Genetic analysis of phenotypic indicators for heat tolerance in crossbred dairy cattle.

Climate change-induced rise in global temperatures has intensified heat stress on dairy cattle and is contributing to the generally observed low milk productivity. Selective breeding aimed at enhancing animals' ability to withstand rising temperatures while maintaining optimal performance is crucial for ensuring future access to dairy products. However, phenotypic indicators of heat tolerance are yet to be effectively factored into the objectives of most selective breeding programs. This study investigated the response of milk production to changing heat load as an indication of heat tolerance and the influence of calving season on this response in multibreed dairy cattle performing in three agroecological zones Kenya. First-parity 7-day average milk yield (65 261 milk records) of 1 739 cows were analyzed. Based on routinely recorded weather data that were accessible online, the Temperature-Humidity Index (THI) was calculated and used as a measure of heat load. THI measurements used represented averages of the same 7-day periods corresponding to each 7-day average milk record. Random regression models, including reaction norm functions, were fitted to derive two resilience indicators: slope of the reaction norm (Slope) and its absolute value (Absolute), reflecting changes in milk yield in response to the varying heat loads (THI 50 and THI 80). The genetic parameters of these indicators were estimated, and their associations with average test-day milk yield were examined. There were no substantial differences in the pattern of milk yield response to heat load between cows calving in dry and wet seasons. Animals with ≤50% Bos taurus genes were the most thermotolerant at extremely high heat load levels. Animals performing in semi-arid environments exhibited the highest heat tolerance capacity. Heritability estimates for these indicators ranged from 0.06 to 0.33 and were mostly significantly different from zero (P < 0.05). Slope at THI 80 had high (0.64-0.71) negative correlations with average daily milk yield, revealing that high-producing cows are more vulnerable to heat stress and vice versa. A high (0.63-0.74) positive correlation was observed between Absolute and average milk yield at THI 80. This implied that low milk-producing cows have a more stable milk production under heat-stress conditions and vice versa. The study demonstrated that the slope of the reaction norms and its absolute value can effectively measure the resilience of crossbred dairy cattle to varying heat load conditions. The implications of these findings are valuable in improving the heat tolerance of livestock species through genetic selection.

Resilience indicator traits in 3 dairy cattle breeds in Baden-Württemberg.

In recent years, research in animal breeding has increasingly focused on the topic of resilience, which is expected to continue in the future due to the need for high-yielding, healthy, and robust animals. In this context, an established approach is the calculation of resilience indicator traits with time series analyses. Examples are the variance and autocorrelation of daily milk yield in dairy cows. We applied this methodology to the German dairy cow population. Data from the 3 breeds (German Holstein, German Fleckvieh, and German Brown Swiss) were obtained, which included 13,949 lactations from 36 farms from the state Baden-Württemberg in Germany working with automatic milking systems. Using the milk yield data, the daily absolute milk yields, deviations between observed and expected daily milk yields, and relative proportions of daily milk yields in relation to lactation performance were calculated. We used the variance and autocorrelation of these data as phenotypes in our statistical analyses. We estimated a heritability of 0.047 for autocorrelation and heritabilities between 0.026 and 0.183 for variance-based indicator traits. Furthermore, significant breed differences could be observed, with a tendency of better resilience in Brown Swiss. The breed differences can be due to both genetic and environmental factors. A high value of a variance-based indicator trait indicates a low resilience. Performance traits were positively correlated with variance-based indicator traits calculated from absolute daily milk yields, but they were negatively correlated with variance-based indicators calculated from relative daily milk yields. Thus, they can be considered as different traits. Although variance-based indicators based on absolute daily milk yields were affected by the performance level, variance-based indicators based on relative daily milk yields were corrected for the performance level and also showed higher heritabilities. Thus, they seem to be more suitable for practical use. Further studies need to be conducted to calculate the correlations between resilience indicators, functional traits, and health traits.

Morphology, adipocyte size, and fatty acid analysis of dairy cattle digital cushions, and the effect of body condition score and age.

