Australian Dairy Herds Research Articles

Etiology and epidemiology of digital dermatitis in Australian dairy herds

Bovine digital dermatitis (BDD) is an important cause of lameness in dairy cows worldwide. However, very little is known about this disease in Australian herds, which are predominantly managed on pasture. The primary objectives of this cross-sectional study were to describe the presence and prevalence of BDD in Australian dairy herds and to characterize the microbiota of healthy skin and M4 lesions of BDD-affected, pasture-managed cows. Cows from 71 dairy herds were examined at milking time to identify the presence of BDD lesions. True prevalence was estimated using Bayesian methods with informative priors for sensitivity and specificity. Biopsy samples (n = 60) were collected from cows with and without BDD lesions in 7 pasture-based herds. The microbiota in the superficial and deep strata of each tissue biopsy were characterized via sequencing of the V3-V4 region of the bacterial ribosomal RNA gene. Lesions were detected in 1,817 (11.5%) of 15,813 cows and in 68 of 71 (95.8%) herds. The median herd-level apparent and true prevalences of BDD were 8.5% and 18.1%, respectively, but prevalences varied considerably between farms. On farms with BDD, M4 lesions accounted for 70% to 100% of all lesions (interquartile range = 95.1%-100%, median = 100%); M2 lesions (i.e., large ulcerative lesions) were observed at low prevalence (<2.2%) in the few herds (7/71, 9.9%) where they were found. There was a significant difference in the composition of the microbiota between healthy skin and M4 lesions but not between superficial and deep tissue layers. Several gut- and effluent-associated bacterial taxa, including Lentimicrobium and Porphyromonas, which have previously been associated with BDD, were abundant in BDD lesions but not in control biopsies. Our study supports the idea that such taxa are involved in, although possibly not essential to, lesion development and persistence in pasture-managed cows in Australia. Our results also suggest that Dichelobacter may contribute to the disease process. We conclude that BDD is likely to occur in most Australian dairy farms, but that further studies are needed to identify its effect on cow welfare and productivity. Further investigation of the etiology of BDD in Australian dairy herds is also necessary to inform prevention and control strategies.

Temporal trends in estimated breeding values for daughter fertility in Holstein and Jersey cows in the Australian dairy industry

Context Milk yield and fertility are negatively genetically correlated in dairy cows, so selection for milk yield would be expected to result in genetic deterioration in fertility unless there is concurrent selection for fertility. Aim The main study aim was to describe temporal trends in estimated breeding values (Australian Breeding Values, ABVs) for daughter fertility for Holstein and Jersey cows in Australian dairy herds. Methods A retrospective descriptive study was conducted using milk recording and ABV data from cows in commercial dairy herds. Calvings and lactations from 1980 to 2022 were used, along with ABVs for cows that calved over that period and for sires of those cows. Herd-year mean estimated breeding values were calculated for each breed as the means for cows of that breed that calved in the herd that year. Key results Daughter fertility ABVs declined (i.e. deteriorated) markedly in Holsteins in the Australian dairy industry, commencing before 1980. Rates of decline were most rapid in sires, less rapid in cows and least rapid at herd level. Selection pressure for cows with higher daughter fertility ABVs due to cow culling decisions was probably occurring within Australian herds but any such effect was minimal. The decline in cow daughter fertility ABVs is being reversed, but recovery of herd means in the study population has been slow. The rate of decline in daughter fertility ABVs in Jersey cows was less than for Holsteins. Conclusions Over a period of genetic deterioration, then recovery for a trait, genetic trends in sires are not closely related to genetic trends at herd level. The rapid decline in daughter fertility ABVs for sires probably resulted in substantial reductions in herd reproductive performance and cow longevity in Holstein herds in the Australian dairy industry. Under current trends, it will be a considerable time before the adverse effects of the decline in daughter fertility ABVs are fully reversed. Implications An important ongoing task for animal breeding is to identify and monitor traits that may become important for farmers and community in future but may be declining genetically under current selection decisions.

Synchronization of breeding and its impact on genetic parameters and evaluation of female fertility traits.

