Pasture-based Dairy Herds Research Articles

Associations between colostrum management, passive immunity, calf-related hygiene practices, and rates of mortality in preweaning dairy calves

Calves are particularly vulnerable to health issues before weaning and experience high rates of mortality. Poor colostrum quality or substandard colostrum management, combined with poor hygiene, can increase disease susceptibility, contributing to elevated mortality rates. This study aimed to assess colostrum and calf management together with subsequent mortality rates in preweaning calves. Forty-seven Irish spring-calving, pasture-based dairy herds were enrolled in the study. To investigate whether colostrum and hygiene practices change as the calving season progresses, each farm was visited in both the first and last 6 wk of the calving season. The concentration of IgG in 250 colostrum samples and 580 calf serum samples was determined by radial immunodiffusion assay. Mean colostrum IgG concentration was 85 mg/mL, and mean calf serum IgG concentration was 30.9 and 27.1 mg/mL, respectively, in the first and last 6 wk of the calving season. Smaller herd size and younger age at sampling were associated with higher calf serum IgG concentration. Dairy breed calves were associated with higher serum IgG concentrations compared with beef breed calves; no association was detected based on sex. For feeding equipment hygiene, we assessed the presence of protein residues and found that hygiene levels tended to worsen from the first to the final 6 wk of the calving season. We found no association between feeding equipment hygiene and herd size or 28-d calf mortality rate. Colostrum and calf management practices were not associated with either calf serum IgG concentration or 28-d calf mortality rate. We found that IgG concentration in colostrum produced in Irish dairy herds was generally good, although large variation existed, emphasizing the need for assessment of colostrum before feeding. Results also suggested that hygiene practices associated with calf rearing can be improved, particularly in the latter half of the calving season.

Risk factors associated with lameness and hoof lesions in pasture-based dairy cattle systems in southeast Brazil

Cattle lameness is an important welfare concern that also has an economic impact on the dairy industry. It can be a significant problem among pasture-based herds. Our objectives were to identify cow- and herd-level factors related to lameness and hoof lesions in dairy cows grazing year-round in Minas Gerais, Brazil. We performed a cross-sectional study in 48 pasture-based dairy herds, visiting each farm in a single visit. We evaluated 2,262 cows for mobility score (0-3) and 392 cows for hoof lesions. We used a questionnaire and checklist to capture herd management data. All information obtained was used to build multivariable models. The factors associated with lameness were low body condition score, longer time spent in the corral, being kept in paddocks during the drought period, and poor hygiene. For hoof lesions, track features were the most significant factor in determining the likelihood of heel horn erosion, white line fissure, and sole hemorrhage-by more than 3 times. Different factors related to unhygienic conditions such as leg cleanliness, frequency of cleaning, and longer time spent in the corral were associated with infectious hoof lesions. Poor human-animal relationship was related to sole hemorrhage, but patient handling of cows on the track was a protective factor against interdigital hyperplasia. The results of this study suggest that improving hygiene conditions, track features, and cow handling can improve dairy cattle mobility scores in pasture-based farms under tropical conditions. These findings also represent a first step toward planning actions aimed at decreasing lameness and hoof lesions in the studied region.

Fertility of fresh and frozen sex-sorted semen in dairy cows and heifers in seasonal-calving pasture-based herds

