In vitro calibration and in vivo validation of phenomenological corrosion models for resorbable magnesium-based orthopaedic implants.

Metallic bioresorbable orthopaedic implants based on magnesium, iron and zinc-based alloys that provide rigid internal fixation without foreign-body complications associated with permanent implants have great potential as next-generation orthopaedic devices. Magnesium (Mg) based alloys exhibit excellent biocompatibility. However, the mechanical performance of such implants for orthopaedic applications is contingent on limiting the rate of corrosion in vivo throughout the bone healing process. Additionally, the surgical procedure for the implantation of internal bone fixation devices may impart plastic deformation to the device, potentially altering the corrosion rate of the device. The primary objective of this study was to develop a computer-based model for predicting the in vivo corrosion behaviour of implants manufactured from a Mg-1Zn-0.25Ca ternary alloy (ZX10). The proposed corrosion model was calibrated with an extensive range of mechanical and in vitro corrosion testing. Finally, the model was validated by comparing the in vivo corrosion performance of the implants during preliminary animal testing with the corrosion performance predicted by the model. The proposed model accurately predicts the in vitro corrosion rate, while overestimating the in vivo corrosion rate of ZX10 implants. Overall, the model provides a "first-line of design" for the development of new bioresorbable Mg-based orthopaedic devices. STATEMENT OF SIGNIFICANCE: Biodegradable metallic orthopaedic implant devices have emerged as a potential alternative to permanent implants, although successful adoption is contingent on achieving an acceptable degradation profile. A reliable computational method for accurately estimating the rate of biodegradation in vivo would greatly accelerate the development of resorbable orthopaedic implants by highlighting the potential risk of premature implant failure at an early stage of the device development. Phenomenological corrosion modelling approach is a promising computational tool for predicting the biodegradation of implants. However, the validity of the models for predicting the in vivo biodegradation of Mg alloys is yet to be determined. Present study investigates the validity of the phenomenological modelling approach for simulating the biodegradation of resorbable metallic orthopaedic implants by using a porcine model that targets craniofacial applications.

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, there is very little 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 this varied considerably between farms. On farms with BDD, M4 lesions accounted for 70 to 100% of all lesions (interquartile range = 95.1 to 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 statistically 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, though 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 impact 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.

Comparison of four clinical sample types for detection and investigation of PCV3 prevalence in the pig farrowing room.

Porcine circovirus type 3 (PCV3) is a newly described circovirus that has been identified in pig populations across the globe. The virus is associated with multiple diseases including reproductive and systemic diseases. As effective vaccines are lacking, surveillance is crucial for PCV3 control, but there are currently, few side-by-side comparisons of the efficacy of different samples for the detection of PCV3. This study collected four sample types, including colostrum, udder skin wipes, placental umbilical cord blood, and processing fluid from 134 litters in a sow farm from July to September 2021 for PCV3 detection based on quantitative PCR tests. Udder skin wipes showed the highest detection rates (76.9%), while 71.6% of the processing fluid, 49.3% of the placental umbilical cord, and 29.1% of the colostrum samples were positive. Logistic regression analysis suggested that the detection rates of udder skin wipes and processing fluid were similar (odds ratio for processing fluid vs udder skin wipes was 0.76, 95% confidence interval (CI) 0.43-1.32), but the two tests were probably not identifying the same population as infected, as the agreement between the samples was only moderate (Gwet's AC1: 0.65). In this study, we were able to demonstrate that PCV3 was present in the farrowing room throughout the period from birth to weaning using udder skin wipes, although viral load decreased over time. The odds of PCV3 detection in colostrum from 2-parity sows was three times higher (95% CI 1.4-6.8) than that of primiparous sows, while the odds of PCV3 detection in sows with mummified fetuses was 2.7 times higher (95% CI 1.1-6.6) than sows with no mummified fetuses. In conclusion, these results indicate that udder skin wipes have high detection rates in infected animals over the whole period from birth to weaning and would thus be suitable samples for PCV3 surveillance in the farrowing rooms.