The digital cushion is an essential part of maintaining a healthy foot, working to dissipate foot strike and body weight forces and lameness from claw horn disruption lesions. Despite the importance of the digital cushion, little is known about the basic anatomy, adipocyte morphology, and fatty acid composition in relation to age, limb position, and body condition score. In total, 60 claws (from 17 cows) were selected and collected from a herd, ensuring that body condition score data and computed micro-tomography were known for each animal. Digital cushion tissue underwent histological staining combined with stereology, systematic random sampling, and cell morphology analysis, in addition to lipid extraction followed by fatty acid analysis. The results describe digital cushion architecture and adipocyte sizes. Adipocyte size was similar across all 4 claws (distal left lateral and medial and distal right lateral and medial) and across the ages (aged 2-7 yr); however, animals with body condition score of 3.00 or more at slaughter had a significantly increased cell size in comparison to those with a score of less than 2.50. Of 37 fatty acid methyl esters identified, 5 differed between either the body condition score or different age groups. C10:0 capric acid, C14:0 myristic acid, C15:0 pentadecanoic acid, and C20:0 arachidic acid percentages were all lesser in lower body condition score cows, whereas C22:1n-9 erucic acid measurements were lesser in younger cows. Saturated fatty acid, monounsaturated fatty acid, and polyunsaturated fatty acid percentages were not altered in the different claws, ages, or body condition score groups. Triglyceride quantities did not differ for claw position or age but had decreased quantities in lower body condition score animals. Digital cushion anatomy, cellular morphology, and fatty acid composition have been described in general and also in animals with differing ages, body condition scores, and in the differing claws. Understanding fat deposition, mobilization, and composition are essential in not only understanding the roles that the digital cushion plays but also in preventing disorders and maintaining cattle health and welfare.

How Information Communication Technology Can Enhance Evidence-Based Decisions and Farm-to-Fork Animal Traceability for Livestock Farmers.

Due to changes in the livestock sector and the rise of consumer demand for comprehensive and integrated food security and safety, there has been a concern on the use of farm data in enhancing animal traceability and decision-making by farmers and other decision-makers in the livestock sector. To ensure high production through effective decision-making and auditable standards, producers are required to have better traceability and record systems. Therefore, this study aimed at (1) reviewing the current recording/data management and animal traceability systems used by small-scale farmers in developing countries and (2) analyzing how data management systems should be designed to enhance efficient decision-making and animal traceability from farm to fork. This study found that, still, a majority of small-scale farmers do not keep records leading to poor decision-making on the farm and policymaking. We also found that those who keep records do not store their data in electronic format, which again poses another challenge in data analysis. Moreover, this study found that the majority of traceability tools used by farmers in developing countries do not meet international standards based on tools they use for tracing animals; farmers were reported to use tools like branding and ear tagging, which provide very little information about the animal. Such tools lack the capability to keep track of useful information about an animal, e.g., information about feeding and animal health. In conclusion, this study recommended a better electronic system to be used at the farm level to facilitate data analysis, hence promoting informed decision-making and adherence to the international animal traceability standards. Otherwise, there is a need for researchers to conduct more studies in developing different analytical models for exploring on-farm data in order to improve the decision-making process by farmers and other stakeholders.

Machine learning models for predicting the use of different animal breeding services in smallholder dairy farms in Sub-Saharan Africa.

This study is concerned with developing predictive models using machine learning techniques to be used in identifying factors that influence farmers' decisions, predict farmers' decisions, and forecast farmers' demands relating to breeding service. The data used to develop the models comes from a survey of small-scale dairy farmers from Tanzania (n = 3500 farmers), Kenya (n = 6190 farmers), Ethiopia (n = 4920 farmers), and Uganda (n = 5390 farmers) and more than 120 variables were identified to influence breeding decisions. Feature engineering process was used to reduce the number of variables to a practical level and to identify the most influential ones. Three algorithms were used for feature selection, namely: logistic regression, random forest, and Boruta. Subsequently, six predictive models, using features selected by feature selection method, were tested for each country-neural network, logistic regression, K-nearest neighbor, decision tree, random forest, and Gaussian mixture model. A combination of decision tree and random forest algorithms was used to develop the final models. Each country model showed high predictive power (up to 93%) and are ready for practical use. The use of ML techniques assisted in identifying the key factors that influence the adoption of breeding method that can be taken and prioritized to improve the dairy sector among countries. Moreover, it provided various alternatives for policymakers to compare the consequences of different courses of action which can assist in determining which alternative at any particular choice point had a high probability to succeed, given the information and alternatives pertinent to the breeding decision. Also, through the use of ML, results to the identification of different clusters of farmers, who were classified based on their farm, and farmers' characteristics, i.e., farm location, feeding system, animal husbandry practices, etc. This information had significant value to decision-makers in finding the appropriate intervention for a particular cluster of farmers. In the future, such predictive models will assist decision-makers in planning and managing resources by allocating breeding services and capabilities where they would be most in demand.

