Revealing the diversity of internal body temperature and panting response for feedlot cattle under environmental thermal stress.

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.

Pairwise comparison locomotion scoring for dairy cattle.

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.

Timing of eating during transition impacts feedlot cattle diet and liveweight gain.

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, G0: not present across 4 days, G1: present for 1 day, G2: 2 days, G3: 3 days and G4: 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 G0 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 G4. 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.

The effect of temporal variation in feed quality and quantity on the diurnal feeding behaviour of dairy cows.

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.

The effect of pasture quantity temporal variation on milking robot utilization.

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.

Robot utilisation of pasture-based dairy cows with varying levels of milking frequency.

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< 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.

Development of a new clinical mastitis detection method for automatic milking systems.

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.

The effect of temperate or tropical pasture grazing state and grain-based concentrate allocation on dairy cattle production and behavior.

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.

Invited review: The evolution of cattle bioacoustics and application for advanced dairy systems.

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.

Short communication: The diurnal intake and behavior of dairy cows when access to a feed of consistent nutritive value is restricted.

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 mm3) 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.

Review: Milking robot utilization, a successful precision livestock farming evolution.

Automatic milking systems (AMS), one of the earliest precision livestock farming developments, have revolutionized dairy farming around the world. While robots control the milking process, there have also been numerous changes to how the whole farm system is managed. Milking is no longer performed in defined sessions; rather, the cow can now choose when to be milked in AMS, allowing milking to be distributed throughout a 24 h period. Despite this ability, there has been little attention given to milking robot utilization across 24 h. In order to formulate relevant research questions and improve farm AMS management there is a need to determine the current knowledge gaps regarding the distribution of robot utilization. Feed, animal and management factors and their interplay on levels of milking robot utilization across 24 h for both indoor and pasture-based systems are here reviewed. The impact of the timing, type and quantity of feed offered and their interaction with the distance of feed from the parlour; herd social dynamics, climate and various other management factors on robot utilization through 24 h are provided. This novel review draws together both the opportunities and challenges that exist for farm management to use these factors to improved system efficiency and those that exist for further research.

Differential rumination, intake, and enteric methane production of dairy cows in a pasture-based automatic milking system.

Proper performance monitoring of cows on pasture-based diets is crucial to inform nutritional recommendations that minimize undesirable effects of high ruminant CH4 emissions into the environment. The prediction of linkages between rumination patterns, methane emissions, and correlated production traits of cows in a pasture-based automatic milking system was tested. A previous 10-d baseline measurement of rumination activity by acoustic methodology of 156 Holstein-Friesian cows was used for frequency analysis of rumination time and identification of 2 treatment groups (n = 37 cows/group) represented by cows with consistently high (HR; 75th rumination percentile = 617.55 ± 81.37 min/d) or low (LR; 25th rumination percentile = 356.65 ± 72.67 min/d) rumination. The HR and LR cows were paired by nearest parity, days in milk, body weight (BW), and previous 10-d milk production, and within pairs randomly assigned to 1 of 2 experimental groups managed on a voluntary milking system with diets consisting of at least 75% pasture, plus concentrates. Animal traits, including rumination time, mass flux of CH4 (QCH4) and carbon dioxide (QCO2), milk production, and estimated dry matter intake according to individual QCO2 fluxes over a 22-d period were analyzed with repeated measure mixed models for a completely randomized design, structural equation modeling, and nonlinear regression. High rumination and methane was seen in older and heavier cows that had greater estimated dry matter intake and milk production. A consistent difference in rumination time and QCH4 across days was detected between HR and LR, even after adjustment for metabolic BW. Estimated dry matter intake had direct positive effects on rumination and QCH4, but no independent direct effect of rumination on QCH4 was detected. The LR cows produced more QCH4/milk, associated with lower milk, BW, concentrate intake, and greater activity at pasture. A typical dilution of maintenance effect on QCH4/milk was detected as a consequence of increasing milk yield and similar significant reduction of QCO2/milk. The results raise challenging questions regarding the rumination patterning of grazing dairy cows and alternatives to reduce ruminant methane emissions in grazing dairy cows.

Modelling Pasture-based Automatic Milking System Herds: The Impact of Large Herd on Milk Yield and Economics.

