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Genetics, animal husbandry, and the feedbase all impact cattle growth. Australia's cattle feedbase covers 40% of the continent and encompasses diverse climates and landscapes, making stocking rate decisions challenging. Of the factors contributing to climate change, rainfall is a primary determinant of feedbase growth and, with this, cattle growth. Understanding the interplay between rainfall and cattle growth across the diverse Australian landscape is thus critical to aid farmer decision-making. However, revealing such interactions between landscape and rainfall for cattle growth for such decision-making has until now been infeasible due to a lack of sufficient temporal and spatial cattle growth data. The Optiweigh (OW) system has been deployed across Australia's extensive beef production systems as a voluntary weighing unit, opportunistically monitoring cattle liveweight (LW). This study determined the impact of rainfall on the temporal and spatial variability of beef cattle growth across three of Australia's agro-climatic zones (grassland, subtropical, and temperate), aiming to describe the diverse feedbase through patterns of LW variability. A total of 1.3 million cattle LW observations were collected from 82 026 cattle over 2 years (2020-2022). Rainfall data from the Australian Bureau of Meteorology were also collated for the closest meteorological station to each OW unit. Cattle LW average daily gain (ADG) was clustered by season and zone. A series of linear mixed models were used to examine ADG for each zone-season combination, with random effects for individual animals and farms, and fixed effects for climate zone and current and lagged rainfall. The overall mean ADG for the dataset was 0.68 kg/day, with greater growth variability between farms within a zone (SD: 0.349 ± 0.021 kg/day, estimate ± SE) than between cattle within a farm (SD: 0.229 ± 0.004 kg/day). This ADG variability can be partly attributed to the timing and amount of rainfall, with agro-climatic zones showing unique interactions between rainfall and ADG. Seasonal lagged rainfall effects were present in the grassland and temperate zones, while rainfall in the temperate zone had a year-round effect on cattle growth. Furthermore, season-wise lagged rainfall had mixed effects on ADG, whereas rainfall occurring in a season reduced growth in the same season across zones (P < 0.001). These findings provide valuable initial insights into the variability of ADG across the landscape over time and markedly improve our understanding of the interplay between climate and Australia's diverse feedbase, contributing to improved management strategies., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

With increasing climate variability, there is a rise in the exposure to, and incidence of, ruminant heat stress (HS), increasing the requirement for focused research. As such, precise terminology is crucial to maintain effective communication and knowledge advancement. Despite this, several key terms are currently defined inconsistently, leading to confusion and misinterpretation. This paper examines the historical and contemporary use of the terms 'resistance', 'tolerance', 'resilience', and 'susceptibility' across various disciplines, revealing significant ambiguities that hinder both research and practice. Through this comprehensive review, we propose new definitions for each term as they are used relating to HS, with a focus on ruminant production. Proposed definitions align with current scientific understanding, providing a robust framework for future research and application. As further research is conducted, we hope these definitions can be improved through the inclusion of quantitative measures which align with these classifications. This present review provides definition clarity for common heat abatement terminology, enabling consistency and from this, progress in the field to ameliorate HS for ruminants., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

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.

Modern intensive dairy farming relies on data to aid and prioritize management decisions made on farm. Decisions made early in an animal's life can have lasting effects on welfare, productivity, longevity, and profitability. Precision technology such as automated calf feeders (ACF) allow the customization of feeding programs, but despite this, weaning weights (WWT) vary substantially between calves. This observational study used a 3-yr dataset comprising 1,440 female Holstein Friesian calves at a single intensive commercial dairy farm (Dairy Australia feeding system 5; indoor, total mixed ration) using ACF to (1) determine the variability in WWT (as a proxy of animal performance) of calves within this system; (2) identify the contributing factors responsible for the variation in WWT; and (3) identify potential early management intervention points that could be indicative of the performance of calves at weaning within the system. Calves entered the ACF at 10 d of age with 12 calves per ACF; calves were weighed at birth and weaning using weigh scales. We discovered a large range of calf WWT (41-118 kg/head) at ~60 d of age despite the application of strict uniform management protocols. Our results from modeling showed that WWT was significantly and positively associated with birth weight (BWT), with low BWT calves (<36 kg) achieving an average of 70 kg weight at weaning. In contrast, heavier BWT (>36 kg) calves achieved an average of 82 kg at weaning. Based on calf feeder data, cumulative milk consumption and cumulative unrewarded visits to the feeder, as well as BWT, were identified as indicators of greater WWT as all these were highly significant terms in the model for WWT. Results suggest that quantifying consumption and number of visitations to the ACF at d 5 may allow farmers to identify, with time to intervene, calves underperforming within the feeder or system, therefore increasing their potential for growth. Additionally, this demonstrated that greater milk consumption (>30 kg) and interaction with the feeder up to d 5 in the feeder is more likely to yield a WWT >75 kg, identifying a potential point for management intervention for calves below consumption and interaction thresholds (e.g., by developing alarm systems based on consumption or visitation number)., (© 2024.)