Achieving an acceptable level of fertility in herds is difficult for many dairy producers because identifying cows in estrus has become challenging owing to poor estrus expression, increased herd size, and lack of time and skilled labor for estrus detection. As a result, synchronization of estrus is often used to manage reproduction. The aims of this study were (1) to identify artificial inseminations (AI) that were performed following synchronization and (2) to assess the effect of synchronization on genetic parameters and evaluation of fertility traits. This study used breeding data collected between 1995 and 2021 from over 4,600 Australian dairy herds that had at least 30 matings per year. Because breeding methods were not reported, the recording pattern of breeding dates showing a large proportion of the total AI being recorded on a single date of the year served as an indicator of synchronization. First, the proportion of AI recorded on each day of the year was calculated for each herd-year. Subsequently, synchronization was defined when a herd with, for instance, only 30 matings in a year, had at least 0.20 or more AI on the same day. As the number of breedings in a herd-year increased, the threshold for classifying AI was continuously reduced from 0.20 to as low as 0.03 under the assumption that mating of many cows on a single date becomes increasingly difficult without synchronization. From the current data, we deduced that 0.11 of all AI were possibly performed following synchronization (i.e., timed AI, TAI). The proportion of AI classified as TAI increased over time and with herd size. Although the deviation from equal numbers of mating on 7 d of the week was not used for classifying AI, 0.44 of AI being categorized as TAI were performed on just 2 d of the week. When data classified as TAI were used for estimating genetic parameters and breeding values, the interval between calving and first service (CFS) was found to be the most affected trait. The phenotypic and additive genetic variance and heritability, as well as variability and reliability of estimated breeding values of bulls and cows for CFS were lower for TAI than for AI performed following detected estrus (i.e., estrus-detected AI, EAI). For calving interval, first service nonreturn rate (FNRR), and successful calving rate to first service, genetic correlations between the same trait measured in TAI and EAI were close to 1, in contrast to 0.55 for CFS. The lower genetic variances and heritabilities for FNRR and calving interval in TAI than in EAI suggests that synchronization reduces the genetic variability of fertility. In conclusion, TAI makes CFS an ineffective measure of fertility. One approach to minimize this effect on genetic evaluations is to identify TAI (using the method described for example) and then set the CFS of these cows as missing records when running multitrait genetic evaluations of fertility traits that include CFS. In the long term, the most practical and accurate way to reduce the effect of synchronization on genetic evaluations is to record TAI along with mating data.

Evaluation of the MilA ELISA for the diagnosis of herd infection with Mycoplasma bovis using bulk tank milk and estimation of the prevalence of M. bovis in Australia

Infection with Mycoplasma bovis has been identified as a growing threat in dairy industries worldwide and there is an urgent need for an inexpensive and accurate herd-level screening tool to identify herds that have been exposed to M. bovis. This study aimed to evaluate the use of the MilA ELISA for testing bulk tank milk (BTM) samples for antibodies against M. bovis and estimate a suitable cut-off and diagnostic sensitivity (DSe) and specificity (DSp) for this assay. An optimal cut-off was then applied for investigating the geographical and seasonal distribution of infection with M. bovis in Australia. A total of 5554 BTM samples from 2683 dairy herds were collected during March, August and December 2017. BTM samples were tested in the MilA ELISA and a cut-off of 29 antibody units (AU) was estimated to be optimal using Bayesian latent class analysis which makes no assumption about the true disease status of herds under investigation. At this cut-off, the DSe and DSp were estimated to be 96.6% (95% highest probability density [HPD] interval: 87.0, 99.8) and 94.2% (95% HPD: 89.9, 97.4), respectively. The diagnostic specifications were found to vary markedly with stage of the production cycle, suggesting that targeted sampling was needed to maximize accuracy. We also found distinct differences in the apparent prevalence of M. bovis in different dairying regions, as well as seasonal variation. The highest apparent prevalence of M. bovis was observed in samples collected in March and an overall drop in the proportion of positive herds was seen from March to December. Overall, this study provides insights into the dynamics of BTM antibodies against M. bovis in Australian dairy herds and how the MilA ELISA can be applied for bulk tank milk testing.