Our objective in this study was to evaluate the reproductive performance of dairy heifers and cows inseminated with fresh or frozen sex-sorted semen (SS) in seasonal-calving pasture-based dairy herds. Ejaculates of 10 Holstein-Friesian bulls were split and processed to provide (1) fresh conventional semen at 3 × 106 sperm per straw (CONV); (2) fresh SS at 1 × 106 sperm per straw (SS-1M); (3) fresh SS semen at 2 × 106 sperm per straw (SS-2M); and (4) frozen SS at 2 × 106 sperm per straw (SS-FRZ). Generalized linear mixed models were used to evaluate the effect of semen treatment and other explanatory variables on pregnancy per artificial insemination (P/AI) in heifers (n = 3,214) and lactating cows (n = 5,457). In heifers, P/AI was greater for inseminations with CONV (60.9%) than with SS-FRZ (52.8%) but did not differ from SS-1M (54.2%) or SS-2M (53.5%). Cows inseminated with CONV had greater P/AI (48.0%) than cows inseminated with SS, irrespective of treatment (SS-1M, SS-2M, and S-FROZEN; 37.6, 38.9, and 40.6%, respectively). None of the SS treatments differed from each other with regard to P/AI in either heifers or cows. The relative performance of SS compared with CONV was also examined [i.e., relative P/AI = (SS P/AI)/(CONV P/AI) × 100]. Frozen SS achieved relative P/AI >84%. Bull affected P/AI in both heifers and cows, but no bull by semen treatment interaction was observed. In heifers, P/AI increased with increasing predicted transmitting ability for milk protein percentage. In cows, P/AI increased with increasing Economic Breeding Index (EBI) and with days in milk (DIM) at AI but decreased with increasing EBI milk subindex, parity and with DIM2. Cows in parity ≥5 had the lowest P/AI and differed from cows in parities 1, 2, or 3. Dispatch-to-AI interval of fresh semen did not affect P/AI in lactating cows, but a dispatch-to-AI interval by bull interaction was detected whereby P/AI was constant for most bulls but increased with greater dispatch-to-AI intervals for 2 bulls. In conclusion, frozen SS achieved greater P/AI relative to conventional semen than was previously reported in lactating cows. Fresh SS did not achieve greater P/AI than frozen SS, regardless of whether the sperm dose per straw was 1 × 106 or 2 × 106. A bull effect for all semen treatments, as well as a dispatch-to-AI interval by bull interaction for fresh semen, highlights the importance of using a large team of bulls for breeding management.

Associating cow characteristics with mobility scores in pasture-based dairy cows

The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.

Routine Herd Health Data as Cow-Based Risk Factors Associated with Lameness in Pasture-Based, Spring Calving Irish Dairy Cows.

Simple SummaryDairy cow lameness is considered one of the most important animal welfare and economic concerns for the dairy industry. Cow-based risk factors for lameness are not well described, especially in comparison to herd-level risk factors such as housing environment and roadway condition. This study investigates the use of routinely gathered herd health data as cow-based risk factors for lameness in dairy cows. A total of 1715 cows in 10 pasture-based Irish dairy herds were monitored for lameness during the spring and summer of 2013 and 2014 as part of the University College Dublin herd health programme. Herd health monitoring data analysed to identify potential risk factors for lameness consisted of milk production data, genetic merit information, calving details, peri-parturient disease records and body condition scores. This analysis showed a significant effect of increasing parity, lower body condition score at calving and excessive body condition loss after calving on the risk of cows being diagnosed as lame during the lactation. In conclusion, routinely gathered herd health monitoring data can be used to identify cows at increased risk of being lame and to implement lameness control strategies.Herd-level risk factors related to the cow’s environment have been associated with lameness. Uncomfortable stall surface and inadequate depth of bedding as well as abrasive alley way surface are contributing factors to increased levels of lameness. Access to pasture has been found as having a beneficial effect on cows’ locomotion. However, dairy cattle managed under grazing conditions are exposed to a different set of risk factors for lameness, mainly associated with cow tracks. Cow-based risk factors for lameness are not as clearly defined as the herd level risk factors. The objective of the present study was to use routine herd health monitoring data to identify cow-based risk factors for lameness and utilise this information to indicate cows at risk of developing lameness in the first 150 days of lactation. Lameness data were gathered from 10 pasture-based dairy herds. A total of 1715 cows were monitored, of which 1675 cows were available for analysis. Associations between lameness status and potential cow-level risk factors were determined using multivariable logistic regression. Parity 3 and 4 + cows showed odd ratios (OR’s) for lameness of 3.92 and 8.60 respectively (95% confidence interval (CI) 2.46–6.24; 5.68–13.0). Maximum loss of Body condition score (BCS) after calving exhibits OR’s for lameness of 1.49 (95% CI 1.08–2.04) if cows lost 0.5 in BCS after calving and 2.26 (95% CI 1.30–3.95) for cows losing more than 0.5 BCS. Animals calving in BCS 3.25 and ≥ 3.5 had correlating OR’s of 0.54 (95% CI 0.34–0.87) and 0.33 (95% CI 0.16–0.65) for being lame compared to cows calving with BCS ≤ 2.75. Data gathered as part of herd health monitoring can be used in conjunction with lameness records to identify shortcomings in lameness management. Findings and recommendations on lameness management can be formulated from readily available information on cow-based risk factors for lameness.