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.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Islam, Garcia, Sarker, Islam and Clark.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ojeda, Islam, Correa-Luna, Gargiulo, Clark, Rotili and Garcia.)

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.

Core body temperature (CBT) regulation is crucial for mammalian wellbeing and survival. Cattle pant to dissipate excess heat to regulate CBT when ambient conditions exceed thermoneutral zones. However, to date, neither the variability in cattle heat response, the lagged response of CBT to thermal indices, nor the diurnal patterns of thermal indices, CBT and panting have been reported in the literature. We decomposed thermal indices, CBT and panting time-series data for 99 feedlot heifers across three discrete heat events into diurnal, trend and residual components. Both raw and decomposed data were analysed to explore the lagged CBT and panting responses and the association between series. We show ambient thermal conditions impact CBT with a 1-h lag despite a lag of between 1.5 to 3 h from raw data. Average individual panting scores were used to identify heat-susceptible and heat-tolerant cattle. Heat-susceptible cattle showed greater CBT (P < 0.01) between 8:00 and 23:00 and greater panting duration (P < 0.05) between 10:00 and 18:00 than heat-tolerant cattle under the same thermal conditions and these variations followed a similar pattern despite differences in cattle breed. This new information enables targeted amelioration and selection of individuals against heat susceptibility., (© 2023. The Author(s).)

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.

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 (R 2 ), 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 R 2 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 R 2 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., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Conventional locomotion scoring is a subjective, absolute, and discrete assessment of locomotion. Here we assess pairwise comparison scoring to improve upon the limited intra- and interobserver consistency typical of conventional locomotion scoring. Five observers performed conventional 4-level locomotion scoring using 50 video recordings of dairy cattle, and also assessed 90 pairs of videos (composed from the same 50 recordings) using relative pairwise scoring. Intra- and interobserver consistency of pairwise scores [intraobserver: percentage agreement (PA) = 82%, κ = 0.63; interobserver: PA = 79%, κ = 0.57] were greater than of 4-level absolute scores (intraobserver: PA = 72%, κw = 0.74; interobserver: PA = 56%, κw = 0.59). Pairwise scores were scaled with an optimization method to obtain the position of the 50 recordings on a continuous locomotion scale. These continuous locomotion scores (CLS) were compared with the conventional mean absolute visual locomotion scores (VLS). Correlation between CLS and VLS was strong (τ = 0.69), and consistency between binarized CLS and binarized VLS was high (PA = 84%, κ = 0.66 for threshold VLS ≥1). Just noticeable difference (JND) for locomotion scoring was 0.3 on a 4-level scale ranging from 0 to 3. Pairwise scoring and scaling had the scoring consistency of binary absolute scoring with finer continuous granularity than 4-level absolute scoring. The pairwise scoring method, and associated scaling, offer a more consistent and informative alternative to conventional absolute multilevel locomotion scoring., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The timing of eating, relative to when feed is offered, is affected by the social rank of feedlot cattle due to limited feed bunk space. As cattle can select feed based on dietary preference, the timing of eating for cattle in feedlot may be associated with the ingested diet composition. Our objectives were to determine the nutritive value and timing of feed ingested by 100 feedlot cattle during transition and the association of timing of eating with feeding behaviours and average daily gain (ADG). Cattle behaviour and timing of eating were determined on 100 feedlot cattle using accelerometer-based ear tag sensors from days 3 to 6 post feedlot induction (observation period), and the ongoing impact of this period on ADG was determined for the full feed period (75 days). To determine eating patterns at the time of feed offer, cattle were grouped according to the number of days they were recorded as eating within 1 h of feed being offered across 4 observation days, G 0 : not present across 4 days, G 1 : present for 1 day, G 2 : 2 days, G 3 : 3 days and G 4 : present for each of the 4 days. Total mixed ration (TMR) samples were collected for nutritive value analysis from four locations along the feed bunk from the time feed was offered and at hourly intervals thereafter for 7 h each day during the observation period. The composition of feed in the bunk changed across the 7 h of measurement (P < 0.05). The DM and CP of feed increased from 65 to 70% and 15 to 16%, respectively, and the NDF decreased from 36 to 32%. Thus, the preferred TMR feed component was the fibrous dietary fraction. However, the overall composition of the ingested diet for 7 h post feeding was similar between groups. Cattle in G 0 had reduced eating time (0.7 vs 4.8%; P < 0.001), rumination time (4.5 vs 19.5%; P < 0.001) and ADG (1.0 vs 1.3 kg/d; P < 0.05) across the study, as compared with cattle in G 4 . Offering a more fibrous ration during feedlot transition, and customised cattle segregation and/or customised feeding regimes based on sensor derived feeding behaviour profiles during acclimation to feedlot can optimise ADG, animal welfare and feedlot profit., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