Current situations of animal data recording, dairy improvement infrastructure, human capacity and strategic issues affecting dairy production in sub-Saharan Africa.

An online survey on the state of existing dairy data, dairy improvement infrastructure and human capacity in sub-Saharan Africa (SSA) was undertaken with the aim of assessing whether the state of existing animal recording, dairy improvement methods and key issues facing dairy production together with means of addressing the issues differ among countries and regions of SSA. Respondents comprised experts and practitioners in livestock production and genetic resources from research institutes, animal breeding companies, universities, non-governmental organisations and government agricultural ministries. The main dairy farming system in which the respondents were involved was mixed crop-livestock system (30.2%), and this was mainly practised in the private land tenure system (46.3%). Data were analysed using linear model and paired Student t test in R software package. Respondents identified key issues affecting dairy production as poor genetic assessment of imported exotic breeds and crosses in Africa (62.3%), fluctuations in milk prices within both the formal and informal markets (50.9%), no comprehensive sire ranking systems (39.6%), housing and health management regimes which adversely affect milk yield (32.1%), poor market networks for dairy products (25.5%), poor feeding (13.3%), inadequate genetic technologies (9.4%) and poor animal performance recording systems (9.4%). Respondents emphasised the need for updated breeding policies, sire ranking systems, adequate farm management systems, capacity building, across-country collaborations and joint genetic assessments of dairy breeds found in sub-Saharan Africa. The current situation of dairy production though similar for the different countries, differed in order of emphasis and magnitude across the countries and regions in sub-Saharan Africa.

Farmer-preferred traits in smallholder dairy farming systems in Tanzania.

Decisions of breeding schemes in many countries in sub-Saharan Africa tend to be either government or project driven, with a focus on upgrading local breeds. However, there is scant information on the individual animal traits that smallholder farmers prefer. The aim of this study was to examine farmers' preferences of dairy cattle traits using a discrete choice experiment methodology. The study was conducted through visits to 555 randomly selected dairy farms in the sub-humid Eastern coast and temperate Southern highlands of Tanzania. Choices of animal traits were presented to farmers who were asked to evaluate choice alternatives based on attribute levels and finally select the alternative with the highest utility. The choice experiment data were analysed using a conditional logit model. Coefficients for milk yield, fertility, feed requirement, temperament and diseases resistance were overall statistically significant (p < 0.05). In order of perceived importance, farmers were willing to keep a cow with high milk yield (coefficient = 1.43 ± 0.059), good fertility (0.85 ± 0.050), easy temperament (0.76 ± 0.066), low feed requirement (- 0.56 ± 0.092) and enhanced tropical disease resistance (0.48 ± 0.048). The purchase price coefficient was negative (- 0.001 ± 0.0003), indicating that farmers would prefer improved dairy cattle at affordable prices. Farmers' preferred traits were influenced by agro-ecological zone and type of production system (extensive vs intensive). The study provides an opportunity for breeding programme designers to take farmers' preferred dairy traits into serious consideration.

Multi-country investigation of factors influencing breeding decisions by smallholder dairy farmers in sub-Saharan Africa.

