Description and typology of intensive Chios dairy sheep farms in Greece

Seroepidemiology of Maedi-Visna in Intensively Reared Dairy Sheep: A Two-Year Prospective Study

The objective of this study is to prospectively evaluate the seroepidemiology of maedi-visna (MV) infections in intensively reared dairy sheep. A total of 407 purebred Chios and Lacaune ewes from four farms were surveyed for two consecutive years and were serologically tested semiannually with an indirect ELISA at pre-mating and pre-lambing. The farms' structure and management practices were similar and animal traits (age, breed, and production stage) were recorded. Based on the serological status, morbidity frequency measures were estimated, and ewes were categorized as constantly seronegative, constantly seropositive, seroconverted, seroreverted, or as animals with an intermittent presence of antibodies. During the study, period seroprevalence, incidence rate, and cumulative incidence were 84.8%, 33.6 new cases per 100 sheep-semesters, and 64.2%. Point-seroprevalence ranged from 48.5% to 96.0% among the studied farms and sampling occasions, and they increased by age. Increased morbidity frequency measures indicate the significance of horizontal transmission in intensive dairy sheep farms. A remarkable percentage of infected animals seroreverted (8.1%) or presented an intermittent presence of antibodies (10.3%) during the study, confirming the risk of misdiagnosis in cross-sectional studies and in the currently implemented testing and elimination programs. The serological patterns observed in our study need to be considered when studying MV epidemiology and for the designing of efficient MV elimination programs.

Data on Mapping 444 Dairy Small Ruminant Farms during a Countrywide Investigation Performed in Greece

The small ruminant industry is the most important branch of Greek agriculture. Nevertheless, despite the importance of small ruminant farming for Greece, no detailed mapping of the respective farms has been undertaken and published. The present work refers to mapping the dairy sheep and goat industry in Greece through an extensive, countrywide cross-sectional study, in which information was obtained from 325 sheep and 119 goat farms. The objectives were the collection, the classification and the presentation of data obtained from all these farms through interviews, using a questionnaire and through examination of samples collected during the visits. All the farms enrolled in the study were visited by the investigators. Initially, information was obtained by means of a detailed, structured questionnaire with 442 questions. Moreover, samples of milk were collected from the bulk-tank of each farm and faecal samples were collected from female animals in each farm. The milk samples were processed for cytological and microbiological examination. Staphylococcus spp. and Listeria spp. isolates were recovered and identified at a species level; furthermore, a full antibiotic sensitivity pattern assessment was conducted. Faecal samples were processed by standard parasitological tests for the identification of protozoan, trematode, cestode and gastrointestinal and respiratory nematode parasites. The paper presents the cumulative findings of the study, i.e., the answers to the questions during the interviews and the results of the laboratory examinations performed in the samples; the findings are presented separately for sheep and goat farms. The findings can be used as baseline measurements; individual farms and cohorts of farms can be compared against the current results to draw conclusions against the countrywide situation. Moreover, the current results can be used as reference points for the future, in order to assess changes that might have occurred in the meantime. The study also described the differences between farms with sheep or goats; in total, differences in 137 parameters were identified. Some of these can be attributed to the different management systems practiced; sheep flocks are managed mostly under the intensive or semi-intensive system, whilst goat herds are managed mostly under the semi-extensive or extensive system. These findings can be useful in the health management of small ruminants, in providing evidence-based support and within the scope of precise livestock medicine and health management.

Sheep Face Recognition Model Based on Deep Learning and Bilinear Feature Fusion

A key prerequisite for the establishment of digitalized sheep farms and precision animal husbandry is the accurate identification of each sheep's identity. Due to the uncertainty in recognizing sheep faces, the differences in sheep posture and shooting angle in the recognition process have an impact on the recognition accuracy. In this study, we propose a deep learning model based on the RepVGG algorithm and bilinear feature extraction and fusion for the recognition of sheep faces. The model training and testing datasets consist of photos of sheep faces at different distances and angles. We first design a feature extraction channel with an attention mechanism and RepVGG blocks. The RepVGG block reparameterization mechanism is used to achieve lossless compression of the model, thus improving its recognition efficiency. Second, two feature extraction channels are used to form a bilinear feature extraction network, which extracts important features for different poses and angles of the sheep face. Finally, features at the same scale from different images are fused to enhance the feature information, improving the recognition ability and robustness of the network. The test results demonstrate that the proposed model can effectively reduce the effect of sheep face pose on the recognition accuracy, with recognition rates reaching 95.95%, 97.64%, and 99.43% for the sheep side-, front-, and full-face datasets, respectively, outperforming several state-of-the-art sheep face recognition models.