Prevalence and genetic diversity of Theileria equi from horses in Xinjiang Uygur Autonomous region, China.

Theileria equi is a tick-borne intracellular apicomplexan protozoan parasite that causes equine theileriosis (ET). ET is an economically important disease with a worldwide distribution that significantly impacts international horse movement. Horses are an essential part of the economy in Xinjiang which is home to ∼10% of all the horses in China. However, there is very limited information on the prevalence and genetic complexity of T. equi in this region. Blood samples from 302 horses were collected from May to September 2021 in Ili, Xinjiang, and subjected to PCR examination for the presence of T. equi. In addition, a Bayesian latent class model was employed to estimate the true prevalence of T. equi, and a phylogenetic analysis was carried out based on the 18S rRNA gene of T. equi isolates. Seventy-two horses (23.8%) were PCR positive. After accounting for the imperfect PCR test using a Bayesian latent class model, the estimated true prevalence differed considerably between age groups, being 10.8% (95%CrI: 5.8% - 17.9%) in ≤ 3-year-old horses and 35.7% (95%CrI: 28.1% - 44.5%) in horses that were > 3 year-old. All T. equi isolates had their 18S rRNA gene (430bp) sequenced and analyzed in order to identify whether there were multiple genotypes of T. equi in the Xinjiang horse population. All of the 18S rRNA genes clustered into one phylogenetic group, clade E, which is thus probably the dominant genotype of T. equi in Xinjiang, China. To summarize, we monitored the prevalence of T. equi in horses of Xinjiang, China, with a focus on the association between age and the occurrence of T. equi by Bayesian modelling, accompanied by the genotyping of T. equi isolates. Obtaining the information on genotypes and age structure is significant in monitoring the spread of T. equi and studying the factors responsible for the distribution.

Assessing Alternatives to Locomotion Scoring for Detecting Lameness in Dairy Cattle in Tanzania: Infrared Thermography.

Lameness detection is a significant challenge. Locomotion scoring (LS), the most widely used system for detecting lameness, has several limitations, including its subjective nature and the existence of multiple systems, each with its own advantages and disadvantages. Therefore, this study aimed to evaluate whether the foot skin temperature (FST) of hind limbs, as measured using infrared thermography (IRT), could potentially be used as an alternative on Tanzanian dairy farms. Each of the three study farms were visited twice during the afternoon milking on consecutive days, with a total of 170 cows assessed. DairyNZ LS (4-point scale (0-3)) was undertaken on the first day as the cows exited the milking parlour after being milked, while on the following day, the plantar aspect of the hind limbs of the cows was thermally imaged while they were standing in the milking parlour, using a handheld T650sc forward-looking infrared camera. Mean FST was higher for cows with a locomotion score of 1 than those with a score of 0; higher for cows with a locomotion score of 2 than those with a score of 1; and higher for cows with a locomotion score of 3 than those with a score of 2, with each one-unit locomotion score increase being associated with a 0.57 °C increase in mean temperature across all zones. The optimal cut-off point of 38.0 °C for mean temperature across all zones was identified using a receiver operator characteristic curve. This cut-off point had a sensitivity of 73.2% and a specificity of 86.0% for distinguishing cows with a locomotion score ≥ 2 (clinical lameness). The prevalence of clinical lameness across all three farms was 33%, which meant that only 72% of cows with a mean FST across all zones ≥ 38.0 °C had been identified as clinically lame using LS. This study confirmed that IRT has the potential to be used to detect lameness on Tanzanian dairy farms. However, before it can be widely used, improvements in accuracy, especially specificity, are needed, as are reductions in equipment (IR camera) costs.

Genomic epidemiology of bovine mastitis-causing Staphylococcus aureus in New Zealand.