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., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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.

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.

The diurnal feeding patterns of dairy cows affects the 24 h robot utilisation of pasture-based automatic milking systems (AMS). A decline in robot utilisation between 2400 and 0600 h currently occurs in pasture-based AMS, as cow feeding activity is greatly reduced during this time. Here, we investigate the effect of a temporal variation in feed quality and quantity on cow feeding behaviour between 2400 and 0600 h as a potential tool to increase voluntary cow trafficking in an AMS at night. The day was allocated into four equal feeding periods (0600 to 1200, 1200 to 1800, 1800 to 2400 and 2400 to 0600 h). Lucerne hay cubes (CP = 19.1%, water soluble carbohydrate = 3.8%) and oat, ryegrass and clover hay cubes with 20% molasses (CP = 11.8%, water soluble carbohydrate = 10.7%) were offered as the 'standard' and 'preferred' (preference determined previously) feed types, respectively. The four treatments were (1) standard feed offered ad libitum (AL) throughout 24 h; (2) as per AL, with preferred feed replacing standard feed between 2400 and 0600 h (AL + P); (3) standard feed offered at a restricted rate, with quantity varying between each feeding period (20:10:30:60%, respectively) as a proportion of the (previously) measured daily ad libitum intake (VA); (4) as per VA, with preferred feed replacing standard feed between 2400 and 0600 h (VA + P). Eight non-lactating dairy cows were used in a 4 × 4 Latin square design. During each experimental period, treatment cows were fed for 7 days, including 3 days habituation and 4 days data collection. Total daily intake was approximately 8% greater (P < 0.001) for the AL and AL + P treatments (23.1 and 22.9 kg DM/cow) as compared with the VA and VA + P treatments (21.6 and 20.9 kg DM/cow). The AL + P and VA treatments had 21% and 90% greater (P < 0.001) dry matter intake (DMI) between 2400 and 0600 h, respectively, compared with the AL treatment. In contrast, the VA + P treatment had similar DMI to the VA treatment. Our experiment shows ability to increase cow feeding activity at night by varying feed type and quantity, though it is possible that a penalty to total DMI may occur using VA. Further research is required to determine if the implementation of variable feed allocation on pasture-based AMS farms is likely to improve milking robot utilisation by increasing cow feeding activity at night.

Feed accounts for the greatest proportion of egg production costs and there is substantial variation in feed to egg conversion ratio (FCR) efficiency between individual hens. Despite this understanding, there is a paucity of information regarding layer hen feeding behaviour, diet selection and its impact on feed efficiency. It was hypothesised that variation in feed to egg conversion efficiency between hens may be influenced by feeding behaviour. For this experiment, two 35-bird groups of ISA Brown layers were selected from 450 individually caged hens at 25-30 weeks of age for either low FCR < 1.8 ± 0.02 (high feed efficiency (HFE) or high FCR > 2.1 ± 0.02 (low feed efficiency (LFE)). For each of these 70 hens, intake of an ad-libitum mash diet at 2-minute time intervals, 24 h a day, for 7 days was determined alongside behavioural assessment and estimation of the selection of components of the mash. The group selected for HFE had a lower feed intake, similar egg mass and associated lower FCR when compared with the LFE group. Whilst feed intake patterns were similar between HFE and LFE hens, there was a distinct intake pattern for all layer hens with intake rate increasing from 0300 to 1700 h with a sharp decline to 2200 h. High feed efficiency hens selected a diet with 25% more ash and 4% less gross energy than LFE hens. The LFE hens also spent more time eating with more walking events, but less time spent resting, drinking, preening and cage pecking events as compared with HFE hens. In summary, there was no contrasting diurnal pattern of feed consumption behaviour between the groups ranked on feed efficiency, however high feed efficiency hens consumed less feed and selected a diet with greater ash content and lower gross energy as compared with LFE hens. Our work is now focused on individual hen diet selection from mash diets with an aim of formulating precision, targeted diets for greater feed efficiency., Competing Interests: The authors have no competing interests to declare.