Helminth Infections in Dairy Sheep Found in an Extensive Countrywide Study in Greece and Potential Predictors for Their Presence in Faecal Samples

The aims of the present study were: (a) to describe the prevalence of helminth infections from pooled faecal samples from sheep flocks across Greece and (b) to evaluate flock-related factors potentially associated with the presence of these infections in the flocks. An extensive countrywide study was performed on 325 sheep farms throughout Greece; faecal samples were collected from ewes and processed for the identification of helminth parasites. Helminths were detected in samples from 92.9% of flocks; these included Dicrocoelium dendriticum (16.7% of flocks), Fasciola hepatica (0.6%), Paramphistomum cervi (2.2%), Moniezia spp. (18.8%), Trichostrongylidae (85.5%), Nematodirus spp. (18.8%), Strongyloides papillosus (7.1%), Trichuris spp. (20.0%) and lungworms (17.8%). Mean Trichostrongylidae counts across all flocks in the study were 215 epg. Specifically, for Trichostrongylidae, there were differences between flocks that had or had not received anthelmintics during the two months prior to sampling, as well as between flocks located in various areas of the country. In multivariable analyses, for the outcome 'high (>300) epg counts in faecal samples', the month into the lactation period at sampling and the application of reproductive control practices on the farm emerged as significant factors; for the outcome 'high proportion (>63%) of Teladorsagia spp. in faecal samples', the availability of straw bedding emerged as a significant factor; and for the outcome 'high proportion (>63%) of Haemonchus contortus in faecal samples', the age of the farmer emerged as a significant factor. For the outcome 'presence of Trichuris spp. in faecal samples', the provision of finished feed (concentrate) to animals emerged as a significant factor, whilst, finally, for the outcomes 'presence of D. dendriticum in faecal samples' and 'presence of lungworms in faecal samples,' no significant factors emerged.

Characteristics of Buffalo Farming Systems in Turkey Based on a Multivariate Aggregation of Indicators: A Survey Study

This study aimed to determine the heterogeneity that exists in water buffalo husbandry systems in Marmara Region, Turkey. A questionnaire containing a total of 60 indicators was submitted to 52 farmers. A Principal Component Analysis was performed to reduce original variables into a simplified and latent structure, which was characterized by six orthogonal components: milk productivity, economic efficiency, roughage management, dual-purpose farming, concentrate supply, and fodder production. An ANOVA model was applied to the six components to investigate the effects of the province, investment levels, grazing type, milk production, and profitability. Differences in milk productivity, roughage management, concentrate supply, and fodder management were significant according to the province and grazing type, which indicated a difference in intensification levels among the cities. Economic efficiency and dual-purpose farming differed significantly for milk production levels as well as milk productivity, and economic efficiency differed for profitability levels. We found a tendency regarding the impact of roughage management on profitability. The results conclude that profitability was associated with improving the milking traits of buffaloes and roughage management of the farms.

Effects of Intensive and Semi-Intensive Production on Sheep Milk Chemical Composition, Physicochemical Characteristics, Fatty Acid Profile, and Nutritional Indices

Simple Summary

Intensive and semi-intensive sheep farming are the two farming systems usually employed in Greece. Several studies have been conducted on the effect of the farming system on sheep milk fatty acid composition. This study simultaneously examines milk basic composition, physicochemical characteristics, fatty acid composition, and nutritional value according to the production system. Bulk tank milk from farms using the intensive and semi-intensive production systems was analyzed. The results show that grazing can improve the fatty acid composition of milk. Thus, pasture-based feeding strategies could improve the fatty acid composition and the nutritional properties of sheep dairy products.