We analysed the genomes of 188 bovine-mastitis-causing S. aureus isolates obtained over a 17-year period from more than 65 dairy farms across New Zealand. The analysis revealed a unique pattern of dominance over the entire period of study, of clonal complex 1, sequence type 1 (CC1/ST1), which accounted for ∼75% of the isolates. CC1/ST1 was also the commonest lineage infecting humans in New Zealand in the same period, but most bovine CC1/ST1 analysed in this study carried the genes coding for the bovine-adaptive bicomponent leucocidin lukF and lukM and lacked the corresponding human-adaptive lukF-PV and lukS-PV genes. Typical ruminant-associated lineages, such as ST97, ST151 and CC133 were also observed. Cluster analyses of the core and accessory genomes revealed genomic segregations according to the CCs, but lack of segregation based on the geographical location or collection year, suggesting a stable population in space and time. To our knowledge, this is the first identification of genomic markers of host adaptation to cattle in S. aureus CC1/ST1, a lineage commonly associated with humans, worldwide. The temporal clonal stability observed would enable the development of a S. aureus vaccine for New Zealand cattle, which is unlikely to undergo substantial reduction of efficacy due to clonal drifts or shifts.

Evaluating the Effect of Preventative Trimming on Distance from the Sole Surface to the Distal Phalanx Using Ultrasonography for Lameness Prevention in Pasture-Based Dairy Cows.

One common management strategy used to reduce the risk of lameness is prophylactic claw trimming. However, in pasture-based cattle, there is a concern that the immediate reduction in sole thickness resulting from sole trimming will lead to medium-to-long-term reductions in sole thickness, which may increase the risk of lameness. Nevertheless, there is a lack of data on sole thickness and trimming in pasture-based cows. Therefore, the aim of this study was to evaluate the effect of trimming on sole thickness over the medium-to-long term, as estimated using the ultrasound-measured distance from the external claw sole surface to the distal phalanx (DDP) and of DDP on the interval between calving and increased locomotion scores. A total of 38 cows were randomly selected from a 940-cow spring calving dairy farm in the North Island of New Zealand; 18 were allocated to the ultrasound hoof-trimming group and 20 were allocated to the ultrasound non-trimming group. Starting in May 2018, at the end of the 2017/18 lactation, ultrasound measurements of DDP of the right hind hoof were made on all 38 cows, and the hindlimbs of the trimming group cows were trimmed by an experienced professional hoof trimmer using the five-step Dutch method. This was repeated in October 2018 (early lactation) and May 2019 (late lactation). After calving, the cows were locomotion scored fortnightly until the end of lactation using the 4-point (0-3) scale DairyNZ system. The effect of DDP on the interval between calving and the first locomotion scores ≥1 and ≥2 was assessed using Cox proportional hazards models, and the association between trimming and DDP was explored using linear mixed models. The results suggest that DDP has no effect on the time to locomotion scores ≥1 or ≥2, although the wide confidence intervals of the latter suggest that more data are needed before any definitive conclusions can be drawn. The study failed to find any clinically important impact of prophylactic trimming on DDP. This is likely related to the finding that cows with the highest DDP at the first trimming were identified by the hoof trimmer as those needing the most trimming. The results of this study thus suggest that if the Dutch five-step method is properly applied, it is unlikely to affect sole thickness over the short-to-medium term in pasture-based cattle.

Incidence of Inadequate Transfer of Passive Immunity in Dairy Heifer Calves in South Australia.

The objective of this observational study was to estimate the incidence of inadequate transfer of passive immunity (ITPI) on five pasture-based dairy farms in South Australia. Heifer calf uptake of colostrum was evaluated within the first 1−7 days of age (n = 2638) using a digital refractometer to estimate each calf's serum total protein concentration, as an indicator of colostrum uptake. Results of <51 g/L indicated inadequate transfer of passive immunity (ITPI). The data showed that the incidence of ITPI on the farms was 6.5%, 31.3%, 48.8%, 49.7% and 52.4%. The incidence of ITPI was calculated in relation to the age of the calf at testing and the breed of calf, and no significant differences were found. A significant difference was found in the incidence of ITPI when comparing the calf's first feed after separation from the dam (colostrum versus a colostrum-transition milk mixture). The farm with the lowest incidence of ITPI collected calves twice a day, measured colostrum quality on farm with a Brix refractometer and ensured that each calf received an appropriate amount of high-quality colostrum soon after collection. Further studies are required to establish the risk factors of ITPI in South Australian dairy heifers.