Pasture management in Australia's dairy industry requires the manual shifiting of temporary electric fences to maintain pasture quality and growth. Virtual fencing presents an alternative to save time and labour costs. We used automated virtual fence (VF) collars to determine the variation in learning of the virtual fence stimuli, and evaluated the success of the technology to contain cows in a predetermined area of pasture. Twelve Holstein-Friesian non-lactating multiparous dairy cows were fitted with the collars, and a VF was used to restrict cows to two grazing allocations (G1 and G2) across six days. Cows received an audio tone (AT) when they approached the virtual fence, and a paired electrical pulse (EP) if they continued forward. The VF contained cows within predetermined areas for 99% of time, but cows spent the least time near the fence ( p < 0.01). The number of stimuli reduced through time, demonstrating the ability of cows to learn the VF ( p = 0.01). However, the mean number of EP per day ranged from 1 to 6.5 between individuals ( p < 0.01). Therefore, successful containment may have a welfare cost for some individuals. Further work should focus on this individual variation, including measures of welfare.

Achieving a consistent level of robot utilisation throughout 24 h maximises automatic milking system (AMS) utilisation. However, levels of robot utilisation in the early morning hours are typically low, caused by the diurnal feeding behaviour of cows, limiting the inherent capacity and total production of pasture-based AMS. Our objective was to determine robot utilisation throughout 24 h by dairy cows, based on milking frequency (MF; milking events per animal per day) in a pasture-based AMS. Milking data were collected from January and February 2013 across 56 days, from a single herd of 186 animals (Bos taurus) utilising three Lely A3 robotic milking units, located in Tasmania, Australia. The dairy herd was categorised into three equal sized groups (n=62 per group) according to the cow's mean daily MF over the duration of the study. Robot utilisation was characterised by an interaction (P&lt; 0.001) between the three MF groups and time of day, with peak milking time for high MF cows within one h of a fresh pasture allocation becoming available, followed by the medium MF and low MF cows 2 and 4 h later, respectively. Cows in the high MF group also presented for milking between 2400 and 0600 h more frequently (77% of nights), compared to the medium MF group (57%) and low MF group (50%). This study has shown the formation of three distinct groups of cows within a herd, based on their MF levels. Further work is required to determine if this finding is replicated across other pasture-based AMS farms.

In pasture-based automatic milking systems (AMS), a decrease in robot utilization (RU) often occurs in the early morning hours. Novel feeding strategies that encourage voluntary cow traffic throughout 24 h could help mitigate this problem. We determined the effect of 3 distinct pasture allocation methods on RU patterns throughout a 24-h period. The experiment was conducted at the University of Melbourne's Dookie research farm in northern Victoria, Australia. Three Lely Astronaut A3 robotic milking units (Lely, Maassluis, the Netherlands) milked 133 cows, grazing pasture, with concentrate offered at milking in the robots. The farm operated a system of 3-way grazing, with active access to each pasture allocation: 2030-0400 h (allocation A), 0400-1330 h (allocation B), and 1330-2030 h (allocation C). Treatments varied in the quantity of feed offered per hour of active access to each of the 3 pasture allocations. The control treatment offered the same proportion of feed (corrected for active access time) in all 3 pasture allocations (allocation A = 31.3%, B = 39.6%, and C = 29.2%). The day treatment offered the largest proportion of feed during the day (allocation A = 20%, B = 40%, and C = 40%), following the cows' diurnal pattern of feeding activity. The night treatment offered the largest proportion of feed at night (allocation A = 42%, B = 40%, and C = 18%). Due to the nature of pasture-based AMS, treatments could not be applied simultaneously. Therefore, treatments were applied to the entire herd and repeated twice over 42 d, lasting 7 d/treatment, with the first 3 d for habituation, followed by 4 d of data collection. Robot utilization (milkings/h) varied throughout 24 h between treatments, with the night treatment recording greater RU at 0800, 1800, and 1900 h and lower RU between 2100 to 0100 h, compared with the day treatment. The proportion of the herd milking between 0000 and 0600 h was greater for the control (43.3%) and day (45.3%) treatments compared with the night treatment (25.8%). Herd-average daily pasture intake was similar (10.5 kg of dry matter) for all treatments. This experiment is the first to demonstrate the manipulation of RU by varying the quantity of pasture offered. However, the use of variable allocation alone did not eliminate the decrease in RU between 0000 and 0600 h, with the timing of allocation also likely to play a role. We recommend a further research focus on combining both timing and quantity of pasture allocated to improve RU in pasture-based AMS., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