Abstract

Dairy sheep farming is a vital sector of the agricultural economy in Greece. Information on the effect of the farming system on sheep milk characteristics is critical for producing dairy products with improved nutritional value according to the current guidelines for healthy food consumption. This study aimed to investigate the basic composition, physicochemical characteristics, fatty acid composition, and nutritional indices of milk produced in intensive and semi-intensive sheep farms. Bulk tank milk samples from 20 intensive and 20 semi-intensive sheep farms were examined. Sheep in the intensive farms were kept indoors and were fed with roughage, silage, and concentrates. Sheep in the semi-intensive farms were kept indoors during the night and were moved to the pastures during the day. Sheep were fed with roughage, silage, and concentrates in combination with grazing. Milk composition and somatic cell count were determined with automatic analyzers. The physicochemical characteristics were determined with standard laboratory methods. The fatty acid composition was analyzed by gas chromatography. The farming system did not affect milk chemical composition and physicochemical characteristics. However, milk fatty acid composition and nutritional value were significantly improved in milk from farms using the semi-intensive production system, and this favorable effect was attributed to the inclusion of pasture in sheep diet.

Understanding the dairy production systems in rural settlements in the Brazilian semi-arid region: characterization, typology, and holistic perception

The objective of this study was to characterize and typify dairy farms and to evaluate society's perception of dairy production in rural settlements in the Brazilian semi-arid region. A questionnaire containing questions related to socioeconomic, livestock, physical, herd management, and production indicators was applied to 17 milk farmers for typological analysis. A second questionnaire was subsequently applied to the same 17 farmers for the holistic perception of dairy farming in rural settlements, in addition to 47 technicians in the area of animal science and 140 laypeople. Milk samples were collected in the settlement's community cooling tank, while the water used for milking management was collected in the milking parlor at the 17 farms. Multivariate analysis techniques and thematic analysis were performed. Three dairy production systems were identified: low production group (0-25 L), medium production group (25-50 L), and high production group (50-100 L). The physicochemical properties (composition, density, and cryoscopy) of milk attended the Brazilian regulation values. The microbiological parameters of milk and water used for milking are at odds with regulations. Regarding the typology, the indicators, livestock, and productivity showed discriminatory power (P < 0.05) between the productive systems. The responses from the segments of society showed different views on dairy production in rural settlements. It is concluded that the dairy farmers have low education and the cleaning product and water used in milking are out of regulation. The livestock and production indicators typified mainly dairy farms, while the holistic perception showed a lack of efficiency in rural extension, ignorance of the potential of the productive system. Finally, the creation of public policies focusing on the development of the milk production system in settlements is recommended.

Comparative Transcriptome Analysis of Milk Somatic Cells During Lactation Between Two Intensively Reared Dairy Sheep Breeds

In dairy sheep industry, milk production dictates the value of a ewe. Milk production is directly related to the morphology and physiology of the mammary gland; both being designated targets of breeding strategies. Although within a flock breeding parameters are mutual, large differences in milk production among individual ewes are usually observed. In this work, we tested two of the most productive dairy sheep breeds reared intensively in Greece, one local the Chios breed and one foreign the Lacaune breed. We used transcriptome sequencing to reveal molecular mechanisms that render the mammary gland highly productive or not. While highly expressed genes (caseins and major whey protein genes) were common among breeds, differences were observed in differentially expressed genes. ENSOARG00000008077, as a member of ribosomal protein 14 family, together with LPCAT2, CCR3, GPSM2, ZNF131, and ASIP were among the genes significantly differentiating mammary gland's productivity in high yielding ewes. Gene ontology terms were mainly linked to the inherent transcriptional activity of the mammary gland (GO:0005524, GO:0030552, GO:0016740, GO:0004842), lipid transfer activity (GO:0005319) and innate immunity (GO:0002376, GO:0075528, GO:0002520). In addition, clusters of genes affecting zinc and iron trafficking into mitochondria were highlighted for high yielding ewes (GO:0071294, GO:0010043). Our analyses provide insights into the molecular pathways involved in lactation between ewes of different performances. Results revealed management issues that should be addressed by breeders in order to move toward increased milk yields through selection of the desired phenotypes. Our results will also contribute toward the selection of the most resilient and productive ewes, thus, will strengthen the existing breeding systems against a spectrum of environmental threats.

A Typological Classification for Assessing Farm Sustainability in the Italian Bovine Dairy Sector

Italy is among the most important countries in Europe for milk production. The new European policies encourage a transition towards sustainability and are leading European dairy farms to follow new trajectories to increase their economic efficiency, reduce their environmental impact, and ensure social sustainability. Few studies have attempted to classify dairy farms by analyzing the relationships between the structural profiles of farms and the social, environmental, and economic dimensions of sustainability. This work intends to pursue this aim through an exploratory analysis in the Italian production context. The cluster analysis technique made it possible to identify three types of dairy farms, which were characterized on the basis of indicators that represented the three dimensions of sustainability (environmental, social, and economic sustainability) and the emerging structural relationships based on the structural characteristics of the dairy farms. The classification made it possible to describe the state of the art of the Italian dairy sector in terms of sustainability and to understand how different types of farms can respond to the new European trajectories.