A Nutritional Investigation of Major Feed Types and Feed Rations Used in Medium-Scale Dairy Production Systems in Sri Lanka.

In this paper, the nutritional quality, digestibility, and chemical composition of major feed types as well as the use of those feeds in rations by medium-scale dairy farmers in the Kurunegala district of Sri Lanka were studied. Nine dairy farms were visited fortnightly over a five-month period to identify the feeds that were commonly used. All farms operated under a stall-feeding system in which a manually mixed ration (MMR) was fed 2-3 times daily. Four forages were identified: Guinea grass ecotype A (Panicum maximum), called Guinea grass; Hybrid Napier CO-3 (Pennisetum purpureum × Pennisetum americanum), called CO-3 grass; Gliricidia (Gliricidia sepium); and maize stover (Zea mays L.), along with three other supplementary feeds (maize silage, barley distillers' by-products, and commercially formulated cattle feed). These feeds were subjected to proximate analysis and in vitro digestibility analysis. The metabolisable energy (ME) of the forages ranged from 7.5-10.0 MJ/kg dry matter (DM), with the ME of Guinea grass and CO-3 grass (7.5 and 8.0 MJ/kg DM, respectively) being lower than that of Gliricidia (10.0 MJ/kg DM). The neutral detergent fibre (NDF) concentration of both Guinea grass and CO-3 grass (both 72% DM) was much higher than that of Gliricidia (47% DM). Crude protein (CP) was higher in Gliricidia (17.5% DM) than in either Guinea grass or CO-3 grass (8.0 and 8.8% DM, respectively). The ME of the supplementary feeds varied between 11.0 and 12.8 MJ/kg DM, while CP varied between 15.0 and 24.0% DM. The daily ME intake of cows was consistently 10% lower than their calculated daily energy requirement; for dry cows, the mean intake was 90 MJ/cow/day supplied vs. 101 MJ required, while for cows in early lactation the mean intake was 126 MJ/cow/day supplied vs. 140 MJ required. The average CP intake of lactating cows (13.5% DM) was inadequate (requirements: 16 to 17.5% DM), while the average CP intake of dry cows (11.8% DM) was satisfactory (requirements: 11 to 12% DM). The current study shows that the majority of the feed types used in these medium-scale dairy farms provide insufficient ME or CP to meet the nutritional requirements of either lactating or dry cows irrespective of the quantity of feed provided.

Practicability of a Time-Limited Welfare Assessment Protocol for Pasture-Based Dairy Farms, and a Preliminary Assessment of Welfare Outcome Thresholds.

This study assessed a new time-limited protocol developed for pasture-based cows across 23 dairy farms. The process started prior to milking with a questionnaire, followed by an assessment of resources (16 farms only) and behavioural observation of cows at pasture. Remaining animal-based measures were assessed during milking, usually by two assessors (one parlour based and one outside). The protocol proved to be practical and feasible with limited changes needed, except for the assessment of water availability and behaviour. As most cows could access only one water trough, distance between troughs was not a measure of water availability, while the observation of a large numbers of cows at pasture for 30 min resulted in few observations and an uncertain denominator (effective number of observed cows). Further research is needed to determine the best way of assessing water availability and cow behaviour in a time-limited assessment of pasture-based cows. Three animal-based measures (broken tails, dirtiness, and coughing) had mean values higher than the author-determined acceptable thresholds, while <50% of farms met trough cleanliness and track condition targets, and none met the criteria for shelter and shade. This was a sample of farms based on convenience, so more data are required to establish the representativeness of these results. Such testing should involve assessment of the repeatability and reliability of the measures in our protocol.

The Influence of Rotational Length, along with Pre- and Post-Grazing Measures on Nutritional Composition of Pasture during Winter and Spring on New Zealand Dairy Farms.