The aim of this modelling study was to investigate the effect of large herd size (and land areas) on walking distances and milking interval (MI), and their impact on milk yield and economic penalties when 50% of the total diets were provided from home grown feed either as pasture or grazeable complementary forage rotation (CFR) in an automatic milking system (AMS). Twelve scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as 'moderate'; optimum pasture utilisation of 19.7 t DM/ha, termed as 'high') and 2 rates of incorporation of grazeable complementary forage system (CFS: 0, 30%; CFS = 65% farm is CFR and 35% of farm is pasture) were investigated. Walking distances, energy loss due to walking, MI, reduction in milk yield and income loss were calculated for each treatment based on information available in the literature. With moderate pasture utilisation and 0% CFR, increasing the herd size from 400 to 800 cows resulted in an increase in total walking distances between the parlour and the paddock from 3.5 to 6.3 km. Consequently, MI increased from 15.2 to 16.4 h with increased herd size from 400 to 800 cows. High pasture utilisation (allowing for an increased stocking density) reduced the total walking distances up to 1 km, thus reduced the MI by up to 0.5 h compared to the moderate pasture, 800 cow herd combination. The high pasture utilisation combined with 30% of the farm in CFR in the farm reduced the total walking distances by up to 1.7 km and MI by up to 0.8 h compared to the moderate pasture and 800 cow herd combination. For moderate pasture utilisation, increasing the herd size from 400 to 800 cows resulted in more dramatic milk yield penalty as yield increasing from c.f. 2.6 and 5.1 kg/cow/d respectively, which incurred a loss of up to $AU 1.9/cow/d. Milk yield losses of 0.61 kg and 0.25 kg for every km increase in total walking distance (voluntary return trip from parlour to paddock) and every one hour increase in MI, respectively. The high pasture utilisation combined with 30% of the farm in CFR in the farm increased milk yield by up to 1.5 kg/cow/d, thereby reducing loss by up to $0.5/cow/d (c.f. the moderate pasture and 800 cow herd scenario). Thus, it was concluded that the successful integration of grazeable CFS with pasture has the potential to improve financial performance compared to the pasture only, large herd, AMS.

Modelling Pasture-based Automatic Milking System Herds: Grazeable Forage Options.

One of the challenges to increase milk production in a large pasture-based herd with an automatic milking system (AMS) is to grow forages within a 1-km radius, as increases in walking distance increases milking interval and reduces yield. The main objective of this study was to explore sustainable forage option technologies that can supply high amount of grazeable forages for AMS herds using the Agricultural Production Systems Simulator (APSIM) model. Three different basic simulation scenarios (with irrigation) were carried out using forage crops (namely maize, soybean and sorghum) for the spring-summer period. Subsequent crops in the three scenarios were forage rape over-sown with ryegrass. Each individual simulation was run using actual climatic records for the period from 1900 to 2010. Simulated highest forage yields in maize, soybean and sorghum- (each followed by forage rape-ryegrass) based rotations were 28.2, 22.9, and 19.3 t dry matter/ha, respectively. The simulations suggested that the irrigation requirement could increase by up to 18%, 16%, and 17% respectively in those rotations in El-Niño years compared to neutral years. On the other hand, irrigation requirement could increase by up to 25%, 23%, and 32% in maize, soybean and sorghum based rotations in El-Nino years compared to La-Nina years. However, irrigation requirement could decrease by up to 8%, 7%, and 13% in maize, soybean and sorghum based rotations in La-Nina years compared to neutral years. The major implication of this study is that APSIM models have potentials in devising preferred forage options to maximise grazeable forage yield which may create the opportunity to grow more forage in small areas around the AMS which in turn will minimise walking distance and milking interval and thus increase milk production. Our analyses also suggest that simulation analysis may provide decision support during climatic uncertainty.

Modelling Pasture-based Automatic Milking System Herds: System Fitness of Grazeable Home-grown Forages, Land Areas and Walking Distances.

To maintain a predominantly pasture-based system, the large herd milked by automatic milking rotary would be required to walk significant distances. Walking distances of greater than 1-km are associated with an increased incidence of undesirably long milking intervals and reduced milk yield. Complementary forages can be incorporated into pasture-based systems to lift total home grown feed in a given area, thus potentially 'concentrating' feed closer to the dairy. The aim of this modelling study was to investigate the total land area required and associated walking distance for large automatic milking system (AMS) herds when incorporating complementary forage rotations (CFR) into the system. Thirty-six scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as moderate; optimum pasture utilisation of 19.7 t DM/ha, termed as high) and 6 rates of replacement of each of these pastures by grazeable CFR (0%, 10%, 20%, 30%, 40%, 50%) were investigated. Results showed that AMS cows were required to walk greater than 1-km when the farm area was greater than 86 ha. Insufficient pasture could be produced within a 1 km distance (i.e. 86 ha land) with home-grown feed (HGF) providing 43%, 29%, and 22% of the metabolisable energy (ME) required by 400, 600, and 800 cows, respectively from pastures. Introduction of pasture (moderate): CFR in AMS at a ratio of 80:20 can feed a 400 cow AMS herd, and can supply 42% and 31% of the ME requirements for 600 and 800 cows, respectively with pasture (moderate): CFR at 50:50 levels. In contrast to moderate pasture, 400 cows can be managed on high pasture utilisation (provided 57% of the total ME requirements). However, similar to the scenarios conducted with moderate pasture, there was insufficient feed produced within 1-km distance of the dairy for 600 or 800 cows. An 800 cow herd required 140 and 130 ha on moderate and high pasture-based AMS system, respectively with the introduction of pasture: CFR at a ratio of 50:50. Given the impact of increasing land area past 86 ha on walking distance, cow numbers could be increased by purchasing feed from off the milking platform and/or using the land outside 1-km distance for conserved feed. However, this warrants further investigations into risk analyses of different management options including development of an innovative system to manage large herds in an AMS farming system.

