Optimising profitability and productivity of pasture-based dairy farms with automatic milking systems.

There is a large variability in profitability and productivity between farms operating with automatic milking systems (AMS). The objectives of this study were to identify the physical factors associated with profitability and productivity of pasture-based AMS and quantify how changes in these factors would affect farm productivity. We utilised two different datasets collected between 2015 and 2019 with information from commercial pasture-based AMS farms. One contained annual physical and economic data from 14 AMS farms located in the main Australian dairy regions; the other contained monthly, detailed robot-system performance data from 23 AMS farms located across Australia, Ireland, New Zealand, and Chile. We used linear mixed models to identify the physical factors associated with different profitability (Model 1) and partial productivity measures (Model 2). Additionally, we conducted a Monte Carlo simulation to evaluate how changes in the physical factors would affect productivity. Our results from Model 1 showed that the two main factors associated with profitability in pasture-based AMS were milk harvested/robot (MH; kg milk/robot per day) and total labour on-farm (full-time equivalent). On average, Model 1 explained 69% of the variance in profitability. In turn, Model 2 showed that the main factors associated with MH were cows/robot, milk flow, milking frequency, milking time, and days in milk. Model 2 explained 90% of the variance in MH. The Monte Carlo simulation showed that if pasture-based AMS farms manage to increase the number of cows/robot from 54 (current average) to âˆ¼ 70 (the average of the 25% highest performing farms), the probability of achieving high MH, and therefore profitability, would increase from 23% to 63%. This could make AMS more attractive for pasture-based systems and increase the rate of adoption of the technology.

Physical and economic comparison of pasture-based automatic and conventional milking systems.

Automatic milking systems (AMS) have the potential to increase dairy farm productivity and profitability; however, adoption rates, particularly in pasture-based systems, have been lower than expected. The objectives of this study were to compare the physical and economic performance of pasture-based AMS with conventional milking systems (CMS) and to identify gaps for improving AMS productivity and profitability. We used data from 14 AMS and 100 CMS located in the main Australian dairy regions and collected over 3 yr (2015-2016, 2016-2017, 2017-2018). Farms within similar regions and herd sizes were compared. Results showed that all the main physical performance indicators evaluated such as milk production per cow, milk production per hectare, pasture grazed per hectare, or milk solids per full-time equivalent were similar between systems. The AMS farms had higher overhead costs such as depreciation and repairs and maintenance; however, no differences in total labor costs were observed between systems. Profitability, measured as earnings before interest and tax, operating profit margin, and return on total assets, was not significantly different between AMS and CMS. Opportunities for improving pasture utilization, labor efficiency, and robot utilization in AMS farms were identified. Improving efficiency in these areas could improve productivity and profitability of these systems, and therefore increase the interest of this technology.

Modeling variability of the lactation curves of cows in automated milking systems.

Historically, cow selection criteria were developed for conventional milking systems that have regular milking intervals (MI). However, in automatic milking systems (AMS), there is variability in MI within and between cows. These sources of variability provide an opportunity to identify cows with high daily milk yield (DY) and long MI. An extended MI (longer than 16 h in pasture-based systems) has a negative effect on DY. Cows that tolerate extended MI and maintain high DY can be considered more efficient than cows with low DY and long MI, or with high DY but short MI, thereby improving robotic system use. Knowledge of the behavior and parameters of lactation curves of cows in AMS could help farmers to identify cows with a specific lactational phenotype. The objective of this study was to identify individual cows with high DY and long MI within herds, which could reflect increased tolerance to milk accumulation under AMS. A database containing records for 773,483 milking events for one year (July 2016-June 2017) from 4 pasture-based AMS farms was used. Lactation curves within each herd were fitted using several mixed models including fixed effects for the parameters of the lactation curve and random cow effects. Predicted curves of average DY according to parity (multiparous and primiparous) were obtained. The best linear unbiased prediction of the random cow effect allowed us to categorize lactations as having either high or low milk production. The median MI of each lactation was then used to categorize cows as having either short or long MI. Daily yield at the peak of lactation, days to peak and 305-d cumulative milk production were used to compare the effect of DY and MI categories, as well as the DY × MI interaction. Milk production by multiparous and primiparous cows with high DY and long MI was between 35 and 45% higher than that of the low DY and short MI. From all lactations analyzed, the incidence of animals with high DY and long MI across farms was 7.5%. We have identified and quantified a new, AMS-specific, phenotype (the combination of a relatively higher DY with relatively longer MI) with potential to increase use of AMS units. Identifying more efficient animals should help generate new approaches for differential management and for selecting cows in AMS.

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.

Dairy farmers with larger herd sizes adopt more precision dairy technologies.