A Cross-Sectional Epizootiological Study and Risk Assessment of Foot-Related Lesions and Lameness in Intensive Dairy Sheep Farms

Simple Summary

Foot-related lameness is one of the most significant welfare issues in farm animals. Contrary to dairy cows and meat sheep breeds, epizootiological data on foot-lesions and associated lameness in dairy sheep are scarce. In this study, data were collected from 30 representative intensive dairy sheep farms. Multivariate statistical analysis was used to produce a typology of intensive farming systems which resulted in the assignment of farms in two distinct clusters. Six hundred adult ewes were randomly selected from six flocks (three flocks per cluster) and a cross-sectional study was implemented to investigate the epizootiology and potential risk factors of foot-related lameness, foot-lesions and diseases. Ovine interdigital dermatitis and infectious footrot were the most common infectious foot diseases, while white line disease and hoof wall cracks were the most prevalent non-infectious lesions. Infectious footrot was the main cause of lameness and increased with age, whereas body condition score was associated with increased prevalence of ovine interdigital dermatitis. Comparisons between the clusters regarding foot-related lameness, foot-diseases and lesions at the animal, the limb, and the hoof level are presented, and relevant literature, mechanisms, hypotheses, and challenges of the field are discussed.

Abstract

Foot-related lameness, foot-diseases and lesions are emerging issues in dairy sheep; however, relevant epizootiological studies are scarce, and risk factors have not been elucidated. The objectives of this cross-sectional study were (i) to address this dearth of knowledge by investigating the epizootiology of lameness-related foot-lesions and diseases, and (ii) to assess the impact of potential risk factors on foot health, in intensive dairy sheep farms. Thirty farms were assigned in two representative clusters using a multivariate statistical analysis. Three farms per cluster and 100 multiparous milking ewes per farm (total n = 600) were selected and enrolled in the study. Foot-related lameness, ovine interdigital dermatitis (OID), infectious footrot (IFR), white line disease, hoof wall cracks, as well as health and welfare traits were recorded. Overall prevalence of foot-related lameness was 9.0% and was primarily associated with IFR; however, additional infectious and non-infectious foot diseases and lesions also contributed. Among infectious foot diseases, OID was the most prevalent (21.3%) followed by IFR (8.0%); WLD and hoof wall cracks were the most prevalent non-infectious foot-lesions (37.7% and 15.3%, respectively). IFR and OID prevalence increased with age (p < 0.05) and BCS (p < 0.01), respectively, suggesting that host-related factors and husbandry practices are important determinants of its occurrence.

A Decision Support System for Economically Sustainable Sheep and Goat Farming

Simple Summary

The viability of the European sheep and goat sector is threatened by market, policy, social and technical challenges. To address such challenges, innovations for efficient farm management, especially with decision support capabilities, are considered a strategic priority. The iSAGEDSS is a web application, based on the Happy GoatS solution, which allows dairy and meat small ruminant farmers to make annual management plans by testing future what-if scenarios. It is designed for the meat sheep production system in the United Kingdom and Spain, the dairy sheep production system in France and Greece and the dairy goat production system in Greece. Moreover, it addresses all important farm parameters (flock size, production, processing, grazing, feeding, income and costs and farm prices) and utilizing an energy and protein-based algorithm for nutritional management assessment it produces reports, which are focused on profitability and productivity. Environmental-related figures are also estimated. Results are illustrated with simple and easily understood charts and plots. Case study application results showed high prediction accuracy and demonstrated the ability of the system to promote efficient farm management. In this regard, iSAGEDSS is expected to help farmers to adjust to the challenges faced by the sector and remain sustainable.