Evaluation of infrared thermography body temperature and collar-mounted accelerometer and acoustic technology for predicting time of ovulation of cows in a pasture-based system.

This study was conducted to test the hypothesis that the specificity of infrared thermography (IRT) in detecting cows about to ovulate could be improved using different body parts that are less likely to be contaminated by fecal matter. In addition, the combined activity and rumination data captured by accelerometers were evaluated to provide a more accurate indication of ovulation than the activity and rumination data alone. Thermal images of 30 cows were captured for different body areas (eye, ear, muzzle, and vulva) twice daily after AM and PM milking sessions during the entire experimental period. Milk progesterone data and insemination records were used to determine the date of ovulation. Cows were fitted with SCR heat and rumination long-distance tags (SCR HR LD) for 1 month. Activity- and rumination-based estrus alerts were initially identified using default threshold values set by the manufacturer; however, a range of thresholds was also created and tested for both activity and rumination to determine the potential for higher levels of accuracy of ovulation detection. Visual assessment of mounting indicators resulted in 75% sensitivity (Se), 100% specificity (Sp), and 100% positive predictive value (PPV). Overall, IRT showed poor performance for detecting cows about to ovulate. Vulval temperature resulted in the greatest (80%) Sp but the poorest (21%) Se compared with the IRT temperatures of other body areas. The SCR HR LD tags default threshold value resulted in 78% Se, 57% Sp, and 70% PPV. Lowering the activity threshold from the default value improved the sensitivity but created a large number of false positives, which resulted in a decrease in specificity. Lowering the activity threshold to 20 resulted in a detection performance of 80% Se, 94% Sp, and 67% PPV, whereas the rumination levels achieved 35% Se, 69% Sp, and 14% PPV. The area under the curve for the activity level, rumination level, and the combined measures of activity and rumination levels were 0.82, 0.54, and 0.75, respectively. Alerts generated by SCR HR LD tags based on a lower activity threshold level had high sensitivity and may be able to detect a high proportion of cows in ovulatory periods in pasture-based system; however, the specificities and positive predictive value were lower than the visual assessment of mounting indicators.

Rumination and activity levels as predictors of calving for dairy cows.

The Australian dairy herd size has doubled over the last 20 years substantially increasing the time that farmers require for individual animal attention to monitor and intervene with events such as calving. Technology will help focus this limited labour resource on individual cows that require assistance. The objective of this experiment was to first determine the profiles of rumination duration and level of activity as determined by sensors between, and within, days around calving and second to use these data to predict the day of calving for pasture-based dairy cows. After 2 weeks from the expected calving date, 27 cows were fitted with SCR HR LD Tags, located in 40×90 m2 paddock and offered ad libitum oaten hay and 2 kg grain-based concentrate/cow per day until calving. Hourly activity and rumination data for each cow, as determined by the SCR tags, were fitted with linear mixed models and all parameters were estimated using restricted maximum likelihood. Rumination duration decreased by 33% over the day prior and the day of calving, with the decline in rumination duration starting the day prepartum. Activity levels were maintained prepartum but increased in the days postpartum. The day of calving was recorded and used to determine the gold standard positive (the day before calving) and negative (all other) dates. A threshold rumination level of 0.9 (decline in rumination duration of 10%) gave the optimal combination of 70% sensitivity and 70% specificity. This experiment shows the potential to use rumination duration to predict the day of calving and the opportunity to use sensor data to monitor animal health.

Grazing Soybean to Increase Voluntary Cow Traffic in a Pasture-based Automatic Milking System.