The quality of ryegrass−clover pasture was investigated between August (winter: start of calving) and November (spring: end of breeding) on pasture-based dairy farms (>85% of total feed from pasture) that had short (n = 2, Farms A and B; winter ~30 days, spring ~20−25 days) or long (n = 2, Farms C and D; winter ~35 days, spring ~25−30 days) grazing rotations to determine whether quality was affected by grazing rotation length (RT). Weekly assessments of pasture growth and herbage quality were made using a standardised electronic rising plate meter, and near-infrared spectroscopy, respectively. Data were subjected to repeated measure mixed model analysis, in which herbage quality was the outcome variable. The highest pre-grazing dry matter (PGDM) and height, post-grazing dry matter (DM) and height, and number of live leaves per tiller (leaf regrowth stage, LS) were present in late spring. Neutral detergent fibre (NDF), acid detergent fibre (ADF), metabolisable energy (ME), and organic matter digestibility (OMD) were positively correlated to each other (r2 ≥ 0.8) whilst ADF and lipid, and ADF and OMD were negatively correlated (r2 ≥ −0.8; p < 0.01). Metabolisable energy content was negatively correlated with ADF and NDF (r2 = −0.7, −0.8, respectively), and was inversely related to PGDM. Metabolisable energy was higher (p < 0.05) in farms with shorter (overall mean: 11.2 MJ/kg DM) than longer (10.9 MJ/kg DM) RT. Crude protein was also inversely related to PGDM and was higher with shorter (23.2% DM) than longer (18.3% DM; p < 0.05) RT. Pre-grazing DM affected the amount of pasture that was grazed and, hence, the amount of DM remaining after grazing (post-grazing DM or residual), so that PGDM was correlated with post-grazing height and residual DM (r2 = 0.88 and 0.51, respectively; both p < 0.001). In conclusion, RT, LS, and PGDM during winter and spring influenced the herbage quality, therefore, better management of pastures may enhance the productivity of dairy cows.

Evaluating Alternatives to Locomotion Scoring for Detecting Lameness in Pasture-Based Dairy Cattle in New Zealand: In-Parlour Scoring.

Earlier detection followed by efficient treatment can reduce the impact of lameness. Currently, locomotion scoring (LS) is the most widely used method of early detection but has significant limitations in pasture-based cattle and is not commonly used routinely in New Zealand. Scoring in the milking parlour may be more achievable, so this study compared an in-parlour scoring (IPS) technique with LS in pasture-based dairy cows. For nine months on two dairy farms, whole herd LS (4-point 0−3 scale) was followed 24 h later by IPS, with cows being milked. Observed for shifting weight, abnormal weight distribution, swollen heel or hock joint, and overgrown hoof. Every third cow was scored. Sensitivity and specificity of individual IPS indicators and one or more, two or more or three positive indicators for detecting cows with locomotion scores ≥ 2 were calculated. Using a threshold of two or more positive indicators were optimal (sensitivity > 92% and specificity > 98%). Utilising the IPS indicators, a decision tree machine learning procedure classified cows with locomotion score class ≥2 with a true positive rate of 75% and a false positive rate of 0.2%. IPS has the potential to be an alternative to LS on pasture-based dairy farms.

Performance of the StaphGold ELISA test in determining subclinical Staphylococcus aureus infections in dairy cows using a Gaussian mixture model.

BACKGROUND: A novel ELISA test has been developed to detect antigen-specific IgG in early and late lactation cows in New Zealand. OBJECTIVES: This study was to evaluate the discriminatory ability of the ELISA based on the detection of S. aureus-specific IgG as a screening test. METHODS: The ELISA was used for the composite milk samples taken during routine herd testing in 2018-2019 milking season in New Zealand. In the absence of a gold standard test, the diagnostic specificity and sensitivity was estimated using a Gaussian mixture model. RESULTS: The ELISA test had a high accuracy (AUC = 0.98) to detect antigen-specific IgG in early and late lactation cows with high somatic cell count due to either subsequent to or contemporaneous with the S. aureus invasion. Using an S/P ratio = 0.3 as the cut-off value, the ELISA test has sensitivity of 0.9 and specificity of 0.95, while the sensitivity increased to 0.94 at a cost of a decreased specificity of 0.9 at a lower cut-off value 0.26. CONCLUSIONS: The integration of the ELISA test as a screening tool into specific control programs may be useful to reduce the spread of S. aureus infections, to aid with treatment decisions, and to establish a correct milking order.