Artificial insemination (AI) and selective bull mating are considered as robust methods for dairy cattle breeding. Globally, these methods have been used to enhance productivity and realize rapid genetic gains. However, these technologies have had low adoption rates in sub-Saharan Africa (SSA). Even though available evidence suggests that this is due to various infrastructural and technical challenges. There is limited information about what drives this low uptake of AI from a farmer's perspective. Therefore, the main objective of this study was to determine and characterize factors that influence the choice by smallholder farmers between bull service and AI for dairy cow breeding. Further, the relationships between the breeding choices and the bio-physical elements of dairy farming, mainly, farmer characteristics, household income levels, farm management practices, and institutional support structures, were investigated. Data were collected through face-to-face interviews from a total of 16,308 small-scale dairy farmers in Ethiopia (n = 4679), Kenya (n = 5278), Tanzania (n = 3500), and Uganda (n = 2851). The questionnaire was coded in an electronic form using Open Data Kit (ODK) platform to allow for real-time data entry and management. Descriptive statistics, chi-square test, and a t-test were used to evaluate the independent and dependent variables, while logistic regression and factor analysis were used to identify factors that influenced farmers' breeding decisions. Results showed that there was a significant difference in animal husbandry practices between farmers who used artificial insemination (AI) and those who practiced bull mating. The majority of farmers who used AI kept records, purchased more animal feeds, had more labor by hiring workers whose average wages were higher than those of bull service farmers. However, farmers who used AI pay more for services such as water access and breeding while their service providers had to cover long distances compared to farmers who used bulls. This indicates limited access to services and service providers for AI farmers. The ratio of AI to bull service users was even for Ethiopia and Kenya, while in Uganda and Tanzania, more farmers preferred bull service to AI. It was established that the factors that influence farmers' breeding decision were not the same across the region. Factors such as farmer's experience in dairy farming, influence of the neighbor, farmer's ability to keep records, and management practices such as water provision and availability of feeds had a significant association (p < 0.001) with AI adoption among dairy farmers. In contrast, large herd and large land size negatively influenced AI adoption. Institutional settings including cost of AI service and the distance covered by the service provider negatively affected (p < 0.001) the choice of AI as a breeding option. There was a high probability of continued use of a specific breeding method when there was a previous conception success with that same method. Based on the results obtained, we recommend that improvement of institutional settings such as the availability of AI service providers, as well as better access to services such as water, animal feed, and animal health provision, be treated as critical components to focus on for enhanced AI adoption. Most importantly, there is a need to avail training opportunities to equip farmers with the necessary skills for best farm management practices such as record keeping, proper feeding, and selective breeding.

Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle.

It may be possible for dairy farms to improve profitability and reduce environmental impacts by selecting for higher feed efficiency and lower methane (CH4) emission traits. It remains to be clarified how CH4 emission and feed efficiency traits are related to each other, which will require direct and accurate measurements of both of these traits in large numbers of animals under the conditions in which they are expected to perform. The ranking of animals for feed efficiency and CH4 emission traits can differ depending upon the type and duration of measurement used, the trait definitions and calculations used, the period in lactation examined and the production system, as well as interactions among these factors. Because the correlation values obtained between feed efficiency and CH4 emission data are likely to be biased when either or both are expressed as ratios, therefore researchers would be well advised to maintain weighted components of the ratios in the selection index. Nutrition studies indicate that selecting low emitting animals may result in reduced efficiency of cell wall digestion, that is NDF, a key ruminant characteristic in human food production. Moreover, many interacting biological factors that are not measured directly, including digestion rate, passage rate, the rumen microbiome and rumen fermentation, may influence feed efficiency and CH4 emission. Elucidating these mechanisms may improve dairy farmers ability to select for feed efficiency and reduced CH4 emission.

The contribution of previous lameness events and body condition score to the occurrence of lameness in dairy herds: A study of 2 herds.

It has been demonstrated that low body condition and previous occurrence of lameness increase the risk of future lameness in dairy cows. To date the population attributable fraction (PAF), which provides an estimate of the contribution that a risk factor makes toward the total number of disease events in a population, has not been explored for lameness using longitudinal data with repeated measures. Estimation of PAF helps to identify control measures that could lead to the largest improvements on-farm. The aim of this study was to use longitudinal data to evaluate the proportion of lameness that could be avoided in 2 separate herds (2 populations) through (1) reduced recurrence of previous lameness events, (2) and moving body condition score (BCS) into more optimal ranges. Data were obtained from 2 UK dairy herds: herd A, a 200-cow herd with 8 yr of data from a total of 724 cows where lameness events were based on weekly locomotion scores (LS; 1 to 5 scale), and herd B, a 600-cow herd with data recorded over 44 mo from a total of 1,040 cows where treatment of clinical cases was used to identify lameness events. The PAF for categories of BCS were estimated using a closed equation appropriate for multiple exposure categories. Simulation models were used to explore theoretical scenarios to reflect changes in BCS and recurrence of previous lameness events in each herd. For herd A, 21.5% of the total risk periods (cow-weeks) contained a lameness event (LS 3, 4, or 5), 96% of which were repeat events and 19% were recorded with BCS <2 (3 wk previously; 0 to 5 scale). When lameness events were based on 2 consecutive weeks of LS 4 or 5, 4% of risk periods were recorded as lame, of which 89.5% were repeat events. For herd B, 16.3% of the total risk periods (consecutive 30 d) contained a lameness event (72.6% were repeat events) and 20% were recorded with BCS ≤2 (0 to 120 d previously). The median PAF for all previous lameness was between 79 and 83% in the 2 herds. Between 9 and 21% of lameness events could be attributed to previous lameness occurring >16 wk before a risk period. The median PAF estimated for changes in BCS were in the region of 4 to 11%, depending on severity of lameness. Repeated bouts of lameness made a very large contribution to the total number of lameness events. This could either be because certain cows are initially susceptible and remain susceptible, due to the increased risk associated with previous lameness events, or due to interactions with environmental factors. This area requires further research.

