{"results":[{"id":"ss_d13b289a2d14e3de4bfb2e79384ef98a3fb31e0c","title":"Nutrient Requirements of Dairy Cattle","authors":null,"abstract":"","source":"Semantic Scholar","year":2016,"language":"en","subjects":["Biology"],"doi":"10.17226/9825","url":"https://www.semanticscholar.org/paper/d13b289a2d14e3de4bfb2e79384ef98a3fb31e0c","pdf_url":"https://revistas.ucr.ac.cr/index.php/agromeso/article/download/13244/12519","is_open_access":true,"citations":3271,"published_at":"","score":90},{"id":"ss_17747da5912a653ebf71169ef8e13ce3d47c3ca3","title":"Nutrient Requirements of Beef Cattle","authors":[{"name":"Board on Agriculture"},{"name":"Division on Earth"}],"abstract":"","source":"Semantic Scholar","year":2016,"language":"en","subjects":["Biology"],"doi":"10.17226/19398","url":"https://www.semanticscholar.org/paper/17747da5912a653ebf71169ef8e13ce3d47c3ca3","pdf_url":"https://oaktrust.library.tamu.edu/bitstream/1969.1/160188/8/Bull1554a.pdf","is_open_access":true,"citations":1196,"published_at":"","score":90},{"id":"ss_a543347de2ab10e191a1130c04d88e012f4bca21","title":"Invited review: Genomic selection in dairy cattle: progress and challenges.","authors":[{"name":"B. Hayes"},{"name":"P. J. Bowman"},{"name":"A. Chamberlain"},{"name":"M. Goddard"}],"abstract":"","source":"Semantic Scholar","year":2009,"language":"en","subjects":["Biology","Medicine"],"doi":"10.3168/jds.2008-1646","url":"https://www.semanticscholar.org/paper/a543347de2ab10e191a1130c04d88e012f4bca21","pdf_url":"http://www.journalofdairyscience.org/article/S0022030209703479/pdf","is_open_access":true,"citations":1668,"published_at":"","score":83},{"id":"ss_f5762b255ff2dca07b4f05a7048307ac07a2a867","title":"Veterinary medicine : a textbook of the diseases of cattle, horses, sheep, pigs and goats","authors":[{"name":"O. Radostits"},{"name":"S. Done"}],"abstract":"","source":"Semantic Scholar","year":2007,"language":"en","subjects":["Medicine"],"url":"https://www.semanticscholar.org/paper/f5762b255ff2dca07b4f05a7048307ac07a2a867","is_open_access":true,"citations":2185,"published_at":"","score":81},{"id":"ss_8ba9ff2a1528d7d17169f59a5e2ff30c0d50cb52","title":"Veterinary Medicine: A Textbook of the Diseases of Cattle, Sheep, Pigs, Goats and Horses","authors":[{"name":"D. C. Blood"},{"name":"O. Radostits"},{"name":"J. Arundel"}],"abstract":"","source":"Semantic Scholar","year":1994,"language":"en","subjects":["Biology"],"url":"https://www.semanticscholar.org/paper/8ba9ff2a1528d7d17169f59a5e2ff30c0d50cb52","is_open_access":true,"citations":3364,"published_at":"","score":80},{"id":"ss_3505c8a90a5494426a9ce2dd27c9824bdf33fa9a","title":"Methane emissions from cattle.","authors":[{"name":"Kristen A. Johnson"},{"name":"D. Johnson"},{"name":"D. Johnson"}],"abstract":"","source":"Semantic Scholar","year":1995,"language":"en","subjects":["Environmental Science","Medicine"],"doi":"10.2527/1995.7382483X","url":"https://www.semanticscholar.org/paper/3505c8a90a5494426a9ce2dd27c9824bdf33fa9a","is_open_access":true,"citations":2646,"published_at":"","score":80},{"id":"ss_0cec55696cbdeded5dbef4a1fb3b3372fa64ed4a","title":"Double muscling in cattle due to mutations in the myostatin gene.","authors":[{"name":"A. Mcpherron"},{"name":"Se-Jin Lee"}],"abstract":"","source":"Semantic Scholar","year":1997,"language":"en","subjects":["Biology","Medicine"],"doi":"10.1073/PNAS.94.23.12457","url":"https://www.semanticscholar.org/paper/0cec55696cbdeded5dbef4a1fb3b3372fa64ed4a","pdf_url":"https://europepmc.org/articles/pmc24998?pdf=render","is_open_access":true,"citations":2072,"published_at":"","score":80},{"id":"ss_d5d5326b412ca0560e47d1c206ba60ff4a041593","title":"De