A survey of mastitis pathogens including antimicrobial susceptibility in southeastern Australian dairy herds

The objectives for this study were to (1) describe the pathogen profile in quarters from cows with clinical mastitis and in cows with subclinical mastitis in southeastern Australia; and (2) describe antimicrobial susceptibility among isolated pathogens. As a secondary objective, we aimed to compare antimicrobial resistance prevalence in pathogens isolated from clinical and subclinical mastitis samples. A convenience sample of dairy herds (n = 65) from 4 regions in southeastern Australia (Gippsland, Northern Victoria, Tasmania, Western Victoria) were invited to submit milk samples from cows with clinical and subclinical mastitis over a 14-mo period (January 2011 to March 2012). Farmers were instructed to collect aseptic quarter milk samples from the first 10 cases of clinical mastitis for each month of the study. In addition, farmers submitted composite milk samples from cows with subclinical mastitis at 1 or 2 sampling occasions during the study period. Aerobic culture and biochemical tests were used to identify isolates. Isolates were classified as susceptible, intermediate, or resistant to a panel of antimicrobial agents based on the zone of growth inhibition around antimicrobial-impregnated disks, with antimicrobial resistance (AMR) classified as nonsusceptibility by combining intermediate and resistant groups into a single category. Generalized linear mixed models were used to compare the prevalence of AMR between clinical and subclinical mastitis isolates. For clinical mastitis samples (n = 3,044), 472 samples (15.5%) were excluded for contamination. Of the remaining samples (n = 2,572), the most common results were Streptococcus uberis (39.2%), no growth (27.5%), Staphylococcus aureus (10.6%), Escherichia coli (8.4%), and Streptococcus dysgalactiae (6.4%). For subclinical mastitis samples (n = 1,072), 425 (39.6%) were excluded due to contamination. Of the remaining samples (n = 647), the most common results were no growth (29.1%), Staph. aureus (29.1%), and Strep. uberis (21.6%). The prevalence of AMR among common isolates was low for the majority of antimicrobial agents. Exploratory analysis found that the probability of Staph. aureus demonstrating resistance to penicillin was 5.16 times higher (95% confidence interval: 1.68, 15.88) in subclinical isolates relative to clinical Staph. aureus isolates. A similar association was observed for amoxicillin with subclinical Staph. aureus isolates being 4.70 times (95% confidence interval: 1.49, 14.75) more likely to be resistant than clinical Staph. aureus isolates. We concluded that the most common bacteria causing clinical mastitis in dairy herds in Australia is likely to be Strep. uberis, whereas Staph. aureus is likely to be the most common cause of subclinical mastitis. Despite decades of antimicrobial use to control these organisms, AMR appears to be uncommon.

A pilot monitoring strategy for post-partum disease in an Australian dairy herd

ABSTRACT Aims To design a monitoring strategy that could be applied to regular veterinary visits to dairy farms to assess the prevalence and association between health conditions (uterine disease, hyperketonaemia and suboptimal body condition score) when diagnosed and treated at 1–7 days post-calving (DPC) and then re-examined at 28–35 DPC. Methods This study evaluated data from 187 high-yielding dairy cows (21 primiparous, 166 multiparous) on one South Australian dairy farm on two occasions; Visit A which was 1–7 DPC and Visit B which was 28–35 DPC. On each visit, the nature of vaginal discharge, concentration of beta-hydroxybutyrate (BOH) in blood and BCS were recorded and assigned a clinical score. This was converted to a categorical outcome denoting the presence or absence of an abnormal health event, namely metritis or endometritis, hyperketonaemia (BOH concentration ≥1.2 mm/L) and suboptimal body condition score (>0.5 from optimum score). Cows with uterine disease or hyperketonaemia at either visit were treated. The prevalence of abnormal health events at each visit was determined and the association between the prevalence of disease at Visit A and Visit B (following appropriate treatment at Visit A) was measured using regression analysis. Results The prevalence of abnormal vaginal discharge, hyperketonaemia and suboptimal BCS at Visits A and B were 26%, 7%, 35% and 25%,16%, 33% respectively. A higher proportion of primiparous cows (Visit A: 0.86 (95% CI = 0.70–1.00); Visit B: 0.95 (95% CI = 0.86–1.00)) were found to have suboptimal BCS at both visits compared to multiparous cows (Visit A: 0.28 (95% CI = 0.20–0.35); Visit B: 0.24 (95% CI = 0.17–0.32)). A higher prevalence of hyperketonaemia at Visit B for multiparous compared to primiparous cows (19 (95% CI = 12–25)% vs. 0 (95% CI = 0–17) respectively) was identified. An increase in clinical discharge score at Visit A increased the odds of purulent vaginal discharge at Visit B (OR = 1.77 (95% CI = 1.31–2.40)). Failing to calve at target BCS was strongly associated with cows missing target BCS at Visit B (OR = 5.77 (95% CI = 2.35–13.11)) and for every unit increase in BCS at Visit A, BCS at Visit B increased by 0.40 (95% CI = 0.26–0.53). Conclusions and clinical relevance This study describes a pilot monitoring strategy for clinical parameters indicative of post-partum disease at 1–7 and 28–35 DPC. Determining the herd prevalence of these conditions will enable tracking of herd disease status over time. Abbreviations: BCS: Body condition score; BOH: Beta-hydroxybutyrate; DPC: Days post-calving; NEFA: Non-esterified fatty acids; SCHK: Subclinical hyperketonaemia

Breed structures in Australian dairy herds.