Relative emissions intensity of dairy production systems: employing different functional units in life-cycle assessment.

This study aimed to assess the merit and suitability of individual functional units (FU) in expressing greenhouse gas emissions intensity in different dairy production systems. An FU provides a clearly defined and measurable reference to which input and output data are normalised. This enables the results from life-cycle assessment (LCA) of different systems to be treated as functionally equivalent. Although the methodological framework of LCA has been standardised, selection of an appropriate FU remains ultimately at the discretion of the individual study. The aim of the present analysis was to examine the effect of different FU on the emissions intensities of different dairy production systems. Analysis was based on 7 years of data (2004 to 2010) from four Holstein-Friesian dairy systems at Scotland's Rural College's long-term genetic and management systems project, the Langhill herd. Implementation of LCA accounted for the environmental impacts of the whole-farm systems and their production of milk from 'cradle to farm gate'. Emissions intensity was determined as kilograms of carbon dioxide equivalents referenced to six FU: UK livestock units, energy-corrected milk yield, total combined milk solids yield, on-farm land used for production, total combined on- and off-farm land used for production, and the proposed new FU-energy-corrected milk yield per hectare of total land used. Energy-corrected milk was the FU most effective for reflecting differences between the systems. Functional unit that incorporated a land-related aspect did not find difference between systems which were managed under the same forage regime, despite their comprising different genetic lines. Employing on-farm land as the FU favoured grazing systems. The proposed dual FU combining both productivity and land use did not differentiate between emissions intensity of systems as effectively as the productivity-based units. However, this dual unit displayed potential to quantify in a simple way the positive or negative outcome of trade-offs between land and production efficiencies, in which improvement in emissions intensity using one FU may be accompanied by deterioration using another FU. The perceived environmental efficiencies of different dairy production systems in terms of their emissions intensities were susceptible to change based upon the FU employed, and hence the FU used in any study needs to be taken into account in the interpretation of results.

Association between body energy content in the dry period and post-calving production disease status in dairy cattle.

The transition from gestation to lactation is marked by significant physiological changes for the individual cow such that disease incidence is highest in early lactation. Around the time of calving, cows rely on mobilisation of body energy reserves to fill the energy deficit created by an increase in nutrient demands at a time of restricted feed intake. It is well established that monitoring of body energy reserves in lactation is an important component of herd health management. However, despite their influence on future health and productivity, monitoring of body energy reserves in the dry period is often sparse. Further, there is increasing concern that current dry off management is inappropriate for modern cattle and may influence future disease risk. This study aimed to identify candidate indicators of early lactation production disease from body energy data collected in the dry period and production data recorded at the time of dry off. Retrospective analysis was performed on 482 cow-lactations collected from a long-term Holstein-Friesian genetic and management systems project, the Langhill herd in Scotland. Cow-lactations were assigned to one of four health groups based on health status in the first 30 days of lactation. These four groups were as follows: healthy, reproductive tract disorders (retained placenta and metritis), subclinical mastitis and metabolic disorders (ketosis, hypocalcaemia, hypomagnesaemia and left displaced abomasum). ANOVA, employing a GLM was used to determine effects for the candidate indicator traits. Cows which were diagnosed with a reproductive tract disorder in the first 30 days of lactation experienced a significantly greater loss in body energy content, body condition score and weight in the preceding dry period than healthy cows. The rate of change in body energy content during the first 15 days of the dry period was -18.26 MJ/day for cows which developed reproductive tract disorder compared with +0.63 MJ/day for healthy cows. Cows diagnosed with subclinical mastitis in the first 30 days of lactation had significantly greater milk yield at dry off in the previous lactation than cows that developed a reproductive tract disorder or metabolic disease in addition to a significantly higher yield to body energy content ratio at dry off than healthy cows. Physiological and production traits recorded in the lactation and dry period preceding a disease event differed between cows which developed different diseases post-calving. Differences in these traits allow the development of new disease indicators for use in models for the prediction of disease risk in the transition period.

Lameness in dairy heifers; impacts of hoof lesions present around first calving on future lameness, milk yield and culling risk.