Abstract

The European sheep and goat sector is characterized by low professionalization and management training. Moreover, it is fragmented in terms of production aims and farming systems. Here, iSAGEDSS, a web-based application allowing dairy and meat small ruminant farmers in different countries to make annual management plans by testing future scenarios, is presented. Data were obtained for the meat sheep (United Kingdom and Spain), dairy sheep (France and Greece) and dairy goat production systems (Greece) from partners of the Innovation for Sustainable Sheep and Goat Production in Europe (iSAGE) project. These were used to set default values and ranges for all important farm parameters in each system and country. An algorithm was developed assessing nutritional management and its impact on production and financial performance. Reports focus on profitability, productivity and environmental sustainability. A case study in three dairy sheep farms in Greece was performed. In each case, an evaluation scenario was created using actual farm data that were compared with the estimated ones. Two scenarios testing management decisions for gross margin maximization and milk pricing fluctuations were created. Application results showed high prediction accuracy for gross margin and production estimation (error of circa 9% and 4%, respectively). Moreover, the ability to promote financial, production and grazing management efficiency was demonstrated.

Prediction of sheep milk chemical composition using milk yield, pH, electrical conductivity and refractive index

This Research Communication addresses the hypothesis that fat, protein, lactose and total solids content can be predicted using daily milk yield (DMY), pH, electrical conductivity (MEC) and refractive index (RI) of milk as predictors. It also addresses the possibility of these measurements being used for on-farm benchmarking activities towards selecting the highest yielding animals and flocks regarding milk quality traits (MQT). A total of 308 purebred Frizarta ewes were used for the study. From each individual ewe, a composite milk sample was collected. pH, MEC and RI of milk were measured and the samples were assayed for fat, protein, lactose and total solids content, using an automatic infrared milk analyser. The predictive value of DMY, pH, MEC and RI of milk on its MQT was assessed using multiple linear regression analysis. Significant regression equations were produced for all of the studied traits. RI and MEC were significant and reliable predictors for all studied MQT, whereas DMY was a significant predictor for most MQT with the exception of protein content. pH was a marginally significant predictor for some of the MQTs at the initial development of the equations but proved unreliable after bootstraping. Using these equations a number of ewes varying from 75 (for fat) to 97 (for protein) out of the 100 highest MQT yielders were correctly predicted, whereas, none of the ewes out of the 100 lowest MQT yielders was mispredicted as a high yielder for protein-, lactose- and total solids- content. Three out of 100 lowest fat-yielders were mispredicted as high fat-yielders. Similar equations can be used for benchmarking activities towards selecting the highest protein-, fat-, lactose- and total solids- yielding animals and flocks in cases where laboratories for MQT analyses are not readily available or the cost of chemical analyses is high. The method can be regarded as a handy tool for the dairy industry to readily assess milk quality at the farm level.

Genomic diversity and population structure of three autochthonous Greek sheep breeds assessed with genome-wide DNA arrays

In the present study, genome-wide genotyping was applied to characterize the genetic diversity and population structure of three autochthonous Greek breeds: Boutsko, Karagouniko and Chios. Dairy sheep are among the most significant livestock species in Greece numbering approximately 9 million animals which are characterized by large phenotypic variation and reared under various farming systems. A total of 96 animals were genotyped with the Illumina's OvineSNP50K microarray beadchip, to study the population structure of the breeds and develop a specialized panel of single-nucleotide polymorphisms (SNPs), which could distinguish one breed from the others. Quality control on the dataset resulted in 46,125 SNPs, which were used to evaluate the genetic structure of the breeds. Population structure was assessed through principal component analysis (PCA) and admixture analysis, whereas inbreeding was estimated based on runs of homozygosity (ROHs) coefficients, genomic relationship matrix inbreeding coefficients (F_GRM) and patterns of linkage disequilibrium (LD). Associations between SNPs and breeds were analyzed with different inheritance models, to identify SNPs that distinguish among the breeds. Results showed high levels of genetic heterogeneity in the three breeds. Genetic distances among breeds were modest, despite their different ancestries. Chios and Karagouniko breeds were more genetically related to each other compared to Boutsko. Analysis revealed 3802 candidate SNPs that can be used to identify two-breed crosses and purebred animals. The present study provides, for the first time, data on the genetic background of three Greek indigenous dairy sheep breeds as well as a specialized marker panel that can be applied for traceability purposes as well as targeted genetic improvement schemes and conservation programs.

Defining the breeding goal for a sheep breed including production and functional traits using market data

In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of -0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals.