This study investigated the potential for accurate detection of clinical mastitis (CM) in an automatic milking system (AMS) using electronic data from the support software. Data from cows were used to develop the model, which was then tested on 2 independent data sets, 1 with 311 cows (same farm but from a different year) and 1 with 568 cows (from a different farm). In addition, the model was used to test how well it could predict CM 1 to 3 d before actual clinical diagnosis. Logistic mixed models were used for the analysis. Twelve measurements were included in the initial model before a backward elimination, which resulted in the following 6 measurements being included in the final model: quarter-level milk yield (MY; kg), electrical conductivity (EC; mS/cm), average milk flow rate (MF; kg/min), occurrence of incompletely milked quarters in each milking session (IM; yes or no), MY per hour (MYH; kg/h), and EC per hour (ECH; mS/cm/h) between successive milking sessions. The other 6 measurements tested but not included in the final model were peak milk flow rate (kg/min), kick-offs (yes or no) in each milking session, lactation number, days in milk (d), blood in milk (yes or no), and a calculated mastitis detection index used by DeLaval (DelPro software; DeLaval International AB, Tumba, Sweden). All measurements were assessed to determine their ability to detect CM as both individual variables and combinations of the 12 above-mentioned variables. These were assessed by producing a receiver operating characteristic curve and calculating the area under the curve (AUC) for each model. Overall, 9 measurements (i.e., EC, ECH, MY, MYH, MF, IM, peak flow rate, lactation number, and mastitis detection index) had significant mastitis detection ability as separate predictors. The best mastitis prediction was possible by incorporating 6 measurements (i.e., EC, ECH, MY, MYH, MF, and IM) as well as the random cow and quarter effects in the model, resulting in 90% sensitivity and 91% specificity with excellent AUC (0.96). Assessment of the model was found to produce robust results (AUC >0.9) in different data sets and could detect CM with reductions in sensitivity and specificity with increasing days before actual diagnosis. This study demonstrated that improved mastitis status prediction can be achieved by using multiple measurements, and new indexes based on that are expected to result in improved accuracy of mastitis alerts, thereby improving the detection ability and utility on farm., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Grain-based concentrate (GBC) supplement is of high cost to dairy farmers as a feed source as opposed to grazed pasture. Milk production response to GBC is affected by the composition and nutritive value of the remainder of the diet, animal factors, and interactions between forage type and level of GBC. In grazing systems, dairy cattle encounter contrasting pasture states, primarily because the social structure of the herd affects the timing of when each animal accesses a paddock after milking as a result of a relatively consistent cow milking order. However, the effect of feed management, namely pasture state and GBC allocation, on dairy cattle production and behavior is unknown. We examined the effect of varying GBC allocation for dairy cattle grazing differing states of kikuyu grass (Pennisetum clandestinum, a tropical pasture species; experiment 1) and annual ryegrass (Lolium multiflorum L., a temperate pasture species; experiment 2) on dry matter intake, milk production and composition, and grazing behavior. For each experiment, 90 lactating dairy cattle were randomly allocated to 2 consistent (fresh-fresh and depleted-depleted) and 2 inconsistent (fresh-depleted and depleted-fresh pasture state treatments (defined as sequences of pasture state allocation for the morning and afternoon grazing events) and 3 GBC treatments [2.7, 5.4, and 8.1 kg of dry matter (DM)/cow per day], giving 12 treatment combinations for each experiment. The duration of each experiment was 14 d, with the first 7 d used as adaptation to treatment. In each experiment, 3 cattle were selected from each of the 12 pasture type × GBC treatment groups within the experimental herd to determine herbage intake and total DM digestibility using the n-alkanes method (n = 36). There was no interaction between kikuyu grass or ryegrass pasture state and GBC level for intake, digestibility, or milk yield or components. Dairy cattle offered fresh-fresh and depleted-fresh ryegrass produced 9% more milk yield, in line with greater pasture intakes, compared with fresh-depleted and depleted-depleted pasture states. Dairy cattle offered fresh-fresh kikuyu grass had 8% more milk yield and 14% more milk protein yield than other pastures states, but there was no effect of pasture state on milk composition. Milk yield increased with GBC level for both pasture species (∼0.7-0.8 kg of milk/kg of DM GBC) as GBC level increased from 2.5 to 5.4 kg of DM/cow per day. There was a poor response (0.3 kg of milk/kg of DM GBC), and no response, when GBC levels increased from 5.4 to 8.1 kg of DM/cow per day for kikuyu grass and ryegrass, respectively, in line with pasture DMD. Time spent grazing, lying, and ruminating were not associated with kikuyu grass pasture state, GBC, or their interaction. Despite this, there was a linear increase in grazing time in the afternoon coinciding with a linear decrease in lying and rumination time for both kikuyu grass and ryegrass pasture. Together these findings reveal the effect of pasture state and GBC allocation on dairy cattle production and behavior. Tailoring GBC allocation to the state of pasture accessed by cattle appears unwarranted, but there is an opportunity to alter the timing of pasture access to increase herd-level milk production efficiency., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Vocalisations are commonly expressed by gregarious animals, including cattle, as a form of short- and long-distance communication. They can provide conspecifics with meaningful information about the physiology, affective state and physical attributes of the caller. In cattle, calls are individually distinct meaning they assist animals to identify specific individuals in the herd. Consequently, there is potential for these vocalisations to be acoustically analysed to make inferences about how individual animals or herds are coping with their external surroundings, and then act on these signals to improve feed conversion efficiency, reproductive efficiency and welfare. In the case of dairy farming, where herd sizes are expanding and farmers are becoming more reliant on technologies to assist in the monitoring of cattle, the study of vocal behaviour could provide an objective, cost effective and non-invasive alternative to traditional measures of welfare. The vocalisations of cattle in response to calf separation, social isolation and painful husbandry procedures, alongside changes to feeding and oestrous activity are here reviewed. For future application of sound technology, research is first necessary to analyse the acoustic structure of cattle vocalisations and determine the specific information they encode. This review draws together the latest research in field of cattle bioacoustics highlighting how the source-filter theory and affective state dimensional approach can be adopted to decode this information and improve on-farm management.