The importance of lameness in primiparous dairy heifers is increasingly recognised. Although it is accepted that clinical lameness in any lactation increases the risk of future lameness, the impact of foot lesions during the first lactation on long-term lameness risk is less clear. This retrospective cohort study aimed to investigate the impacts of foot lesions occurring around the time of first calving in heifers on future lameness risk, daily milk yield and survival within a dairy herd. Records were obtained for 158 heifers from one UK dairy herd. Heifers were examined in 2 month blocks from 2 months pre-calving through to 4 months post-calving. Sole lesions and white line lesions were scored on a zero to 10 scale and digital dermatitis on a zero to 3 scale. Outcomes investigated were; lameness risk based on weekly locomotion scores, average daily milk yield and culling risk. Mixed effect models were used to investigate associations between maximum lesion scores and outcomes. Lesion scores in the highest score categories for claw horn lesions (sole lesions and white line lesions) in the 2 to 4 month post-calving period were associated with an increased risk of future lameness; heifers with white line lesion scores ≥3 compared with scores zero to 1 and heifers with sole lesion scores ≥4 compared with score 2, at this time point, had a predicted increased risk of future lameness of 1.6 and 2.6 respectively. Sole lesions ≥4 were also associated with a reduction in average daily milk yield of 2.68kg. Managing heifers to reduce claw horn lesions during this time period post-calving may provide health, welfare and production benefits for the long-term future of those animals. A novel finding from the study was that mild lesion scores compared with scores zero to 1, were associated with a reduced risk of future lameness for white line lesions and sole lesions occurring in the pre-calving or 2 to 4 months post-calving periods respectively. Mild sole lesions in the pre-calving period were also associated with a reduced risk of premature culling. One hypothesis for this result is that a mild insult may result in adaptive changes to the foot leading to greater biomechanical resilience and so increased longevity.

Linking bone development on the caudal aspect of the distal phalanx with lameness during life.

Claw horn disruption lesions (CHDL; sole hemorrhage, sole ulcer, and white line disease) cause a large proportion of lameness in dairy cattle, yet their etiopathogenesis remains poorly understood. Untreated CHDL may be associated with damage to the internal anatomy of the foot, including to the caudal aspect of the distal phalanx upon which bone developments have been reported with age and with sole ulcers at slaughter. The primary aim of this study was to assess whether bone development was associated with poor locomotion and occurrence of CHDL during a cow's life. A retrospective cohort study imaged 282 hind claws from 72 Holstein-Friesian dairy cows culled from a research herd using X-ray micro-computed tomography (µ-CT; resolution: 0.11mm). Four measures of bone development were taken from the caudal aspect of each distal phalanx, in caudal, ventral, and dorsal directions, and combined within each claw. Cow-level variables were constructed to quantify the average bone development on all hind feet (BD-Ave) and bone development on the most severely affected claw (BD-Max). Weekly locomotion scores (1-5 scale) were available from first calving. The variables BD-Ave and BD-Max were used as outcomes in linear regression models; the explanatory variables included locomotion score during life, age, binary variables denoting lifetime occurrence of CHDL and of infectious causes of lameness, and other cow variables. Both BD-Max and BD-Ave increased with age, CHDL occurrence, and an increasing proportion of locomotion scores at which a cow was lame (score 4 or 5). The models estimated that BD-Max would be 9.8mm (SE 3.9) greater in cows that had been lame at >50% of scores within the 12mo before slaughter (compared with cows that had been assigned no lame scores during the same period), or 7.0mm (SE 2.2) greater if the cow had been treated for a CHDL during life (compared with cows that had not). Additionally, histology demonstrated that new bone development was osteoma, also termed "exostosis." Age explained much of the variation in bone development. The association between bone development and locomotion score during life is a novel finding, and bone development appears specific to CHDL. Bone development on the most severely affected foot was the best explained outcome and would seem most likely to influence locomotion score. To stop irreparable anatomical damage within the foot, early identification of CHDL and effective treatment could be critical.

Claw length recommendations for dairy cow foot trimming.