Keeping continuous diagnostic data continuous: Application of Bayesian latent class models in veterinary research.

Bayesian finite mixture models, frequently referred to as Bayesian latent class models have become increasingly common for diagnostic test data in the absence of a gold standard test. Most Bayesian analyses in the veterinary literature have dealt with a dichotomised diagnostic outcome. The use of Bayesian finite mixture models for continuous test outcomes, such as sample to positive (S/P) ratios produced by an ELISA, is much less common, despite continuous models taking advantage of all of the information captured in the test outcome. This paper revisits the idea of the Bayesian finite mixture model and provides a practical guide for researchers who would like to use this approach for modelling continuous diagnostic outcomes as it preserves all information from the observed data. Synthetic datasets and a dataset from literature were analysed to illustrate that a mixture model with continuous diagnostic outcomes can be used to estimate true prevalence and to evaluate test sensitivity and specificity. In addition, directly modelling the continuous test outcomes rather than dichotomising them, means that optimal cut-offs can be defined based on the test purpose rather than being determined before testing. Moreover, as animals with higher scores are more likely to be infected, using continuous data allows test interpretation to be made at the individual animal level. In contrast, dichotomization treats all animals above a cut-off as having the same infection risk. This study demonstrates that dichotomisation is not a 'must' when using Bayesian latent class analysis for diagnostic test data, and suggests that latent class analysis using continuous test outcomes should be favoured when evaluating veterinary diagnostic tests producing continuous outcomes.

Evaluating Alternatives to Locomotion Scoring for Lameness Detection in Pasture-Based Dairy Cows in New Zealand: Infra-Red Thermography.

Lameness in cattle is a complex condition with huge impacts on welfare, and its detection is challenging for the dairy industry. The present study aimed to evaluate the association between foot skin temperature (FST) measured using infrared thermography (IRT) and locomotion scoring (LS) in dairy cattle kept at pasture. Data were collected from a 940-cow dairy farm in New Zealand. Cows were observed at two consecutive afternoon milkings where LS was undertaken at the first milking (4-point scale (0-3), DairyNZ). The next day, cows were thermally imaged from the plantar aspect of the hind feet using a handheld T650sc forward-looking infrared camera (IRT). The association between FST and locomotion score was analysed using a generalised linear model with an identity link function and robust estimators. ROC curves were performed to determine optimal threshold temperature cut-off values by maximising sensitivity and specificity for detecting locomotion score ≥ 2. There was a linear association between individual locomotion scores and FST. For mean temperature (MT), each one-unit locomotion score increase was associated with a 0.944 °C rise in MT. Using MT at a cut-off point of 34.5 °C produced a sensitivity of 80.0% and a specificity of 92.4% for identifying cows with a locomotion score ≥ 2 (lame). Thus, IRT has a substantial potential to be used on-farm for lameness detection. However, automation of the process will likely be necessary for IRT to be used without interfering with farm operations.

Effect of Divergent Feeding Regimes During Early Life on the Rumen Microbiota in Calves.

