (n = 6 cow-calf pairs/group). The treatment cows and calves were maintained on pasture together for 106±8.6 d and temporarily separated twice a day for milking. The Industry cows and their calves, were separated within 24 h postpartum. Triaxial accelerometer neck-mounted sensors were fitted to cows 3 weeks before separation to measure hourly rumination and activity. Before separation, cow and calf behavior was observed by scan sampling for 15 min. During the separation process, frequency of vocalizations and turn arounds were recorded. At separation, cows were moved to an observation pen where behavior was recorded for 3 d. A CCTV camera was used to record video footage of cows within the observation pens and behavior was documented from the videos in 15 min intervals across the 3 d. RESULTS: Before separation, industry calves were more likely to be near their mother than Treatment calves. During the separation process, vocalization and turn around behavior was similar between groups. After full separation, treatment cows vocalized three times more than industry cows. However, the frequency of time spent close to barrier, standing, lying, walking, and eating were similar between industry and treatment cows. Treatment cows had greater rumination duration, and were more active, than industry cows. CONCLUSION: These findings suggest a similar behavioral response to full calf separation and greater occurrence of vocalizations, from cows maintained in a long-term, pasture-based, cow-calf rearing system when compared to cows separated within 24 h. However, further work is required to assess the impact of full separation on calf behavior.

Dairy cow and calf behavior and productivity when maintained together on a pasture-based system.

OBJECTIVE: We determined the impact of maintaining pasture-based dairy cows and calves together over 100 days on cow milk production, cow and calf behavior, and calf liveweight and carcass quality. METHODS: Six Holstein-Friesian cows and their male calves were monitored for 106±8.6 days. Cows were temporarily separated twice a day for milking with calves remaining in the paddock. Cow and calf behaviors were recorded via scan sampling at 6 different timepoints, for the first 7 days and twice a week thereafter. Calves were weighed weekly and immediately processed for meat quality and rumen development analysis at 106±8.6 days. Daily cow milk yields were collected from enrollment until 109±8.6 days (3 days post-weaning). RESULTS: The average daily gain of calves was 1.4±0.73 kg/d, with an average carcass dressing percentage of 59%. Calves had the greatest frequency of observed close proximity to cow and suckling in the first two weeks and decreased with experiment duration. During separation for milking, cow vocalizations and attempts to return to their calf decreased over time. Reticulorumen weight was on target for calf age, but as a proportion of total stomach weight was lower than industry averages of calves the same age due to the larger abomasum. Cows produced an average of 12±7.6 kg of milk yield per day over the 3-days before the calves were weaned and increased to mean of 31±8.3 kg/d the 3 days after weaning, indicating a consumption of close to 20 kg per calf per day. CONCLUSION: The impact of a pasture-based cow-calf rearing system on cow and calf behavior and the potential for high levels of calf liveweight gain when provided ad-libitum milk and feed were determined. Further research is required to determine the practicality of replicating such systems with large herds and impact on reared calves post-weaning.

Napier grass (Pennisetum purpureum Schum) management strategies for dairy and meat production in the tropics and subtropics: yield and nutritive value.

Napier grass (Pennisetum purpureum Schumach) comprises up to 80% of the cattle diet in many tropical and subtropical regions and is used primarily by smallholder farmers. Despite the grass's high yield, resulting animal productivity from this grass is low. One of the key reasons for the low animal productivity of Napier grass is its low nutritive value under current management. Taken together, previous work has shown the current yield, crude protein (CP), and metabolisable energy (ME) of Napier grass to be 26 t dry matter (DM)/ha/year, 96 g/kg DM, and 8.7 MJ/kg DM, respectively, ranging from 2 to 86 t DM/ha/year, 9 to 257 g CP/kg DM, and 5.9 to 10.8 MJ ME/kg DM, respectively, suggesting an opportunity for significant improvement on both yield and nutritive value of this grass. The DM yield and nutritive value of this grass are inversely related, indicating a trade-off between yield and quality; however, this trade-off could be minimised by increasing sowing density and harvesting frequency. Available literature shows that this simple management strategy of increasing sowing density (50 cm × 40 cm) and harvesting frequency (11-12 harvests/year) provides 71 t DM/ha with 135 g/kg DM CP and 10.8 MJ ME/kg DM. This quality of Napier grass has the potential to increase both milk and meat production substantially in the tropics and subtropics, and the farmers will likely find this simple management acceptable due to the high yield obtained through this management. However, there is a paucity of work in this field. Therefore, management strategies to improve the nutritive value of Napier grass are required to increase milk and meat production in the tropics and subtropics and in doing so improve the food security of more than half of the global population living in these regions.