Breed structures of Australian dairy herds over time were described for a large subset of milk-recording herds. The focus for this study was to describe the use of crossbreeding by dairy farmers, specifically proportions of herds using crossbreeding, whether they were using two-breed or three-breed crossbreeding systems, and how herd-breed structures changed over time. The most common breed structure in Australian milk-recording herds between 2000 and 2013 was two-breed crossbreeding (39% of herd-years). The next most common breed structure was purebred (35%). Over the period studied, the proportion of herds that were purebred decreased, while the proportion of herds that were crossbreeding increased (particularly three-breed crossbreeding herds). Herd-breed structures and changes over time varied with region and with the herd's calving system. There were also considerable changes in breed structure within herds, including herds changing breed structure before reverting back to their original breed structure. These results indicate that breed structures in milk-recording dairy herds in Australia are dynamic, and that farmers have commonly employed crossbreeding strategies.

Estimating methane coefficients to predict the environmental impact of traits in the Australian dairy breeding program

The dairy industry has been scrutinized for the environmental impact associated with rearing and maintaining cattle for dairy production. There are 3 possible opportunities to reduce emissions through genetic selection: (1) a direct methane trait, (2) a reduction in replacements, and (3) an increase in productivity. Our aim was to estimate the independent effects of traits in the Australian National Breeding Objective on the gross methane production and methane intensity (EI) of the Australian dairy herd of average genetic potential. Based on similar published research, the traits determined to have an effect on emissions include production, fertility, survival, health, and feed efficiency. The independent effect of each trait on the gross emissions produced per animal due to genetic improvement and change in EI due to genetic improvement (intensity value, IV) were estimated and compared. Based on an average Australian dairy herd, the gross emissions emitted per cow per year were 4,297.86 kg of carbon dioxide equivalents (CO2-eq). The annual product output, expressed in protein equivalents (protein-eq), and EI per cow were 339.39 kg of protein-eq and 12.67 kg of CO2-eq/kg of protein-eq, respectively. Of the traits included in the National Breeding Objective, genetic progress in survival and feed saved were consistently shown to result in a favorable environmental impact. Conversely, production traits had an unfavorable environmental impact when considering gross emissions, and favorable when considering EI. Fertility had minimal impact as its effects were primarily accounted for through survival. Mastitis resistance only affected IV coefficients and to a very limited extent. These coefficients may be used in selection indexes to apply emphasis on traits based on their environmental impact, as well as applied by governments and stakeholders to track trends in industry emissions. Although initiatives are underway to develop breeding values to reduce methane by combining small methane data sets internationally, alternative options to reduce emissions by utilizing selection indexes should be further explored.

Analysis of culling reasons and age at culling in Australian dairy cattle

Context A thorough analysis of the reasons for culling was made to understand the phenotypic trend in herd life. In addition, identification of culling reasons could enable to develop a strategy for further evaluation of longevity in Australian dairy cows. Aims The aim of this study was to investigate the main causes of culling in Australian dairy herds and thereby to assess the trend of reason-specific culling over time. Methods Culling reasons in Australian dairy cattle were studied based on culling records from 1995 through 2016. A total of 2 452 124 individual cow culling observations were obtained from Datagene, Australia, of which 2 140 337 were Holstein and 311 787 were from Jersey cows. A binary logistic regression model was used to estimate effects of breed and age and the trend of a particular culling reason over time. Key results The most important culling reasons identified over the 21-year period were infertility (17.0%), mastitis (12.9%), low production (9.3%), sold for dairy purpose (6.4%) and old age (6.2%), whereas 37.4% were ‘other reasons not reported’. The average age at culling was nearly the same for Holstein (6.75 years) and Jersey (6.73 years) cows. The estimated age at culling was slightly increased for Holstein cows (by 3.7 days) and somewhat decreased for Jersey cows (by 11 days) over the last two decades. The probability of culling cows for infertility and low production was high in early parities and consistently declined as age advanced, and culling due to mastitis was higher in older cows. The trend of main culling reasons over time was evaluated, indicating that the probability of culling due to infertility has progressively increased over the years in both breeds, and culling for mastitis in Jersey cows has also increased. Culling of cows due to low production sharply decreased from 2.5 to –8% for Holstein and from 73 to 60% for Jersey cows over the 21-year period. Conclusions Culling age has changed only little in both breeds whereas culling reasons have changed over the last two decades, with low production becoming a less important reason for culling and infertility becoming more important for Holstein and Jersey breeds. Implications Due to changes of culling reasons, there could be a change in the meaning of survival over time as well. As a result, genetic correlation with survival and other traits might be changed and accuracy and bias of genetic evaluations could be affected.