Prevalence of Shiga toxin-producing Escherichia coli in pasture-based dairy herds.

Shiga toxin-producing Escherichia coli strains (STEC) are food-borne pathogens. While E.coli O157:H7 is commonly associated with cattle, less is known about the prevalence of non-O157 STEC serogroups in bovines. This study evaluated the prevalence and virulence status of O157:H7 and six E.coli O-serogroups (O26, O103, O45, O145, O121, O111) in New Zealand dairy farms using molecular as well as culture-based methods. Fresh farm dairy effluent (FDE) (n=36) and composite calf faeces (n=12) were collected over three samplings from 12 dairy farms. All seven target serogroups were detected through molecular techniques. Of the 202 isolates which were serologically confirmed following traditional culturing and immunomagnetic separation (IMS), O103, O26, O45 and O121 were the most common serogroups, being found in 81, 47, 42 and 32% of the FDE and in 17, 33, 25 and 9% of the calf faeces respectively. The majority (157/202) of the isolates were negative for stx and eae virulence genes. The prevalence of the seven target STEC was low, and only nine O26 isolates (4%) were recovered from four of the farms. The study has highlighted the need for improving the isolation of Top 7 STEC from the stx-negative populations present in fresh dairy effluent and calf faeces. SIGNIFICANCE AND IMPACT OF THE STUDY: Shiga toxin-producing Escherichia coli (STEC) are important food-borne pathogens that can cause severe illness in humans. Cattle are asymptomatic reservoirs for STEC, and transmission to humans can be by consumption of food products or water contaminated with cattle faeces. Our study investigated the prevalence of O157:H7 and six E.coli serogroups of STEC (O26, O103, O45, O145, O121, O111) over time in the dairy reservoir and increases the knowledge and understanding of these pathogens on pasture-based farms. Such information is required to develop risk-assessment models aiming at limiting transmission of these STEC to human.

Risk factors for subclinical hypocalcaemia, and associations between subclinical hypocalcaemia and reproductive performance, in pasture-based dairy herds in New Zealand

AIMSTo estimate the herd-level prevalence of subclinical hypocalcaemia within 3 days of calving, to determine cow and herd-level risk factors for this condition, and associations with reproductive performance, in pasture-based cows in New Zealand.METHODSBetween 10 and 15 clinically healthy cows ≥3-years-old (n=1,051) were enrolled from 76 spring-calving dairy herds. Blood samples were collected from all cows on 1 or 2 days within 3 days of calving, and assayed for total concentrations of Ca in serum. Subclinical hypocalcaemia was defined as concentrations of Ca in serum ≤2.14 mmol/L, and herd-level prevalence was the percentage of sampled cows with subclinical hypocalcaemia. Breeding and pregnancy diagnosis data were obtained for each cow to calculate reproductive outcomes. Herd-level data about management practices were collected from farmers at enrolment. Associations between cow-level variables, and reproductive outcomes, and subclinical hypocalcaemia were examined using multivariable logistic regression mixed models. Associations between herd-level variables and prevalence of subclinical hypocalcaemia were examined using a multivariable linear regression model.RESULTSMean herd-level prevalence of subclinical hypocalcaemia was 52 (95% CI=49–55)%. Risk of subclinical hypocalcaemia at the cow-level was associated with an interaction between age of cow and interval from calving to sampling (p=0.03). Increasing age of cow was associated with increased risk of subclinical hypocalcaemia, and cows sampled on the day of calving had an increased risk compared with cows sampled 1 or 2 days after calving. Increased herd-level prevalence of subclinical hypocalcaemia was associated with feeding grass silage (p=0.06) or maize silage (p=0.004), and feeding increasing amounts of elemental Mg in the form of magnesium oxide (p=0.02). The mean farmer-reported herd-level prevalence of clinical hypocalcaemia was 2.9 (95% CI=2.1–3.8)%. Subclinical hypocalcaemia was not associated with any of the reproductive outcomes measured.CONCLUSIONS AND CLINICAL RELEVANCEThere was a high prevalence of subclinical hypocalcaemia in the pasture-fed, spring-calving dairy herds sampled and a large between-herd variation in prevalence. Subclinical hypocalcaemia increased with increasing age, and declined with time postpartum. Herd-level prevalence was associated with feeding grass silage and maize silage to pre-calving cows and with increasing amounts of supplemented magnesium oxide. Subclinical hypocalcaemia was not associated with reproductive outcomes.