The aim was to describe variation in length of the dorsal hoof wall in contact with the dermis for cows on a single farm, and hence, derive minimum appropriate claw lengths for routine foot trimming. The hind feet of 68 Holstein-Friesian dairy cows were collected post mortem, and the internal structures were visualised using x-ray µCT. The internal distance from the proximal limit of the wall horn to the distal tip of the dermis was measured from cross-sectional sagittal images. A constant was added to allow for a minimum sole thickness of 5 mm and an average wall thickness of 8 mm. Data were evaluated using descriptive statistics and two-level linear regression models with claw nested within cow. Based on 219 claws, the recommended dorsal wall length from the proximal limit of hoof horn was up to 90 mm for 96 per cent of claws, and the median value was 83 mm. Dorsal wall length increased by 1 mm per year of age, yet 85 per cent of the null model variance remained unexplained. Overtrimming can have severe consequences; the authors propose that the minimum recommended claw length stated in training materials for all Holstein-Friesian cows should be increased to 90 mm.

Low body condition predisposes cattle to lameness: An 8-year study of one dairy herd.

Lameness in dairy cows is a multifactorial and progressive disease with complex interactions between risk factors contributing to its occurrence. Detailed records were obtained from one United Kingdom dairy herd over an 8-yr period. Weekly locomotion scores were used to classify cows as not lame (score 1 to 2), mildly lame (score 3) and severely lame (score 4 to 5). These outcomes were used to investigate the hypothesis that low body condition score (BCS) is associated with an increased risk of lameness in dairy cows. Mixed effect multinomial logistic regression models were used to investigate the association between prior BCS and repeat lameness events during the longitudinal period of the study. Discrete time survival models were used to explore the relationship between prior BCS and first lifetime lameness events. In total, 79,565 cow weeks at risk were obtained for 724 cows. The number of lameness events was 17,114, of which 8,799 were categorized as mildly lame and 8,315 as severely lame. The median BCS was 2.25 (range, 0.75 to 4.25) and the mean body weight (BW) and age at first calving were 619.5 kg (range, 355.6 to 956.4 kg) and 25.8 mo (range, 20.5 to 37.8 mo), respectively. Subsets of the data were used in the discrete time survival models: 333 mild and 211 severe first lifetime lameness events in heifers (first lactation cows), and 81 mild and 49 severe first lifetime lameness events in cows second lactation or greater. Low BCS 3 wk before a repeated lameness event was associated with a significantly increased risk of lameness. Cows with BCS<2 were at greatest risk of mild or severe lameness, and an increased BCS above 2 was associated with a reduced risk of mild or severe lameness. Low BCS 16 or 8 wk before a first mild or severe lifetime lameness event, respectively, also had a positive association with risk of lameness in cows second lactation or greater. This provides evidence to support targeting management toward maintaining BCS to minimize the risk of lameness. Low BW (independent of BCS) and increased age at first calving above 24 mo were also associated with increased long-term risk of repeated lameness events. Overall, the model explained 62 and 60% of the variability for mild and severe lameness, respectively, highlighting the importance of these variables as risk factors and hence where management could be targeted to significantly affect reducing the risk of lameness.

Genetic parameters for predicted methane production and laser methane detector measurements.

Enteric ruminant methane is the most important greenhouse gas emitted from the pastoral agricultural systems. Genetic improvement of livestock provides a cumulative and permanent impact on performance, and using high-density SNP panels can increase the speed of improvement for most traits. In this study, a data set of 1,726 dairy cows, collected since 1990, was used to calculate a predicted methane emission (PME) trait from feed and energy intake and requirements based on milk yield, live weight, feed intake, and condition score data. Repeated measurements from laser methane detector (LMD) data were also available from 57 cows. The estimated heritabilities for PME, milk yield, DMI, live weight, condition score, and LMD data were 0.13, 0.25, 0.11, 0.92, 0.38, and 0.05, respectively. There was a high genetic correlation between DMI and PME. No SNP reached the Bonferroni significance threshold for the PME traits. One SNP was within the 3 best SNP for PME at wk 10, 20, 30, and 40. Genomic prediction accuracies between dependent variable and molecular breeding value ranged between 0.26 and 0.30. These results are encouraging; however, more work is required before a PME trait can be implemented in a breeding program.

Evaluation of the laser methane detector to estimate methane emissions from ewes and steers.