Pasture-based automatic milking systems (AMS) require cow traffic to enable cows to be milked. The interval between milkings can be manipulated by strategically allocating pasture. The current experiment investigated the effect of replacing an allocation of grazed pasture with grazed soybean (Glycine max) with the hypothesis that incorporating soybean would increase voluntary cow traffic and milk production. One hundred and eighty mixed age, primiparous and multiparous Holstein-Friesian/Illawarra cows were randomly assigned to two treatment groups (n = 90/group) with a 2×2 Latin square design. Each group was either offered treatments of kikuyu grass (Pennisetum clandestinum Hoach ex Chiov.) pasture (pasture) or soybean from 0900 h to 1500 h during the experimental period which consisted of 2 periods of 3 days following 5 days of training and adaptation in each period with groups crossing over treatments after the first period. The number of cows trafficking to each treatment was similar together with milk yield (mean ≈18 L/cow/d) in this experiment. For the cows that arrived at soybean or pasture there were significant differences in their behaviour and consequently the number of cows exiting each treatment paddock. There was greater cow traffic (more cows and sooner) exiting pasture allocations. Cows that arrived at soybean stayed on the allocation for 25% more time and ate more forage (8.5 kg/cow/d/allocation) relative to pasture (4.7 kg/cow/d/allocation). Pasture cows predominantly replaced eating time with rumination. These findings suggest that replacing pasture with alternative grazeable forages provides no additional incentive to increase voluntary cow traffic to an allocation of feed in AMS. This work highlights the opportunity to increase forage intakes in AMS through the incorporation of alternative forages.

Differences in Voluntary Cow Traffic between Holstein and Illawarra Breeds of Dairy Cattle in a Pasture-based Automatic Milking System.

Automatic milking systems (AMS) rely upon voluntary cow traffic (the voluntary movement of cattle around a farm) for milk harvesting and feed consumption. Previous research on conventional milking systems has shown differences between dairy cow breeds for intake and milk production, however, the ability to manipulate voluntary cow traffic and milking frequency on AMS farms through breed selection is unknown. This study investigated the effect of breed (Holstein Friesian versus Illawarra) on voluntary cow traffic as determined by gate passes at the Camden AMS research farm dairy facility. Daily data on days in milk, milk yield, gate passes and milking frequency for 158 Holstein Friesian cows and 24 Illawarra cows were collated by month for the 2007 and 2008 years. Illawarra cows had 9% more gate passes/day than Holstein cows over the duration of the study; however, the milking frequency and milk yield of both breeds were similar. Gate passes were greatest for both breeds in early lactation and in the winter (June to August) and summer (December to February) seasons. These findings highlight an opportunity to translate increased voluntary cow movement associated with breed selection into increased milking frequencies, milk production and overall pasture-based AMS performance.

Supplementing lactating dairy cows fed high-quality pasture with black wattle (Acacia mearnsii) tannin.

A reduction in urinary nitrogen (N) excretion from dairy cows fed pasture containing a high N concentration in the dry matter (DM) will have environmental benefits, because losses to soil water and air by leachate and nitrous oxides (N2O) will be reduced. Condensed tannins (CT) reduce digestion of N, and provision as a dietary additive could have nutritional benefits for production, but the amount required and the responses to different sources of CT on milk production have not been defined. Two experiments were conducted to evaluate effects of supplementation with CT extracted from black wattle (Acacia mearnsii De Wild.) on milk production and faecal N concentration by lactating dairy cows grazing a vegetative Perennial ryegrass (Lolium perenne L.)-based pasture. In one experiment, CT was administered as a drench, twice daily, to 38 multiparous Holstein-Friesian cows assigned to four treatments; control (CONT, 0 g/day), low CT (LCT, 111 g/day), medium CT (MCT, 222 g/day) and high CT (HCT, 444 g/day), grazing as a single group. The CT supplementation affected milk yield (P < 0.001) with a trend of declining milk yield as CT concentration increased from about 0.6 to about 2.9% of dietary DM. Milk urea nitrogen (MUN) decreased at MCT and HCT levels of supplementation (P < 0.01) but milk fat, CP and lactose percentage were not affected by CT supplementation. The CT supplementation increased N concentration in faeces for LCT and MCT treatments (P < 0.05), suggesting partitioning of dietary N away from urine. When CT was pelleted with grain, in a second experiment and fed twice daily as a supplement at milking, it reduced the acceptability relative to pellets without CT, and tended to lower milk production from 25.4 to 24.5 kg/day, although the decline was not significant (P > 0.05). The diet of cows fed pellets with CT contained about 1.2% CT in the DM but neither milk constituents nor MUN were affected by CT-supplemented grain (P > 0.05). These findings demonstrate beneficial effects for production of low concentrations (c. 0.6% DM) of CT from black wattle when given to cows grazing pasture with an N concentration of 3.8%, and suggest a diversion of N from urine, but when CT exceeded about 1.4% of dietary DM, milk production was depressed. The value of supplementing a pasture diet for lactating dairy cows with black wattle tannin extract will depend on costs of supplementation, returns from milk production and liabilities associated with N losses to urine.