An increase in the average herd size on Australian dairy farms has also increased the labor and animal management pressure on farmers, thus potentially encouraging the adoption of precision technologies for enhanced management control. A survey was undertaken in 2015 in Australia to identify the relationship between herd size, current precision technology adoption, and perception of the future of precision technologies. Additionally, differences between farmers and service providers in relation to perception of future precision technology adoption were also investigated. Responses from 199 dairy farmers, and 102 service providers, were collected between May and August 2015 via an anonymous Internet-based questionnaire. Of the 199 dairy farmer responses, 10.4% corresponded to farms that had fewer than 150 cows, 37.7% had 151 to 300 cows, 35.5% had 301 to 500 cows; 6.0% had 501 to 700 cows, and 10.4% had more than 701 cows. The results showed that farmers with more than 500 cows adopted between 2 and 5 times more specific precision technologies, such as automatic cup removers, automatic milk plant wash systems, electronic cow identification systems and herd management software, when compared with smaller farms. Only minor differences were detected in perception of the future of precision technologies between either herd size or farmers and service providers. In particular, service providers expected a higher adoption of automatic milking and walk over weighing systems than farmers. Currently, the adoption of precision technology has mostly been of the type that reduces labor needs; however, respondents indicated that by 2025 adoption of data capturing technology for monitoring farm system parameters would be increased.

Direct detection and characterization of foot-and-mouth disease virus in East Africa using a field-ready real-time PCR platform.

Effective control and monitoring of foot-and-mouth disease (FMD) relies upon rapid and accurate disease confirmation. Currently, clinical samples are usually tested in reference laboratories using standardized assays recommended by The World Organisation for Animal Health (OIE). However, the requirements for prompt and serotype-specific diagnosis during FMD outbreaks, and the need to establish robust laboratory testing capacity in FMD-endemic countries have motivated the development of simple diagnostic platforms to support local decision-making. Using a portable thermocycler, the T-COR™ 8, this study describes the laboratory and field evaluation of a commercially available, lyophilized pan-serotype-specific real-time RT-PCR (rRT-PCR) assay and a newly available FMD virus (FMDV) typing assay (East Africa-specific for serotypes: O, A, Southern African Territories [SAT] 1 and 2). Analytical sensitivity, diagnostic sensitivity and specificity of the pan-serotype-specific lyophilized assay were comparable to that of an OIE-recommended laboratory-based rRT-PCR (determined using a panel of 57 FMDV-positive samples and six non-FMDV vesicular disease samples for differential diagnosis). The FMDV-typing assay was able to correctly identify the serotype of 33/36 FMDV-positive samples (no cross-reactivity between serotypes was evident). Furthermore, the assays were able to accurately detect and type FMDV RNA in multiple sample types, including epithelial tissue suspensions, serum, oesophageal-pharyngeal (OP) fluid and oral swabs, both with and without the use of nucleic acid extraction. When deployed in laboratory and field settings in Tanzania, Kenya and Ethiopia, both assays reliably detected and serotyped FMDV RNA in samples (n = 144) collected from pre-clinical, clinical and clinically recovered cattle. These data support the use of field-ready rRT-PCR platforms in endemic settings for simple, highly sensitive and rapid detection and/or characterization of FMDV.

Review: Capripoxvirus Diseases: Current Status and Opportunities for Control.

Lumpy skin disease, sheeppox and goatpox are high-impact diseases of domestic ruminants with a devastating effect on cattle, sheep and goat farming industries in endemic regions. In this article, we review the current geographical distribution, economic impact of an outbreak, epidemiology, transmission and immunity of capripoxvirus. The special focus of the article is to scrutinize the use of currently available vaccines to investigate the resource needs and challenges that will have to be overcome to improve disease control and eradication, and progress on the development of safer and more effective vaccines. In addition, field evaluation of the efficacy of the vaccines and the genomic database available for poxviruses are discussed.

Epidemiological analysis of an outbreak of foot-and-mouth disease (serotype SAT2) on a large dairy farm in Kenya using regular vaccination.