Reproductive performance of cows after fixed-time artificial insemination with ovulation synchronisation and re-synchrony in southern Australian dairy herds.

To describe reproductive performance of lactating dairy cows after fixed-time artificial insemination (FTAI) with ovulation synchronisation and re-synchrony in Australian dairy herds, and to compare reproductive outcomes with those of conventional mating programs. The study was conducted in two seasonally calving dairy herds in which lactating dairy cows (n = 675) were enrolled into three treatment groups: group 1, oestrus detection and AI for 34 days followed by a natural service period; group 2, FTAI on day 1 followed by re-synchrony of all cows prior to ultrasound pregnancy diagnosis at day 31 and FTAI of cows diagnosed not pregnant at day 34, then a natural service period; group 3, FTAI on day 1 followed by oestrus detection and AI for 34 days, then a natural service period. First-service conception rate (FSCR), 6-week in-calf (6WIC) rate and proportions pregnant at the end of mating were compared using logistic regression with farm fitted as a fixed effect. Times from mating start date to conception were described using survival analysis with Kaplan-Meier failure functions. FSCRs (45.3%, 49.1% and 45.6% for groups 1, 2 and 3, respectively) and proportions pregnant at the end of mating (77.6%, 76.0% and 76.8% for groups 1, 2 and 3, respectively) were similar for all groups. The 6WIC rate in group 2 was similar to that in group 3 (70.4% vs. 67.2%; P = 0.486), but tended to be higher than in group 1 (70.4% vs. 62.0%, P = 0.066). The median days to pregnancy for cows that conceived was 1 day in groups 2 and 3 and 10 days in group 1. Mating plans that use FTAI with ovulation synchronisation and re-synchrony during the AI period can achieve comparable reproductive performance to conventional mating programs in seasonally calving dairy herds.

Short communication: Milking order consistency of dairy cows in large Australian herds

We used on-farm records from dairy infrastructure to examine the consistency of the milking order over 150 d in 5 Australian dairy herds that were milking more than 500 cows as a single group. Within a single day the difference in milking order rank position was less than 20 percentage points for 72% of cows. The correlation coefficient comparing milking rank position in the morning and afternoon was 0.72, with the position of cows at the beginning and end of the milking order being more consistent than cows toward the middle of the milking order. Over a period of 150 d, cows with a mean position in the first and last 20% of the milking order maintained their position more consistently than cows in the middle of the milking order. Milking position of cows between one month and the next was highly correlated (r = 0.88). In large herds, subpopulations of cows are regularly milked toward the beginning and the end of the milking order. It is common for cows to be collected from the paddock as a group, to wait as a group in the dairy yard to be milked, and to return individually to the paddock or feed pad immediately after they have been milked. Thus, cows milked later in the milking order are likely to be away from the paddock for several hours longer than cows milked earlier in the milking order. This may affect their welfare though differences in time available for lying down, equality of pasture eaten, and time spent standing in the dairy yard.

Identifying risk factors associated with lameness in pasture-based dairy herds

Lameness is a significant welfare concern for dairy farmers and a major contributing economic loss to the dairy industry. Information is limited on environmental and managerial risk factors associated with lameness in Australian dairy herds. The objective of this study was to explore and quantify the environmental and management risk factors associated with lameness in pasture-based dairy herds. A cross-sectional study was conducted in 63 pasture-based dairy herds between 2011 and 2014, where all lactating cows were locomotion scored (scale 1–4) during a single visit. Environmental and management variables, such as length of main track and animal handling practices, were recorded during the visit. The prevalence of lameness was measured for each farm and associated risk factors were analyzed using a Generalized Linear Model, where farm was the unit of analysis. Estimated average prevalence of lameness was 18.9% (range 5 to 44.5%). The prevalence of lameness was associated with the amount of rainfall during the 30 d before the farm assessment, smoothness of concrete surface and available space per cow in the holding yard, and length of feed-pad available per cow. Inappropriate handling of cows on the track (e.g., causing sideways pushing among cows) was also a contributing risk factor to high prevalence of lameness in these dairy herds. The findings of this study suggest that by managing several environmental and farming practices, producers can reduce the prevalence of lameness, leading to improved productivity of their herds.