The laser methane detector (LMD) has been proposed as a method to characterize enteric methane (CH4) emissions from animals in a natural environment. To validate LMD use, its CH4 outputs (LMD-CH4), were compared against CH4 measured with respiration chambers (chamber-CH4). The LMD was used to measure CH4 concentration (µL/L) in the exhaled air of 24 lactating ewes and 72 finishing steers. In ewes, LMD was used on 1 d for each ewe, for 2-min periods at 5 hourly observation periods (P1 to P5, respectively) after feeding. In steers fed either low- or high-concentrate diets, LMD was used once daily for a 4-min period for 3 d. The week after LMD-CH4 measurement, ewes or steers entered respiration chambers to quantify daily CH4 output (g/d). The LMD outputs consisted of periodic events of high CH4 concentrations superimposed on a background of oscillating lower CH4 concentrations. The high CH4 events were attributed to eructation and the lower background CH4 to respiration. After fitting a double normal distribution to the data set, a threshold of 99% of probability of the lower distribution was used to separate respiration from eructation events. The correlation between mean LMD-CH4 and chamber-CH4 was not high, and only improved correlations were observed after data were separated in 2 levels. In ewes, a model with LMD and DMI (adjusted R(2) = 0.92) improved the relationship between DMI and chamber-CH4 alone (adjusted R(2) = 0.79) and between LMD and chamber-CH4 alone (adjusted R(2) = 0.86). In both experiments, chamber-CH4 was best explained by models with length of eructation events (time) and maximum values of CH4 concentration during respiration events (µL/L; P < 0.01). Correlation between methods differed between observation periods, indicating the best results of the LMD were observed from 3 to 5 h after feeding. Given the short time and ease of use of LMD, there is potential for its commercial application and field-based studies. Although good indicators of quantity of CH4 were obtained with respiration and eructation CH4, the method needed to separate the data into high and low levels of CH4 was not simple to apply in practice. Further assessment of the LMD should be performed in relation to animal feeding behavior and physiology to validate assumptions of eructation and respiration levels, and other sources of variation should be tested (i.e., micrometeorology) to better investigate its potential application for CH4 testing in outdoor conditions.

Current trends in British dairy management regimens.

This paper presents a summary of results from a 2012 survey that investigated feeding and housing management regimens currently adopted by dairy farmers in Britain. Responses from 863 farms provide a snapshot of dairy industry structure and a description of the range of management systems currently in operation. Outcomes highlight a diversity of management practices, showing that 31% of farms maintained a traditional grazing system with no forage feeding indoors during the summer, whereas 38% of farmers indicated that all their milking cows received some feeding indoors during the summer. A system of housing dairy cows for 24 h/d while they are lactating was implemented by 8% of farms, whereas 1% of farms did not house their cows at any time of the year. Statistical analyses were carried out on 3 distinct groups identified from survey responses: (1) farmers who did not undertake any indoor feeding during the summer; (2) farmers who fed all their milking cows indoors during the summer; and (3) farmers who continuously housed their cows for 24h/d while lactating. Results showed a significant relationship between management type and herd size, and between management type and breed type; on average, herd sizes were larger within systems that feed indoors. No significant relationship was found between management type and farm location when classified by estimated grassland productivity. The results indicate that traditional all-summer grazing is no longer the predominant system adopted by dairy farmers and that other systems such as all-year-round indoor feeding and continuous housing are becoming more prevalent in Britain.

Opportunities and challenges in the use of the Laser Methane Detector to monitor enteric methane emissions from ruminants.

The objective of this review was to examine the application and relative efficiency of the proprietary hand-held Laser Methane Detector (LMD) in livestock production, with a focus on opportunities and challenges in different production systems. The LMD is based on IR absorption spectroscopy, uses a semiconductor laser as a collimated excitation source and uses the second harmonic detection of wavelength modulation spectroscopy to establish a methane (CH4) concentration measurement. The use of the LMD for CH4 detection in dairy cows is relatively recent. Although developed for entirely different purposes, the LMD provides an opportunity for non-invasive and non-contact scan sampling of enteric CH4. With the possibility for real-time CH4 measurements, the LMD offers a molecular-sensitive technique for enteric CH4 detection in ruminants. Initial studies have demonstrated a relatively strong agreement between CH4 measurements from the LMD with those recorded in the indirect open-circuit respiration calorimetric chamber (correlation coefficient, r = 0.8, P < 0.001). The LMD has also demonstrated a strong ability to detect periods of high-enteric CH4 concentration (sensitivity = 95%) and the ability to avoid misclassifying periods of low-enteric CH4 concentration (specificity = 79%). Being portable, the LMD enables spot sampling of methane in different locations and production systems. Two challenges are discussed in the present review. First is on extracting a representation of a point measurement from breath cycle concentrations. The other is on using the LMD in grazing environment. Work so far has shown the need to integrate ambient condition statistics in the flux values. Despite the challenges that have been associated with the use of the LMD, with further validation, the technique has the potential to be utilised as an alternative method in enteric CH4 measurements in ruminants.