novo assembly of the cattle reference genome with single-molecule sequencing","authors":[{"name":"B. Rosen"},{"name":"D. Bickhart"},{"name":"R. Schnabel"},{"name":"S. Koren"},{"name":"C. Elsik"},{"name":"Elizabeth Tseng"},{"name":"T. Rowan"},{"name":"W. Low"},{"name":"A. Zimin"},{"name":"C. Couldrey"},{"name":"R. Hall"},{"name":"Wenli Li"},{"name":"A. Rhie"},{"name":"Jay Ghurye"},{"name":"S. McKay"},{"name":"F. Thibaud-Nissen"},{"name":"J. Hoffman"},{"name":"B. Murdoch"},{"name":"W. Snelling"},{"name":"T. McDaneld"},{"name":"J. Hammond"},{"name":"J. Schwartz"},{"name":"Wilson Nandolo"},{"name":"D. Hagen"},{"name":"Christian Dreischer"},{"name":"Sebastian J. Schultheiss"},{"name":"Steven G. Schroeder"},{"name":"A. Phillippy"},{"name":"J. Cole"},{"name":"Curtis P Van Tassell"},{"name":"G. Liu"},{"name":"T. Smith"},{"name":"J. Medrano"}],"abstract":"Abstract Background Major advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10–12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. Results We present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is \u003e250× more continuous than the original assembly, with contig N50 \u003e25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use. Conclusions We demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Medicine","Art"],"doi":"10.1093/gigascience/giaa021","url":"https://www.semanticscholar.org/paper/d5d5326b412ca0560e47d1c206ba60ff4a041593","pdf_url":"https://academic.oup.com/gigascience/article-pdf/9/3/giaa021/32932931/giaa021.pdf","is_open_access":true,"citations":533,"published_at":"","score":79.99},{"id":"ss_e4072ca35cd1d16881d213e1a9977b07dc370ca6","title":"Highly Pathogenic Avian Influenza A(H5N1) Clade 2.3.4.4b Virus Infection in Domestic Dairy Cattle and Cats, United States, 2024","authors":[{"name":"Eric R. Burrough"},{"name":"Drew R. Magstadt"},{"name":"B. Petersen"},{"name":"Simon J. Timmermans"},{"name":"P. Gauger"},{"name":"Jianqiang Zhang"},{"name":"Chris Siepker"},{"name":"Marta Mainenti"},{"name":"Ganwu Li"},{"name":"Alexis C. Thompson"},{"name":"Patrick J. Gorden"},{"name":"Paul J. Plummer"},{"name":"R. Main"}],"abstract":"We report highly pathogenic avian influenza A(H5N1) virus in dairy cattle and cats in Kansas and Texas, United States, which reflects the continued spread of clade 2.3.4.4b viruses that entered the country in late 2021. Infected cattle experienced nonspecific illness, reduced feed intake and rumination, and an abrupt drop in milk production, but fatal systemic influenza infection developed in domestic cats fed raw (unpasteurized) colostrum and milk from affected cows. Cow-to-cow transmission appears to have occurred because infections were observed in cattle on Michigan, Idaho, and Ohio farms where avian influenza virus–infected cows were transported. Although the US Food and Drug Administration has indicated the commercial milk supply remains safe, the detection of influenza virus in unpasteurized bovine milk is a concern because of potential cross-species transmission. Continued surveillance of highly pathogenic avian influenza viruses in domestic production animals is needed to prevent cross-species and mammal-to-mammal transmission.","source":"Semantic