Implications of prolonged milking time on time budgets and lying behavior of cows in large pasture-based dairy herds

In large Australian pasture-based dairy herds, it is common for the time taken to milk a herd of cows to be up to 4 h. Cows are collected from the paddock as a group, wait in turn in the dairy yard to be milked, and then return individually to the paddock or feed pad immediately after leaving the milking parlor. In such herds, we previously found a consistent milking order, resulting in some cows being regularly away from pasture for several hours per day more than others. Increased time away from pasture may affect the time budgets of cows because of decreased opportunity for grazing or lying down. Lying behavior is a high-priority behavior for cows, and the duration of lying has been used as an important measure of their welfare. We applied activity monitors for 7 d to 15 cows toward the beginning and 15 cows toward the end of the milking order in 10 dairy herds milking 500 to 730 cows as a single group to understand the effect of extra time spent in the dairy on lying behavior. Study cows typically produced 6,000 to 8,000 L in a 300-d lactation on rotary dairy platforms with 40 to 80 units, being fed 2.5 to 6 kg of grain mix in the milking parlor daily, with the rest of the diet being supplied as pasture or forage provided in the pasture or close to the exit of the dairy. Over the 10 farms, 1,948 cow-days were available for analysis. The furthest paddocks on each farm were 1.8 to 3.5 km walking distance from the dairy. A wide range of steps were taken each day, ranging from 1,705 to 15,075 (mean = 5,916). The main predictor of the number of steps was the farm on which the cows were located. Cows that spent less than an hour waiting to be milked (and would be unlikely to have their ability to lie down affected by the milking process) laid down for a mean of 9.8 h/d. Steps walked and delay in the dairy waiting to be milked were both significantly associated with lying time, but the effect was not large. A regression model accounting for the waiting time at the dairy, steps taken, cow age, and farm was used to investigate the relationship with daily lying time. For every 1,000 steps, lying time reduced by 0.49 h; however, the number of steps explained only 1% of the variation in lying time. For every hour increase in waiting time at the dairy, lying decreased by approximately 14 min, but this explained only 14% of the variation in lying. We concluded that milking time durations of 2 to 4 h, common in large Australian pasture-based dairy herds, did not significantly affect the time budget for lying of individual cows in our study herds. Whereas the effect of long milking times does not appear to be a major risk to animal welfare in terms of lying time, the effect on cow health and production warrants further investigation.

Effect of equine chorionic gonadotropin treatment during a progesterone-based timed artificial insemination program on reproductive performance in seasonal-calving lactating dairy cows