The objective of this study was to determine whether divergent feeding regimes during the first 41 weeks of the life of a calf are associated with long-term changes in the rumen microbiota and the associated fermentation end-products. Twenty-four calves (9 ± 5 days of age) were arranged in a 2 × 2 factorial design with two divergent treatments across three dietary phases. In phase 1 (P01), calves were offered a low-milk volume/concentrate starter diet with early weaning (CO) or high-milk volume/pasture diet and late weaning (FO). In phase 2 (P02), calves from both groups were randomly allocated to either high-quality (HQ) or low-quality (LQ) pasture grazing groups. In phase 3 (P03), calves were randomly allocated to one of two grazing groups and offered the same pasture-only diet. During each dietary phase, methane (CH4) and hydrogen (H2) emissions and dry matter intake (DMI) were measured in respiration chambers, and rumen samples for the evaluation of microbiota and short-chain fatty acid (SCFA) characterizations were collected. In P01, CO calves had a higher solid feed intake but a lower CH4 yield (yCH4) and acetate:propionate ratio (A:P) compared with FO calves. The ruminal bacterial community had lower proportions of cellulolytic bacteria in CO than FO calves. The archaeal community was dominated by Methanobrevibacter boviskoreani in CO calves and by Mbb. gottschalkii in FO calves. These differences, however, did not persist into P02. Calves offered HQ pastures had greater DMI and lower A:P ratio than calves offered LQ pastures, but yCH4 was similar between groups. The cellulolytic bacteria had lower proportions in HQ than LQ calves. In all groups, the archaeal community was dominated by Mbb. gottschalkii. No treatment interactions were observed in P02. In P03, all calves had similar DMI, CH4 and H2 emissions, SCFA proportions, and microbial compositions, and no interactions with previous treatments were observed. These results indicate that the rumen microbiota and associated fermentation end-products are driven by the diet consumed at the time of sampling and that previous dietary interventions do not lead to a detectable long-term microbial imprint or changes in rumen function.

Effect of Methane Inhibitors on Ruminal Microbiota During Early Life and Its Relationship With Ruminal Metabolism and Growth in Calves.

The present study aimed to determine whether dietary supplementation with methanogen inhibitors during early life may lead to an imprint on the rumen microbial community and change the rumen function and performance of calves to 49-weeks of rearing. Twenty-four 4-day-old Friesian x Jersey cross calves were randomly assigned into a control and a treatment group. Treated calves were fed a combination of chloroform (CF) and 9,10-anthraquinone (AQ) in the solid diets during the first 12 weeks of rearing. Afterward, calves were grouped by treatments until week 14, and then managed as a single group on pasture. Solid diets and water were offered ad libitum. Methane measurements, and sample collections for rumen metabolite and microbial community composition were carried out at the end of weeks 2, 4, 6, 8, 10, 14, 24 and 49. Animal growth and dry matter intake (DMI) were regularly monitored over the duration of the experiment. Methane emissions decreased up to 90% whilst hydrogen emissions increased in treated compared to control calves, but only for up to 2 weeks after treatment cessation. The near complete methane inhibition did not affect calves' DMI and growth. The acetate:propionate ratio decreased in treated compared to control calves during the first 14 weeks but was similar at weeks 24 and 49. The proportions of Methanobrevibacter and Methanosphaera decreased in treated compared to control calves during the first 14 weeks; however, at week 24 and 49 the archaea community was similar between groups. Bacterial proportions at the phylum level and the abundant bacterial genera were similar between treatment groups. In summary, methane inhibition increased hydrogen emissions, altered the methanogen community and changed the rumen metabolite profile without major effects on the bacterial community composition. This indicated that the main response of the bacterial community was not a change in composition but rather a change in metabolic pathways. Furthermore, once methane inhibition ceased the methanogen community, rumen metabolites and hydrogen emissions became similar between treatment groups, indicating that perhaps using the treatments tested in this study, it is not possible to imprint a low methane microbiota into the rumen in the solid feed of pre-weaned calves.

Risk Factors Associated With Mastitis in Smallholder Dairy Farms in Southeast Brazil.