Field and in-silico analysis of harvest index variability in maize silage.

Maize silage is a key component of feed rations in dairy systems due to its high forage and grain yield, water use efficiency, and energy content. However, maize silage nutritive value can be compromised by in-season changes during crop development due to changes in plant partitioning between grain and other biomass fractions. The partitioning to grain (harvest index, HI) is affected by the interactions between genotype (G) × environment (E) × management (M). Thus, modelling tools could assist in accurately predicting changes during the in-season crop partitioning and composition and, from these, the HI of maize silage. Our objectives were to (i) identify the main drivers of grain yield and HI variability, (ii) calibrate the Agricultural Production Systems Simulator (APSIM) to estimate crop growth, development, and plant partitioning using detailed experimental field data, and (iii) explore the main sources of HI variance in a wide range of G × E × M combinations. Nitrogen (N) rates, sowing date, harvest date, plant density, irrigation rates, and genotype data were used from four field experiments to assess the main drivers of HI variability and to calibrate the maize crop module in APSIM. Then, the model was run for a complete range of G × E × M combinations across 50 years. Experimental data demonstrated that the main drivers of observed HI variability were genotype and water status. The model accurately simulated phenology [leaf number and canopy green cover; Concordance Correlation Coefficient (CCC)=0.79-0.97, and Root Mean Square Percentage Error (RMSPE)=13%] and crop growth (total aboveground biomass, grain + cob, leaf, and stover weight; CCC=0.86-0.94 and RMSPE=23-39%). In addition, for HI, CCC was high (0.78) with an RMSPE of 12%. The long-term scenario analysis exercise showed that genotype and N rate contributed to 44% and 36% of the HI variance. Our study demonstrated that APSIM is a suitable tool to estimate maize HI as one potential proxy of silage quality. The calibrated APSIM model can now be used to compare the inter-annual variability of HI for maize forage crops based on G × E × M interactions. Therefore, the model provides new knowledge to (potentially) improve maize silage nutritive value and aid genotype selection and harvest timing decision-making.

One-Shot Learning with Pseudo-Labeling for Cattle Video Segmentation in Smart Livestock Farming.

Computer vision-based technologies play a key role in precision livestock farming, and video-based analysis approaches have been advocated as useful tools for automatic animal monitoring, behavior analysis, and efficient welfare measurement management. Accurately and efficiently segmenting animals' contours from their backgrounds is a prerequisite for vision-based technologies. Deep learning-based segmentation methods have shown good performance through training models on a large amount of pixel-labeled images. However, it is challenging and time-consuming to label animal images due to their irregular contours and changing postures. In order to reduce the reliance on the number of labeled images, one-shot learning with a pseudo-labeling approach is proposed using only one labeled image frame to segment animals in videos. The proposed approach is mainly comprised of an Xception-based Fully Convolutional Neural Network (Xception-FCN) module and a pseudo-labeling (PL) module. Xception-FCN utilizes depth-wise separable convolutions to learn different-level visual features and localize dense prediction based on the one single labeled frame. Then, PL leverages the segmentation results of the Xception-FCN model to fine-tune the model, leading to performance boosts in cattle video segmentation. Systematic experiments were conducted on a challenging feedlot cattle video dataset acquired by the authors, and the proposed approach achieved a mean intersection-over-union score of 88.7% and a contour accuracy of 80.8%, outperforming state-of-the-art methods (OSVOS and OSMN). Our proposed one-shot learning approach could serve as an enabling component for livestock farming-related segmentation and detection applications.

Intelligent Perception-Based Cattle Lameness Detection and Behaviour Recognition: A Review.