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., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The diurnal variation in pasture nutritive value adds a confounding factor to studies elucidating the effect of time of day on behavior. Our work separates the effect of time of day on both feeding and lying patterns for cows outdoors to enable the alignment of feeding behavior with feed management. We determined the diurnal intake patterns and behavior of dairy cows when the nutritive value of feed remained constant throughout 24 h in an outdoor environment, and when feed access was restricted. Nine nonlactating Holstein-Friesian cows (live weight 626 ± 53 kg, age 96 ± 33 mo; mean ± SD) were split into 3 groups of 3 and offered lucerne hay cubes (cube volume 32 mm 3 ) ad libitum according to 3 treatments: full access (FA, feed access 24 h), day access (DA, feed access between 0600 and 1800 h), and night access (NA, feed access between 1800 and 0600 h). Treatments were applied to individual cows in a crossover design with 7-d periods. During the last 4 d of each period, data were collected on feed intake, as well as feeding and lying behaviors. Total daily intake was greater for cows on the FA treatment (3.5% of BW) compared with the DA and NA treatments at 3.1 and 2.9% of BW, respectively. The cows with FA consumed 69% of their total intake during the day (0600-1800 h), with the greatest intake (39%) occurring during 1200 to 1800 h and only 12% of intake occurring during 2400 to 0600 h. Cows with DA consumed 56% of feed during 0600 to 1200 h and 44% during 1200 to 1800 h. In contrast, NA cows consumed more feed (74%) during the first 6 h period (1800-2400 h), thus maximizing lying time between 2400 and 0600 h. The time spent lying throughout daylight periods varied between treatments; however, total daily lying time was similar across the 3 treatments. This experiment shows the feeding and lying behaviors of cows when feed quality remains constant throughout 24 h, which will assist the formulation of variable feed allocation strategies for future testing in both robotic and conventional milking systems. Varying the quantity of feed offered throughout 24 h may benefit robot utilization at night in automatic milking systems through increased feeding activity, and as we observed, is likely to have little effect on lying time or DMI, with cows readily adapting to changes in feed management. Conversely, aligning feed on offer with preferred feeding time in conventional milking systems may increase the intake of high quality pasture., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)