A typological characterization of Canadian beef cattle farms based on a producer survey

The diverse nature of beef production was captured by establishing a farm typology based on an extensive survey of 1005 Canadian farms in 2011. The survey provided information on the type of operation, cattle numbers, feed storage and management, manure management, land use, producer demographics and attitudes to risk, and technology adoption. Principal component analysis and cluster analysis were used to understand the relationships among variables and to statistically identify farm types. A total of 41 diagnostic variables from 133 survey questions were used to define 16 principal components explaining 68% of the variation. Cluster analysis yielded eight major clusters as distinct farm types. The largest number of farms (37%) was grouped as small-scale, part-time cow–calf operations. Mixed operations (crop–beef) were next most frequent (22%), followed by large cow–calf backgrounding (18%) and diversified cow–calf operations that included crop–beef mixed operations as well as off-farm activities (11%). Cow–calf operations that finished calves comprised 8% of the total farms surveyed. Extensive cow–calf backgrounding operations, large backgrounding/finishing operations, and large finishing operations represented the remaining 3% of the farms. The typology not only provides a strategy by which the Canadian beef cattle industry can be characterized, but also improves understanding of the diversity of farm management practices to help develop policies and beneficial management practices.

Association of lameness with milk yield and lactation curves in Chios dairy ewes

The objective of the study was twofold: (i) to quantify the differences in daily milk yield (DMY) and total milk yield (TMY) between lame and non-lame dairy ewes and (ii) to determine the shape of lactation curves around the lameness incident. The overall study was a prospective study of lameness for the surveyed sheep population, with a nested study including the selection of matching controls for each lame ewe separately. Two intensively reared flocks of purebred Chios ewes and a total of 283 ewes were used. Data, including gait assessment and DMY records, were collected on a weekly basis during on-farm visits across the milking period. A general linear model was developed for the calculation of lactation curves of lame and non-lame ewes, whereas one-way ANOVA was used for the comparisons between lame ewes and their controls. Lameness incidence was 12.4 and 16.8% on Farms A and B, respectively. Average DMY in lame ewes was significantly lower (213.8 g, P < 0.001) compared with the rest of the flock, where DMY averaged 1.340 g. The highest DMY reduction in lame ewes was observed during the week 16 of the milking period (P < 0.001), whereas the reduction of DMY, for lame ewes, remained significant at P < 0.001 level from week 8 to week 28 of milking. Comparisons between lame and controls revealed that at the week of lameness diagnosis a significant DMY reduction (P ≤ 0.001) was observed in lame ewes (about 32.5%), which was maximised 1 week later (35.8%, P ≤ 0.001) and continued for several weeks after recovery, resulting in 19.3% lower TMY for lame ewes for the first 210 d of the milking period (P < 0.01). Moreover, at flock level, TMY for non-lame and lame ewes, as calculated by the general linear model, was 318.9 and 268.0 kg, respectively. The results of this study demonstrate evidence of significant financial losses in dairy sheep due to lameness which, however, need to be accurately estimated in further, more detailed, analyses.

Characterisation of terminal sire sheep farm systems, based on a range of environmental factors: a case study in the context of genotype by environment interactions using Charollais lambs

The objective of this study was to define different terminal sire flock environments, based on a range of environmental factors, and then investigate the presence of genotype by environment interactions (G×E) between the environments identified. Data from 79 different terminal sire flocks (40 Texel, 21 Charollais and 18 Suffolk), were analysed using principal coordinate and non-hierarchical cluster analyses, the results of which identified three distinct environmental cluster groups. The type of grazing, climatic conditions and the use of vitamins and mineral supplements were found to be the most important factors in the clustering of flocks. The presence of G×E was then investigated using data from the Charollais flocks only. Performance data were collected for 12 181 lambs, between 1990 and 2010, sired by 515 different sires. Fifty six of the sires had offspring in at least two of the three different cluster groups and pedigree information was available for a total of 161 431 animals. Traits studied were the 21-week old weight (21WT), ultrasound muscle depth (UMD) and log transformed backfat depth (LogUFD). Heritabilities estimated for each cluster, for each trait, ranged from 0.32 to 0.45. Genetic correlations estimated between Cluster 1 and Cluster 2 were all found to be significantly lower than unity, indicating the presence of G×E. They were 0.31 (±0.17), 0.68 (±0.14) and 0.18 (±0.21) for 21WT, UMD and LogUFD, respectively. Evidence of sires re-ranking across clusters was also observed. Providing a suitable strategy can be identified, there is potential for the optimisation of future breeding programmes, by taking into account the G×E observed. This would enable farmers to identify and select animals with an increased knowledge as to how they will perform in their specific farm environment thus reducing any unexpected differences in performance.