During August-September 2012, an outbreak of Foot-and-mouth Disease (FMD) due to serotype Southern African Territories-2 (SAT2) occurred on a large, extensively grazed dairy farm in Nakuru County, Kenya. Over 29 days, 400/644 (62.1%) cattle were recorded as displaying clinical signs consistent with FMD. Out of the 18 management groups present, 17 had clinical cases (weighted mean incidence rate 3.5 per 100 cattle-days, 95% CI 2.4, 5.1; range 0.064-10.9). Transmission may have been encouraged when an infected group was moved to a designated isolation paddock. A four to five day minimum incubation period was apparent in five groups for which a point source exposure was evident. Further transmission was associated with the movement of individual animals incubating infection, use of a common dip and milking parlour, and grazing of susceptible groups in paddocks neighbouring to infectious cases. Animals over 18 months old appeared to be at highest risk of disease possibly due to milder clinical signs seen among younger animals resulting in reduced transmission or cases not being recorded. Cows with a breeding pedigree containing a greater proportion of zebu appeared to be at lower risk of disease. The outbreak occurred despite regular vaccination (three times per year) last performed approximately three months before the index case. Incidence risk by the lifetime number of doses received indicated limited or no vaccine effectiveness against clinical disease. Reasons for poor vaccine effectiveness are discussed with antigenic diversity of the SAT2 serotype and poor match between the field and vaccine strain as a likely explanation. Detailed field-derived epidemiological data based on individual animals are rarely presented in the literature for FMD, particularly in East-Africa and with the SAT2 serotype. This study provides a detailed account and therefore provides a greater understanding of FMD outbreaks in this setting. Additionally, this is the first study to provide field-derived evidence of poor vaccine effectiveness using a SAT2 vaccine. Further field-based measures of vaccine effectiveness in line with evaluation of human vaccines are needed to inform FMD control policy which has previously relied heavily upon experimental data and anecdotal experience.

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.

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.

Animal behavior and pasture depletion in a pasture-based automatic milking system.

In pasture-based automatic milking systems (AMS), feed is the main incentive that can be managed to encourage reliable and consistent voluntary and distributed cow traffic. Modifying timing, placement and size of feed allocations is expected to have an effect on cow behavior that could avoid the occurrence of extended milking intervals, which have a negative effect on milk yield. Therefore, behavioral studies provide information on how cows modify their actions under different management regimes and can help explain the impact of those regimes. Behavioral observations were conducted in spring 2011 at the FutureDairy AMS research farm, as part of a study where a herd of 175 cows was split into two groups that received supplementary feed either before (PRE), or immediately after (POST) milking. In addition, all cows were offered access to two daily pasture allocations. Observations were conducted in the pasture allocation on 15 focal cows from each treatment group during four periods of 24 h to detect presence and behavior (grazing, ruminating, idling and other) every 15 min. In addition, bite rate and pasture biomass were measured every hour. Overall, despite the finding that more POST cows than PRE cows entered the pasture allocation during the first 8 h of active access, there was no difference in the total proportion of cows that had gained access by the end of the active access period (average 68% for both treatments). Cows in the PRE treatment started exiting the pasture allocation just 6 h after entering, compared with 8 h for POST cows, although their behaviors in the pasture allocation did not differ. Behaviors and bite rate were more dependent on pasture biomass than on supplementary feeding management.

Relationships between metabolite and IGF1 concentrations with fertility and production outcomes following left abomasal displacement.

Left displacement of the abomasum (LDA) is an important periparturient disorder of dairy cows. This study evaluated differences in metabolic parameters between case-control pairs of cows (n=67) from 24 farms, and related these to outcomes in fertility and production. Cows with an assisted delivery were ×3 more likely to develop LDA, and affected cows tended to have had a longer dry period. At recruitment, cows with LDA tended to be in lower body condition accompanied by significantly higher circulating concentrations of ß-hydroxybutyrate (BHB), non-esterified fatty acid (NEFA) and glucose and lower IGF1. Overall culling rate for all cows in the subsequent lactation was 22.5 per cent. Cows with LDA were not at increased odds of being culled but they produced, on average, 2272 l less milk and tended to have longer intervals to conception. Considering all cows irrespective of LDA status, the mean IGF1 level at recruitment was the only measured parameter associated with subsequent risk of culling (culled 11.7 ng/ml, not culled 23.5 ng/ml; P=0.005). Our findings support previous work indicating that poor insulin sensitivity through an uncoupling of the somatotrophic axis may be an important factor associated with LDA. Improved nutritional management of dry cows should reduce the incidence of both LDA and culling.

Effect of pre- versus postmilking supplementation on traffic and performance of cows milked in a pasture-based automatic milking system.

Cows milked in a pasture-based automatic milking system tend to have a lower daily milking frequency in comparison with cows milked in indoor systems. Milking events with intervals beyond 16h have been reported to have a negative effect on milk yield and udder health, and therefore it is important to minimize their occurrence. As feed is the main incentive to encourage cow traffic around the system, a study was conducted to compare pre- (PRE) versus postmilking (POST) supplementary feed placement strategies in a pasture-based automatic milking system. We hypothesized that PRE cows would have a stronger incentive to walk voluntarily from the paddock to the dairy facility to get milked (due to the reward being more immediate), thereby reducing their milking interval and increasing daily milking frequency and milk yield. The PRE cows returned to the dairy facility sooner (PRE=11.9 vs. POST=13.27h) but had longer milking intervals (PRE=15.3 vs. POST=14.28h). This was due to the additional time spent in the prefeeding area (PRE=56 versus POST=23min) combined with a longer average time spent in the premilking waiting yard (PRE=97 versus POST=77min). Treatment did not affect daily milk yield per cow. The result of this study demonstrates the potential of manipulating feeding management strategies to influence cow behavior and traffic in voluntary milking systems.