Farm economic impacts of bovine Johne's disease in endemically infected Australian dairy herds.

To determine the farm economic impact of bovine Johne's disease (BJD) infection and controls in commercial Victorian dairy herds. Benefit-cost analysis of BJD and various control methods in a Victorian dairy herd. Farm losses from BJD occurred from clinical disease. Clinical cases occur on average in 5-year-old cows, resulting in losses of A$1895 in the year of culling and A$221 in the year preceding culling, giving a total loss of A$2116. Early removal also resulted in loss of future profit equating to A$375 per year. This is the annualised value of foregone future income and costs expressed as a net present value (NPV). The total loss from removal of a clinical case was estimated as A$2491. The average clinical incidence in infected dairy herds prior to entry into the Victorian Bovine Johne's Test-and-Control Program (TCP) was 1.8% and the average Victorian dairy herd size was 262 cows in 2013-14, resulting in annual losses of 4.7 clinical cases if infected and implementing no BJD control. Farm annual loss of profit was estimated as A$11,748 ($44.84 per cow/year). Control of BJD using vaccination, test-and-cull or combined approaches was economical but the cost of implementation in initial years would exceed disease costs. Vaccination-based control provided minimal long-term losses and was the most cost-effective control over a 10-year planning horizon. Endemic BJD resulted in modest but persistent losses in typical infected dairy herds. Control of disease using test-and-cull, vaccination or combined test-and-cull with vaccination was cost-effective.

A survey of Australian dairy farmers to investigate animal welfare risks associated with increasing scale of production

Although large herds (more than 500 cows) only represent 13% of Australian dairy farms, they represent more than 35% of the cows milked. A survey of Australian dairy farmers was conducted to assess relationships between herd size and known or proposed risk factors for adverse animal welfare outcomes in Australian dairy herds in relation to increasing scale of production. Responses from 863 Australian dairy farms (13% of Australian dairy farms) were received. Increasing herd size was associated with increases in stocking density, stock per labor unit, and grain fed per day—all of which could reasonably be hypothesized to increase the risk of adverse welfare outcomes unless carefully managed. However, increasing herd size was also associated with an increased likelihood of staff with formal and industry-based training qualifications. Herd size was not associated with reported increases in mastitis or lameness treatments. Some disease conditions, such as milk fever, gut problems, and down cows, were reported less in larger herds. Larger herds were more likely to have routine veterinary herd health visits, separate milking of the main herd and the sick herd, transition diets before calving, and written protocols for disease treatment. They were more likely to use monitoring systems such as electronic identification in the dairy, computerized records, daily milk yield or cell count monitoring, and pedometers or activity meters. Euthanasia methods were consistent between herds of varying sizes, and it was noted that less than 3% of farms make use of captive-bolt devices despite their effectiveness and ready availability. Increasing herd size was related to increased herd milking time, increased time away from the paddock, and increased distance walked. If the milking order of cows is consistent, this may result in reduced feed access for late-milking-order cows because of a difference in time away from the paddock. More than 95% of farmers believed that their cows were content most of the time, and cows were reported as well behaved on more than 90% of farms. Although the potential animal welfare issues appear to be different between herd sizes, no evidence existed for a relationship between herd size and adverse welfare outcomes in terms of reported disease or cow contentment levels.

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.