The aim of this study was to investigate the potential risk factors for clinical and subclinical mastitis in smallholder dairy farms in Brazil. A prospective, repeated cross-sectional study was carried out between May 2018 and June 2019 on 10 smallholder dairy farms. Potential risk factors for subclinical and clinical mastitis at the herd and cow level were recorded through interviewing the owner and by observation. A combination of clinical udder examination and the Tamis (screened mug with a dark base) test (Tadabras Indústria e Comércio de Produtos Agrovetereinário LTDA, Bragrança Paulista, SP, Brazil) were applied to observe clinical mastitis, and the California Mastitis Test (Tadabras Indústria e Comércio de Produtos Agrovetereinário LTDA, Bragrança Paulista, SP, Brazil) was used to determine subclinical mastitis. A total of 4567 quarters were tested, 107 (2.3%) had clinical mastitis, while 1519 (33.2%) had subclinical mastitis. At the cow level, clinical mastitis risk was highest in mid-lactation (50-150 days in milk) with OR 2.62 with 95% confidence interval (CI) of 1.03-6.67, while subclinical mastitis was highest in late lactation (> 150 days in milk) with OR 2.74 (95% CI 2.05-3.63) and lower in primiparous (OR 0.54, 95% CI 0.41-0.71) than multiparous cows. At the herd level, using dry-cow treatment (OR 4.23, 95% CI 1.42-12.62) was associated with an increased risk of clinical mastitis. Milking clinical (OR 0.37, 95% CI 0.24-0.56) and subclinical cases last (OR 0.21, 95% CI 0.09-0.47) and cleaning the milking parlor regularly (OR 0.27, 95% CI 0.15-0.46) had decreased odds for subclinical mastitis, while herds with optimized feed had greater odds (OR 9.11, 95% CI 2.59-31.9). Prevalence of clinical mastitis was at its lowest at the first visit in June/July and highest at the last visit in April/June (OR 3.81, 95% CI 1.93-7.52). Subclinical mastitis also presented increased odds in the last visit (OR 2.62, 95% CI 2.0-3.36). This study has identified some risk factors for mastitis on smallholder farms but further research on more farms across more areas of Brazil is required to develop a targeted mastitis control program for smallholder farms.

Design-Based Approach for Analysing Survey Data in Veterinary Research.

Sample surveys are an essential approach used in veterinary research and investigation. A sample obtained from a well-designed sampling process along with robust data analysis can provide valuable insight into the attributes of the target population. Two approaches, design-based or model-based, can be used as inferential frameworks for analysing survey data. Compared to the model-based approach, the design-based approach is usually more straightforward and directly makes inferences about the finite target population (such as the dairy cows in a herd or dogs in a region) rather than an infinite superpopulation. In this paper, the concept of probability sampling and the design-based approach is briefly reviewed, followed by a discussion of the estimations and their justifications in the context of several different elementary sampling methods, including simple random sampling, stratified random sampling, and one-stage cluster sampling. Finally, a concrete example of a complex survey design (involving multistage sampling and stratification) is demonstrated, illustrating how finding unbiased estimators and their corresponding variance formulas for a complex survey builds on the techniques used in elementary sampling methods.

Rule Discovery in Milk Content towards Mastitis Diagnosis: Dealing with Farm Heterogeneity over Multiple Years through Classification Based on Associations.

Subclinical mastitis, an economically challenging disease of dairy cattle, is associated with an increased use of antimicrobials which reduces milk quantity and quality. It is more common than clinical mastitis and far more difficult to detect. Recently, much attention has been paid to the development of machine-learning expert systems for early detection of subclinical mastitis from milking features. However, differences between animals within a farm as well as between farms, particularly across multiple years, are major obstacles to the generalisation of machine learning models. Here, for the first time, we integrated scaling by quartiling with classification based on associations in a multi-year study to deal with farm heterogeneity by discovery of multiple patterns towards mastitis. The data were obtained from one farm comprising Holstein Friesian cows in Ongaonga, New Zealand, using an electronic automated monitoring system. The data collection was repeated annually over 3 consecutive years. Some discovered rules, such as when the milking peak flow is low, electrical conductivity (EC) of milk is low, milk lactose is low, milk fat is high, and milk volume is low, the cow has subclinical mastitis, reached high confidence (>70%) in multiple years. On averages, over 3 years, low level of milk lactose and high value of milk EC were part of 93% and 83.8% of all subclinical mastitis detecting rules, offering a reproducible pattern of subclinical mastitis detection. The scaled year-independent combinational rules provide an easy-to-apply and cost-effective machine-learning expert system for early detection of hidden mastitis using milking parameters.