Comparison of 2 systems of pasture allocation on milking intervals and total daily milk yield of dairy cows in a pasture-based automatic milking system.

Cows milked in pasture-based automatic milking systems (AMS) have greater milking intervals than cows milked in indoor AMS. Long milking intervals greater than 16h have a negative effect on milk yield and udder health. The impact of 2 systems of pasture allocation in AMS on milking interval and yield was investigated at the FutureDairy AMS research farm (Elizabeth Macarthur Agricultural Institute, New South Wales Department of Primary Industries, Camden, New South Wales, Australia) in late November to early December 2010. Two- (2WG) versus 3-way grazing (3WG) allocations per 24-h period were compared in a field study to test the hypothesis that an increase in the frequency of pasture allocation would reduce the milking interval and, therefore, increase milking frequency. The study involved the entire milking herd of 145 cows, with (mean ± SD) DIM=121±90d, 7-d average milking frequency=1.52±0.41 milkings/cow per day, and 7-d average milk yield=21.3±7.6kg/cow per day. Cows were milked using 2 DeLaval VMS milking units (DeLaval International AB, Tumba, Sweden). Cows in the 3WG treatment had 31% reduced milking interval, 40% greater milking frequency, and 20% greater daily milk production compared with 2WG. Increased milking frequency and milk production for 3WG was associated with greater utililization levels of the AMS milking units throughout the day. These results support the recommendation that, wherever possible, farmers installing AMS should incorporate sufficient infrastructure to accommodate 3WG, which provides additional flexibility with managing extremely long (and short) milking intervals.

Aspects of bovine caesarean section associated with calf mortality, dam survival and subsequent fertility.

Bovine caesarean section is a common surgery performed by cattle practitioners yet evidence for justifying many aspects of the surgical procedure is lacking. Between 2001 and 2007, questionnaires were used to gather information on 103 cases of caesarean section performed in one, predominantly dairy, veterinary practice. The results showed that the 14-day cow survival rate was 80.6%, and of those surviving beyond this period, 55.4% carried another calf to term, 27.7% were culled due to infertility and 16.9% were culled due to other reasons. Variables associated with reduced 14-day dam mortality included exteriorising the uterus during surgery (odds ratio [OR] 0.018, 95% confidence interval [CI] 0.0019-0.17, P<0.001), dystocia where fetomaternal disproportion was present (OR 0.090, 95% CI 0.097-0.83, P=0.033), a female calf (OR 0.036, 95% CI 0.0019-0.69, P=0.027), no retained fetal membranes at the first post-operative revisit (OR 0.095, 95% CI 0.013-0.69, P=0.020) and removing abdominal blood clots during surgery (OR 0.10, 95% CI 0.011-0.93, P=0.043). Using a Utrecht suture pattern on the uterus was associated with reduced culling due to infertility (OR 0.12, 95% CI 0.020-0.67, P=0.016). Incision infection was noted in 25.9% of cases where incision status was recorded but this was not associated with the type of local anaesthesia used. Overall calf survival up to the first post-operative visit (24-48 h) was 59.4%, and was associated with shorter duration of surgery, and dystocia due to fetomaternal disproportion. These results offer some evidence-based guidelines to optimise outcomes for this common surgery performed under field conditions.

Cost-effectiveness of farm interventions for reducing the prevalence of VTEC O157 on UK dairy farms.

A randomized control trial on verocytotoxigenic Escherichia coli (VTEC)-infected farms found evidence that: (1) keeping animals in the same group; (2) maintaining dry bedding; (3) preventing direct contact with neighbouring cattle; and (4) maintaining a closed herd, were associated with a reduced risk of infection in youngstock aged 3­18 months. This study evaluated these interventions using a cost-effectiveness framework for UK dairy farms. Keeping animals in the same group was considered to have negligible cost and was feasible for herds containing over 77 dairy cows. Assuming equal efficacy of the remaining interventions, preventing direct contact between neighbouring cattle is most cost-effective with a median annual cost of £2.76 per cow. This compares to £4.18 for maintaining dry bedding and £17.42 for maintaining a closed herd using quarantine procedures. Further model validation and exploration of other potential benefits are required before making policy decisions on VTEC control.