The aim of this study was to investigate the effect of progesterone (P4)-based timed artificial insemination (TAI) programs on fertility in seasonal-calving, pasture-based dairy herds. A total of 1,421 lactating dairy cows on 4 spring-calving farms were stratified based on days in milk (DIM) and parity and randomly allocated to 1 of 3 treatments: (1) control: no hormonal treatment; cows inseminated at detected estrus; (2) P4-Ovsynch: cows received a 7-d P4-releasing intravaginal device (PRID Delta; CEVA Santé Animale, Libourne, France) with 100 μg of a gonadotropin-releasing hormone (GnRH) analog (Ovarelin; CEVA Santé Animale) at PRID insertion, a 25-mg injection of PGF2α (Enzaprost; CEVA Santé Animale) at PRID removal, GnRH at 56 h after device removal and TAI 16 h later; (3) P4-Ovsynch+eCG: the same as P4-Ovsynch, but cows received 500 IU of equine chorionic gonadotropin (eCG; Syncrostim; CEVA Santé Animale) at PRID removal. At 10 d before mating start date (MSD), all cows that were ≥35 DIM were examined by transrectal ultrasound to assess presence or absence of a corpus luteum; body condition score (BCS) was also recorded. Pregnancy diagnosis was performed by transrectal ultrasonography 30 to 35 d after insemination. Overall pregnancy/AI (P/AI) was not different between groups (50.9, 49.8, and 46.3% for control, P4-Ovsynch, and P4-Ovsynch+eCG, respectively) but the 21-d pregnancy rate was increased by the use of synchronization (35.0, 51.7, and 47.2%, respectively). Compared with the control group, synchronization significantly reduced the interval from MSD to conception (34.6, 23.0, and 26.5 d, respectively) and consequently reduced the average days open (98.0, 86.0, and 89.0 d). Across all treatment groups, DIM at the start of synchronization affected P/AI (42.3, 49.5, and 53.9% for <60, 60-80, and >80 DIM, respectively), but neither parity (46.5, 50.4, and 48.4% for parity 1, 2, and ≥3, respectively) nor BCS (44.0, 49.4, and 58.6% for ≤2.50, 2.75-3.25, and ≥3.50, respectively) affected the likelihood of P/AI. Two-way interactions between treatment and DIM, parity, or BCS were not detected. In conclusion, the use of TAI accelerated pregnancy establishment in cows in a pasture-based system by reducing days open, but eCG administration at PRID removal did not affect P/AI.

The cost-benefit of genomic testing of heifers and using sexed semen in pasture-based dairy herds

Recent improvements in dairy cow fertility and female reproductive technologies offer an opportunity to apply greater selection pressure to females. This means there may be greater incentive to obtain genomic breeding values for females. We modeled the impact of changes to key parameters on the net benefit from genomic testing of heifer calves with and without usage of sexed semen. This paper builds on earlier cost-benefit studies but uses parameters relevant to pasture-based systems. A deterministic model was used to evaluate the effect on net benefit due to changes in (1) reproduction rate, (2) genomic test costs, (3) availability of parent-derived breeding values (EBVPA), and (4) replacement rate. When the use of sexed semen was included, we also considered (1) the proportion of heifers and cows mated to sexed semen, (2) decreases in conception rate in inseminations with sexed semen, and (3) the marginal return for surplus heifers. Scenarios with lower replacement rates and no availability of EBVPA had the largest net benefits. Under current Australian parameters, the net benefit of genomic testing realized over the lifetime of genotyped heifers is expected to range from A$204 to A$1,124 per 100 cows for a herd with median reproductive performance. The cost of a genomic test, a perceived barrier to many farmers, had only a small effect on net benefit. Genomic testing alone was always more profitable than using sexed semen and genomic testing together if the only benefit considered was increased genetic gain in heifer replacements. When other benefits (i.e., the higher sale price of a surplus heifer compared with a male calf) were considered, there were combinations of parameters where net benefit from using sexed semen and genomic testing was higher than the equivalent scenario with genomic testing only. Using sexed semen alongside genomic testing is most likely to be profitable when (1) used in heifers, (2) the marginal return for selling surplus heifers (sale price minus rearing costs) is greater than A$400, and (3) conception rates of no more than 10 percentage points lower than those achieved using conventional semen can be realized. Net benefit was highly dependent on the marginal return. Demonstrating that the initial investment in genomic testing can be recouped within the lifetime of the heifers tested may assist in the development of extension messages to explain the value of genomic testing females at the herd level.