A study relating the composition of follicular fluid and blood plasma from individual Holstein dairy cows to the in vitro developmental competence of pooled abattoir-derived oocytes

The fertility of high-performance (high milk yield) dairy breeds such as the Holstein within the Australian dairy herd has been on the decline for the past two decades. The 12-month calving interval for pasture-based farming practices results in oocyte maturation coinciding with peak lactation, periods of negative energy balance, and energy partitioning for lactation, causing energy deficiency in some organ systems, including the reproductive system. Oocyte developmental competence (the ability to undergo successful fertilization, embryo development, and establishment of pregnancy) is intrinsically linked with the composition of follicular fluid (FF). The aim of this study was to determine if there was a relationship between the fat and carbohydrate levels in plasma and FF and the ability to support in vitro oocyte maturation (IVM). Plasma and FF were collected in vivo from eight Holstein cows between 52 and 151 days post-partum. Plasma glucose trended (P = 0.072) higher and triglyceride levels were significantly higher than in FF (P < 0.05), but there were no relationships between FF and plasma composition. Glucose FF concentration was negatively related to follicular lactate and nonesterified fatty acid (NEFA) levels and days post-partum. Conversely, FF triglyceride concentrations were positively related to FF NEFA levels and negatively related to milk fat and protein composition. Abattoir-derived cumulus–oocyte complexes were cultured in either 50% FF (FF-IVM) or 50% plasma (plasma-IVM), with on-time embryo development then assessed. Although there were no differences between animals, the blastocyst rates after FF-IVM were negatively related to plasma glucose and days post-partum and positively related to body condition score and plasma NEFA levels. In comparison to the previous studies, total NEFA levels in FF were not related to animal parameters and did not influence oocyte developmental competence in vitro. Results from this study suggest that days post-partum and body condition score influence carbohydrate metabolism within the follicular environment, and this may be attributed to the pasture-based feed system applied in the Australian dairy industry.

The effect of changing cow production and fitness traits on net income and greenhouse gas emissions from Australian dairy systems

The aim of this study was to compare the effect of changing a range of biological traits on farm net income and greenhouse gas emissions (expressed in carbon dioxide equivalents, CO2-eq.) in the Australian dairy cow population. An average cow was modeled, using breed-average information for Holsteins and Jerseys from the Australian Dairy Herd Improvement Scheme. A Markov chain approach was used to describe the steady-state herd structure, as well as estimate the CO2-eq. emissions per cow and per kilogram of milk solids. The effects of a single unit change in herd milk volume, fat and protein yields, live weight, survival, dry matter intake, somatic cell count, and calving interval were assessed. With the traits studied, the only single-unit change that would bring about a desirable increase in both net income and reduced emissions intensity per cow and per kilogram of milk solids in Australian dairy herds would be an increase in survival and reductions in milk volume, live weight, DMI, SCC, and calving interval. The models developed can be used to assess lifetime dairy system abatement options by breeding, feeding, and management. Selective breeding and appropriate management can both improve health, fertility, and feed utilization of Australian dairy systems and reduce its environmental impact.

Associations between body condition, rumen fill, diarrhoea and lameness and ruminal acidosis in Australian dairy herds

AIMS: To investigate associations between ruminal acidosis and body condition score (BCS), prevalence of poor rumen fill, diarrhoea and lameness in dairy cows in New South Wales and Victoria, Australia.METHODS: This was a cross-sectional study conducted in 100 dairy herds in five regions of Australia. Feeding practices, diets and management practices of herds were assessed. Lactating cows within herds were sampled for rumen biochemistry (n = 8 per herd) and scored for body condition, rumen fill and locomotion (n = 15 per herd). The consistency of faecal pats (n = 20 per herd) from the lactating herd was also scored. A perineal faecal staining score was given to each herd. Herds were classified as subclinically acidotic (ACID), suboptimal (SO) and non-acidotic (Normal) when ≥3/8 cows per herd were allocated to previously defined categories based on rumen biochemical measures. Multivariate logistic regression models were used to examine associations between the prevalence of conditions within a herd and explanatory variables.RESULTS: Median BCS and perineal staining score were not associated with herd category (p >0.05). In the multivariate models, herds with a high prevalence of low rumen fill scores (≤2/5) were more likely to be categorised Normal than SO with an associated increased risk of 69% (p = 0.05). Herds that had a greater prevalence of lame cows (locomotion scores ≥3/5), had 103% higher risk of being categorised as ACID than SO (p = 0.034). In a multivariate logistic regression model, with herd modelled as a random effect, an increase of 1% of pasture in the diet was associated with a 5.5% increase in risk of high faecal scores (≥4/5) indicating diarrhoea (p = 0.001).CONCLUSIONS AND CLINICAL RELEVANCE: This study confirmed that herd categories based on rumen function are associated with biological outcomes consistent with acidosis. Herds that had a higher risk of lameness also had a much higher risk of being categorised ACID than SO. Herds with a high prevalence of low rumen scores were more likely to be categorised Normal than SO. The findings indicate that differences in rumen metabolism identified for herd categories ACID, SO and Normal were associated with differences in disease risk and physiology. The study also identified an association between pasture feeding and higher faecal scores. This study suggests that there is a challenge for farmers seeking to increase milk production of cows on pasture to maintain the health of cattle.