The growing world population has increased the demand for animal-sourced protein. However, animal farming productivity is faced with challenges from traditional farming practices, socioeconomic status, and climate change. In recent years, smart sensors, big data, and deep learning have been applied to animal welfare measurement and livestock farming applications, including behaviour recognition and health monitoring. In order to facilitate research in this area, this review summarises and analyses some main techniques used in smart livestock farming, focusing on those related to cattle lameness detection and behaviour recognition. In this study, more than 100 relevant papers on cattle lameness detection and behaviour recognition have been evaluated and discussed. Based on a review and a comparison of recent technologies and methods, we anticipate that intelligent perception for cattle behaviour and welfare monitoring will develop towards standardisation, a larger scale, and intelligence, combined with Internet of things (IoT) and deep learning technologies. In addition, the key challenges and opportunities of future research are also highlighted and discussed.

The Brain in Motion II Study: study protocol for a randomized controlled trial of an aerobic exercise intervention for older adults at increased risk of dementia.

BACKGROUND: There remains no effective intervention capable of reversing most cases of dementia. Current research is focused on prevention by addressing risk factors that are shared between cardiovascular disease and dementia (e.g., hypertension) before the cognitive, functional, and behavioural symptoms of dementia manifest. A promising preventive treatment is exercise. This study describes the methods of a randomized controlled trial (RCT) that assesses the effects of aerobic exercise and behavioural support interventions in older adults at increased risk of dementia due to genetic and/or cardiovascular risk factors. The specific aims are to determine the effect of aerobic exercise on cognitive performance, explore the biological mechanisms that influence cognitive performance after exercise training, and determine if changes in cerebrovascular physiology and function persist 1 year after a 6-month aerobic exercise intervention followed by a 1-year behavioural support programme (at 18 months). METHODS: We will recruit 264 participants (aged 50-80 years) at elevated risk of dementia. Participants will be randomly allocated into one of four treatment arms: (1) aerobic exercise and health behaviour support, (2) aerobic exercise and no health behaviour support, (3) stretching-toning and health behaviour support, and (4) stretching-toning and no health behaviour support. The aerobic exercise intervention will consist of three supervised walking/jogging sessions per week for 6 months, whereas the stretching-toning control intervention will consist of three supervised stretching-toning sessions per week also for 6 months. Following the exercise interventions, participants will receive either 1 year of ongoing telephone behavioural support or no telephone support. The primary aim is to determine the independent effect of aerobic exercise on a cognitive composite score in participants allocated to this intervention compared to participants allocated to the stretching-toning group. The secondary aims are to examine the effects of aerobic exercise on a number of secondary outcomes and determine whether aerobic exercise-related changes persist after a 1-year behavioural support programme (at 18 months). DISCUSSION: This study will address knowledge gaps regarding the underlying mechanisms of the pro-cognitive effects of exercise by examining the potential mediating factors, including cerebrovascular/physiological, neuroimaging, sleep, and genetic factors that will provide novel biologic evidence on how aerobic exercise can prevent declines in cognition with ageing. TRIAL REGISTRATION: ClinicalTrials.gov NCT03035851 . Registered on 30 January 2017.

Should Dairy Cattle Be Trained to a Virtual Fence System as Individuals or in Groups?

Pre-commercial virtual fence (VF) neckbands (eShepherd®, Agersens, Melbourne, Vic, Australia) can contain cows within a designated area without the need for physical fencing, through associative learning of a paired audio tone and electrical pulse. Cattle are gregarious, so there may be an impact of herd mates on the learning process. To evaluate this, a VF was set 30 m down one of three test paddocks with a feed attractant 70 m past the VF. Twenty-three Holstein-Friesian cows were all fitted with VF neckbands and trained as individuals or in groups (5-6) for four 10 min tests; then, cows were crossed over to the alternate context for two more 10 min tests. The number of cows breaking through the VF and the number of paired stimuli reduced across time (from 82% to 26% and 45% to 14%, respectively, p < 0.01). Cows trained in a group (88%) were more likely to interact with the VF in the crossover compared to those trained as individuals (36%) (p < 0.01), indicating an influence of group members on individual cow response. Individual training is impractical, therefore, future research should evaluate group training protocols ensuring all cows learn the VF to avoid any adverse impacts on animal welfare.