Early-life events associated with first-lactation performance in pasture-based dairy herds

This was a prospective cohort study to determine how events from birth until first calving affect performance during the first lactation in pasture-based dairy herds in Victoria, Australia. Events during the preweaning (0-84 d), prepubertal (85-473 d), and postpubertal (474-804 d) periods were recorded in 6 herds, and their association with first-lactation 100-d and 250-d total milk, fat, and protein yields was quantified. Predictors of first-lactation performance included passive transfer status as a calf; season of birth; age of dam; the presence or absence of dystocia at the time of the heifer's birth; the presence or absence of preweaning diarrhea; preweaning, prepubertal, and postpubertal average daily weight gain; age at first calving; the presence or absence of periparturient disease at first calving; sex of the first-born calf; the presence or absence of a stillborn calf at the first calving; and requirement of assistance at the first calving. Lactation performance was quantified using cumulative 100-d and 250-d milk, fat, and protein yields estimated from herd recording. A multivariable linear regression model was developed for each outcome: cumulative 100-d milk, fat, and protein yield and cumulative 250-d milk, fat, and protein yield. Heifers that experienced dystocia at the time of their birth produced 7.6 kg [95% confidence interval (CI): 1.8-13.3] less fat and 4.8 kg (95% CI: 0.6-8.9) less protein at 100 d in milk in the first lactation compared with heifers that were delivered without dystocia. Heifers born in the summer and autumn produced 20 L (95% CI: 0.8-40) more milk and 20 kg (95% CI: 5.9-33) more protein at 250 d in milk in the first lactation compared with heifers born in the spring. For 100 g/d increases in prepubertal average daily gain, heifers produced an additional 182 L (95% CI: 149-216) of milk, 4.1 kg (95% CI: 2.8-5.5) of fat, and 4.0 kg (95% CI 3.1-5.0) of protein at 100 d in milk and an additional 345 L (95% CI 264-425) of milk, 6.1 kg (95% CI 3.2-9.0) of fat, and 7.5 kg (95% CI 5.3-9.7) of protein at 250 d in milk. Postpubertal average daily gain was positively associated with 100-d milk yield and 250-d milk yield and protein production. We conclude that of all the growth periods assessed in this study, events that occurred during the prepubertal period (85-473 d of age) had the greatest effect on first-lactation performance.

Calf and replacement heifer mortality from birth until weaning in pasture-based dairy herds in New Zealand

The aims of this study were to (1) estimate the perinatal (birth to 24 h) and postnatal (∼24 h to the mean weaning age of 13 wk) mortality risk in pasture-based dairy calves until weaning, and (2) identify associated risk factors in the 2015 calving season. A prospective survey of 32 seasonal calving dairy farms was undertaken. Farmers recorded (daily) the number and sex of the calves alive or dead in the paddocks where cows calved. All daily animal movements in and out of the calf rearing facilities, including death and euthanasia, and the identification of the animals (if applicable) were recorded, and a survey of the farm management practices was undertaken. Individual and farm-level risk factors for perinatal mortality were modeled separately using generalized logistic mixed models with a random effect fitted for herd. Postnatal mortality incidence risk was calculated using time at risk for each calf from 24 h of age, collapsed into weeks, and multiplying the incidence risk by the mean weaning age of the study population. Farm-level risk factors contributing to postnatal mortality in the first week of life were assessed using a multivariable logistic mixed regression model. The mean perinatal mortality risk was 5.7% (95% confidence interval 5.4 to 6.1%) with a range from 2.2 to 8.6% (18,437 calves, 30 farms). Perinatal calf mortality was greater for male relative to female calves (odds ratio 1.39; 95% confidence interval 1.22 to 1.59), calves born in the first week of the calving period in comparison to wk 2 to 11 (odds ratio 0.32 to 0.66), and those born on days with greater rainfall (odds ratio 1.01 per 1 mm increase; 95% confidence interval 1.00 to 1.02). At the farm level, perinatal mortality increased for every extra week of calving period length (odds ratio 1.12; 95% confidence interval 1.06 to 1.17). The mean postnatal mortality risk was 4.1% (95% confidence interval 3.6 to 4.6%) with a range of 0 to 11% between farms. Farm-level risk factors contributing to mortality in the first week of life included farmer-reported disease problems in calves (odds ratio 2.2; 95% confidence interval 1.62 to 2.96), or calves hand-fed colostrum in the first 12 h of life (odds ratio 1.66; 95% confidence interval 1.26 to 2.19), which was assumed to be associated with poor colostrum quality and bacterial contamination. Regional differences were also observed in both perinatal and postnatal mortality risks, indicating that weather conditions, herd size, and management variations contribute to mortality incidence. In summary, the mortality risk of perinatal calves and postnatal calves until weaning on pasture-based farms is comparable with data published from other dairying systems despite the notable management differences. Several risk factors were identified that could be managed to reduce mortality incidence of dairy calves.