Artificial insemination field data on the use of sexed and conventional semen in nulliparous Holstein heifers

This study investigated conception rates and other reproductive outcomes achieved with artificial insemination (AI) of nulliparous Holstein heifers using sexed and conventional semen in a commercial Australian dairy herd in central western New South Wales from January 2004 to April 2009. Retrospective data from on-farm records of 9,870 inseminations of 4,456 heifers were analyzed using several mixed models to assess the effect of temperature and humidity surrounding breeding, insemination sire, artificial insemination technician, service number, and heifer weight and age at breeding on reproductive traits (conception rates, sex ratios, gestation length, and abortion and stillbirth rates). Semen was used from 15 sexed sires and 41 unsexed sires. Sexed semen was primarily used at first and second service. Empirical conception rates of 31.6 and 39.6% were achieved for sexed and unsexed semen respectively, whereas model-based predictions were lower, at 21.3 and 32.1%. Conception rates were significantly affected by insemination sire, sex-sorting, heifer age at breeding, temperature and humidity surrounding breeding, service number, and AI technician. Sexed semen yielded 86% heifers, compared with 48% for conventional semen. Significant predictors of calf sex included semen sexing, gestation length, and insemination sire. Twinning rate was high, at 3.6% for both semen types, and gestation length and heifer weight at breeding were significant predictors of twinning. Abortion rates for sexed and unsexed conceptions were similar at 6.1 and 6.5%, respectively, and were affected by heifer age at breeding. Stillbirth rate was affected by calf sex, twinning, gestation length, and AI technician; semen sorting, age at breeding, and temperature and humidity were marginally significant predictors. No abnormalities were observed in the development of offspring, except for a marginally higher stillbirth rate for sexed calves, a finding that needs further investigation. Many variables influence the breeding outcomes associated with the application of sex-sorted sperm on commercial dairy farms. Recognition and management of these variables will increase the economic return from the investment in sex-sorted sperm.

Long-term selection strategies for complex traits using high-density genetic markers

Selection of animals for breeding ranked on estimated breeding value maximizes genetic gain in the next generation but does not necessarily maximize long-term response. An alternative method, as practiced by plant breeders, is to build a desired genotype by selection on specific loci. Maximal long-term response in animal breeding requires selection on estimated breeding values with constraints on coancestry. In this paper, we compared long-term genetic response using either a genotype building or a genomic estimated breeding value (GEBV) strategy for the Australian Selection Index (ASI), a measure of profit. First, we used real marker effects from the Australian Dairy Herd Improvement Scheme to estimate breeding values for chromosome segments (approximately 25cM long) for 2,650 Holstein bulls. Second, we selected 16 animals to be founders for a simulated breeding program where, between them, founders contain the best possible combination of 2 segments from 2 animals at each position in the genome. Third, we mated founder animals and their descendants over 30 generations with 2 breeding objectives: (1) to create a population with the “ideal genotype,” where the best 2 segments from the founders segregate at each position, or (2) obtain the highest possible response in ASI with coancestry lower than that achieved under breeding objective 1. Results show that genotype building achieved the ideal genotype for breeding objective 1 and obtained a large gain in ASI over the current population (+A$864.99). However, selection on overall GEBV had greater short-term response and almost as much long-term gain (+A$820.42). When coancestry was lowered under breeding objective 2, selection on overall GEBV achieved a higher response in ASI than the genotype building strategy. Selection on overall GEBV seems more flexible in its selection decisions and was therefore better able to precisely control coancestry while maximizing ASI. We conclude that selection on overall GEBV while minimizing average coancestry is the more practical strategy for dairy cattle where selection is for highly polygenic traits, the reproductive rate is relatively low, and there is low tolerance of coancestry. The outcome may be different for traits controlled by few loci of relatively large effects or for different species. In contrast to other simulations, our results indicate that response to selection on overall GEBV may continue for several generations. This is because long-term genetic change in complex traits requires favorable changes to allele frequencies for many loci located throughout the genome.