Automated Monitoring of Panting for Feedlot Cattle: Sensor System Accuracy and Individual Variability.

Heat stress causes significant economic losses by reducing the productivity and welfare of cattle whilst requiring a significant investment in resource for amelioration. Panting score (PS) is considered a robust indicator of cattle heat stress; however, individualised visual monitoring is impractical. Thermal index-based monitoring and mitigation decisions are applied at the herd level, but they have limited application for the individual animal. As such, an automated system to monitor the real-time animal response to heat stress is required for strategic mitigation. Our objectives were to validate an accelerometer-based ear tag sensor to monitor cattle panting and to determine individual variability in heat stress responses with reference to thermal indices. Two experiments were conducted: Experiment 1 validated the sensors, and Experiment 2 determined individual variability comparing sensor data against thermal indices. Ear tag sensors were fitted at feedlot entry to continuously monitor the behaviour of 100 steers of mixed breed in Experiment 1 and 200 steers and heifers of mixed breed in Experiment 2. Sensor-derived 'heavy breathing' was validated against visually observed PS. Sensor-derived behaviour bouts were analysed as 'raw', and single behaviour states were also converted to the preceding bout of ≥2 min, which was referred to as 'fill' data for the validation study. Our results demonstrate the sensors' ability to accurately monitor panting in feedlot cattle. Sensor-recorded 'heavy breathing' duration per animal was highly correlated to observed panting duration for both raw (r = 0.89) and fill (r = 0.90) data; however, the concordance correlation co-efficient was lower for raw (0.45) as compared with fill (0.76). Predicted agreement for raw data were 75%, 45%, and 68% and predicted agreement for fill data were 65%, 54%, and 83% for PS0, PS1, and PS2, respectively. Sensitivity for raw data were 39%, 37%, and 45% and for fill data, they were 59%, 54% and 82% for all PS data, PS1 and PS2, respectively. Specificity and positive predictive values for both raw (77% and 79%, respectively) and fill (65% and 77%, respectively) data show the probability of reporting false positives by sensors to be low. Experiment 2 revealed that the duration of panting increased from 0800 to 1700 h alongside changes in thermal indices with significant differences between and within breed and coat colour categories of cattle, suggesting that grouping and allocating heat amelioration measures by breed and coat colour can be effective in commercial feedlots. However, there was high variability (CV > 80%) in the duration of panting between individuals within the same breed and same coat colour, revealing the potential for strategic management at an individual level, and with the same data, genetic selection for heat resilience.

Milk Yield, Milk Composition, and the Nutritive Value of Feed Accessed Varies with Milking Order for Pasture-Based Dairy Cattle.

(1) Background: Pasture varies in its chemical composition from the top of the sward to the base and cattle prefer to eat the leaf fraction. In pasture-based dairy systems, cattle predominantly walk back to pasture voluntarily after each milking, with the first cattle arriving to pasture hours before the last. Here we study the impact of pasture composition according to milking order on milk yield and milk composition for dairy cattle offered grazed ryegrass pasture. (2) Methods: In the first experiment, individual cow milk yield data were recorded on six farms over 8 months. The herd was divided into groups of 50 cows for analysis according to milking order. In the second experiment, the impact of milking order on milk composition and pasture composition accessed was determined in addition to milk yield on three farms. (3) Results: After accounting for age and stage of lactation effects, cattle milked first in experiment 1 produced, on average, 4.5 L/cow/day (+18%; range 14 to 29%) more than cattle milked last. In experiment 2, dairy cattle milked first (first 50 cows) in farm 1 had greater milk, protein, and solids non-fat (SNF) yield; and less lactose content than those milked last (last 50 cows). In farm 2, dairy cattle milked first had greater milk yield, SNF yield, lactose yield, and fat yield; but less protein and SNF content than cattle milked last. In farm 3, cattle milked first produced milk with greater fat and protein content than cattle milked last. In line with these differences in milk yield and composition, the composition of pasture across vertical strata differed, particularly for crude protein (CP) and acid detergent fiber (ADF) content. Conclusion: This work highlights the opportunity to increase herd nutrient use efficiency for improved milk production through strategic pasture allowance and supplementation strategies.