Cattle Review

Introduction: This edition of Cattle Review considers three papers from Ireland on fertility in pasture-based dairy herds, farmers' views on Johne's disease control and the relationship between bovine viral diarrhoea and bovine tuberculosis.

The creation and evaluation of a model predicting the probability of conception in seasonal-calving, pasture-based dairy cows

Reproductive performance in pasture-based production systems has a fundamentally important effect on economic efficiency. The individual factors affecting the probability of submission and conception are multifaceted and have been extensively researched. The present study analyzed some of these factors in relation to service-level probability of conception in seasonal-calving pasture-based dairy cows to develop a predictive model of conception. Data relating to 2,966 services from 737 cows on 2 research farms were used for model development and data from 9 commercial dairy farms were used for model testing, comprising 4,212 services from 1,471 cows. The data spanned a 15-yr period and originated from seasonal-calving pasture-based dairy herds in Ireland. The calving season for the study herds extended from January to June, with peak calving in February and March. A base mixed-effects logistic regression model was created using a stepwise model-building strategy and incorporated parity, days in milk, interservice interval, calving difficulty, and predicted transmitting abilities for calving interval and milk production traits. To attempt to further improve the predictive capability of the model, the addition of effects that were not statistically significant was considered, resulting in a final model composed of the base model with the inclusion of BCS at service. The models' predictions were evaluated using discrimination to measure their ability to correctly classify positive and negative cases. Precision, recall, F-score, and area under the receiver operating characteristic curve (AUC) were calculated. Calibration tests measured the accuracy of the predicted probabilities. These included tests of overall goodness-of-fit, bias, and calibration error. Both models performed better than using the population average probability of conception. Neither of the models showed high levels of discrimination (base model AUC 0.61, final model AUC 0.62), possibly because of the narrow central range of conception rates in the study herds. The final model was found to reliably predict the probability of conception without bias when evaluated against the full external data set, with a mean absolute calibration error of 2.4%. The chosen model could be used to support a farmer's decision-making and in stochastic simulation of fertility in seasonal-calving pasture-based dairy cows.

The effect of cow-level factors on colostrum quality, passive immunity and health of neonatal calves in a pasture-based dairy operation

A study of 95 cows (19 primiparous and 76 multiparous) and their offspring was performed on a pasture-based dairy in the coastal region of South Africa. Collected data included weight changes during the dry period, colostrum immunoglobulin G (IgG) and calf serum IgG at 24–48 h after birth. Colostrum and serum IgG concentrations were measured using radial immunodiffusion and colostrum was regarded as having adequate IgG concentration if the amount was ≥50 g/L. Calf serum IgG concentration of ≥10 g/L was considered an adequate transfer of passive immunity. The median (range in parentheses) colostrum quality for cows with weight loss during the dry period was 23.1 g/L (9.0, 108.1) compared with 61.9 g/L (10.9, 200.0) in cows without weight loss. The median serum IgG of calves from cows with weight loss was 9.9 g/L (0.5, 44.6) compared with 14.0 g/L (0.5, 76.3) in calves from cows that did not lose weight during the dry period. Cows experiencing weight loss were four times more likely to have colostrum with lower concentrations of IgG (OR = 0.25; 95% CI, 0.07–0.88; P = 0.030). Lactation number was also significantly associated with colostrum IgG concentration (P &lt; 0.001), with younger cows tending to have higher IgG concentrations. Failure of passive transfer did not have a significant effect on any calf-health or production variables measured in the study. The effect of dry-cow feeding on colostrum IgG concentration is poorly understood and inadequate pasture management could have an impact on colostrum quality in pasture-based dairy herds.

0615 Survey of temporal variation in pasture mineral concentrations and total dietary mineral intake in pasture-based dairy herds

0615 Survey of temporal variation in pasture mineral concentrations and total dietary mineral intake in pasture-based dairy herds

An automatic model configuration and optimization system for milk production forecasting

The objective of this study was to develop and implement the Milk Production Forecast Optimization System (MPFOS) for the purpose of comparing the effectiveness of multiple herd milk yield prediction models for an Irish pasture-based dairy herd. The MPFOS was populated by nine milk production models that were categorized into three types: curve fitting, regression and auto-regressive models. The Adaptive Stratified Sampling Approach (ASSA) was introduced for data filtering, processing and for randomly selecting each member of the 100 cow sample herd. The MPFOS calculated optimal model parameters, statistical analysis and milk production forecasts for each chosen model using input data combinations based on animal, herd and milk production records. The model evaluations were based on historical milk production data between the years 2004 and 2009 from dairy farms in the south of Ireland situated in close proximity. Milk yield records from 2004 to 2008 were used for model training, whereas the milk production records for 2009 were set for model evaluation and validation. The ASSA randomly selected the representative herd population based on the required criteria. The MPFOS automatically generated the optimal configuration for each of the nine milk production forecast models and benchmarked their performance over a short, medium and long term prediction horizon. The Root Mean Square Error (RMSE) value of the nine prediction models varied substantially (from 68.5kg to 210.4kg per day). The surface fitting model performed better (10% in RPE and R2) than the dynamic NARX model for the same prediction horizon (365-day and 30-day). However, the NARX model provided more accurate results for shorter (10-day) prediction horizons. The MPFOS found the most accurate model based on prediction horizon length and on number of input parameters. The results of this study demonstrate the effectiveness of the MPFOS as a model configuration and comparison tool. The MPFOS may also be employed for selecting the optimal milk production forecast model for a specific application.

Shorter sampling periods and accurate estimates of milk volume and components are possible for pasture based dairy herds milked with automated milking systems.

Dairy cows grazing pasture and milked using automated milking systems (AMS) have lower milking frequencies than indoor fed cows milked using AMS. Therefore, milk recording intervals used for herd testing indoor fed cows may not be suitable for cows on pasture based farms. We hypothesised that accurate standardised 24 h estimates could be determined for AMS herds with milk recording intervals of less than the Gold Standard (48 hs), but that the optimum milk recording interval would depend on the herd average for milking frequency. The Gold Standard protocol was applied on five commercial dairy farms with AMS, between December 2011 and February 2013. From 12 milk recording test periods, involving 2211 cow-test days and 8049 cow milkings, standardised 24 h estimates for milk volume and milk composition were calculated for the Gold Standard protocol and compared with those collected during nine alternative sampling scenarios, including six shorter sampling periods and three in which a fixed number of milk samples per cow were collected. Results infer a 48 h milk recording protocol is unnecessarily long for collecting accurate estimates during milk recording on pasture based AMS farms. Collection of two milk samples only per cow was optimal in terms of high concordance correlation coefficients for milk volume and components and a low proportion of missed cow-test days. Further research is required to determine the effects of diurnal variations in milk composition on standardised 24 h estimates for milk volume and components, before a protocol based on a fixed number of samples could be considered. Based on the results of this study New Zealand have adopted a split protocol for herd testing based on the average milking frequency for the herd (NZ Herd Test Standard 8100:2015).

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.

Non-return rate as a predictor of calving rate in seasonal-calving pasture-based dairy herds

Non-return rate as a predictor of calving rate in seasonal-calving pasture-based dairy herds