Scholar","year":2024,"language":"en","subjects":["Medicine"],"doi":"10.3201/eid3007.240508","url":"https://www.semanticscholar.org/paper/e4072ca35cd1d16881d213e1a9977b07dc370ca6","is_open_access":true,"citations":396,"published_at":"","score":79.88},{"id":"ss_f165e9bb84fd95477627f0443f5f718367670aa3","title":"Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010","authors":[{"name":"M. Gilbert"},{"name":"Gaëlle Nicolas"},{"name":"G. Cinardi"},{"name":"T. Boeckel"},{"name":"S. Vanwambeke"},{"name":"William Wint"},{"name":"T. Robinson"}],"abstract":"Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables. Design Type(s) data integration objective • parallel group design • process-based data analysis objective Measurement Type(s) livestock abundance Technology Type(s) digital curation Factor Type(s) animal • geographic location Sample Characteristic(s) chicken • cattle • Bovinae • Ovis aries • Capra aegagrus • Equus • Sus • Anatidae • Earth (Planet) • anthropogenic habitat Design Type(s) data integration objective • parallel group design • process-based data analysis objective Measurement Type(s) livestock abundance Technology Type(s) digital curation Factor Type(s) animal • geographic location Sample Characteristic(s) chicken • cattle • Bovinae • Ovis aries • Capra aegagrus • Equus • Sus • Anatidae • Earth (Planet) • anthropogenic habitat Machine-accessible metadata file describing the reported data (ISA-Tab format)","source":"Semantic Scholar","year":2018,"language":"en","subjects":["Geography","Medicine"],"doi":"10.1038/sdata.2018.227","url":"https://www.semanticscholar.org/paper/f165e9bb84fd95477627f0443f5f718367670aa3","pdf_url":"https://www.nature.com/articles/sdata2018227.pdf","is_open_access":true,"citations":565,"published_at":"","score":78.95},{"id":"ss_4f47c1cb42e2c9ebd048389bbbf3277b91dab426","title":"Emergence and interstate spread of highly pathogenic avian influenza A(H5N1) in dairy cattle","authors":[{"name":"Thao-Quyen Nguyen"},{"name":"Carl R. Hutter"},{"name":"Alexey Markin"},{"name":"Megan N. Thomas"},{"name":"Kristina Lantz"},{"name":"M. Killian"},{"name":"Garrett M. Janzen"},{"name":"Sriram Vijendran"},{"name":"Sanket Wagle"},{"name":"Blake Inderski"},{"name":"Drew R. Magstadt"},{"name":"Ganwu Li"},{"name":"D. Diel"},{"name":"Elisha A Frye"},{"name":"K. Dimitrov"},{"name":"A. Swinford"},{"name":"Alexis C. Thompson"},{"name":"Kevin R. Snevik"},{"name":"D. L. Suarez"},{"name":"E. Spackman"},{"name":"Steven M. Lakin"},{"name":"Sara C. Ahola"},{"name":"Kammy R. Johnson"},{"name":"A. Baker"},{"name":"S. Robbe-Austerman"},{"name":"Mia K. Torchetti"},{"name":"T. Anderson"}],"abstract":"Highly pathogenic avian influenza (HPAI) viruses cross species barriers and have the potential to cause pandemics. In North America, HPAI A(H5N1) viruses related to the goose/Guangdong 2.3.4.4b hemagglutinin phylogenetic clade have infected wild birds, poultry, and mammals. Our genomic analysis and epidemiological investigation showed that a reassortment event in wild bird populations preceded a single wild bird-to-cattle transmission episode. The movement of asymptomatic cattle has likely played a role in the spread of HPAI within the United States dairy herd. Some molecular markers in virus populations were detected at low frequency that may lead to changes in transmission efficiency and phenotype after evolution in dairy cattle. Continued transmission of H5N1 HPAI within dairy cattle increases the risk for infection and subsequent spread of the virus to human populations.","source":"Semantic Scholar","year":2024,"language":"en","subjects":["Medicine","Biology"],"doi":"10.1101/2024.05.01.591751","url":"https://www.semanticscholar.org/paper/4f47c1cb42e2c9ebd048389bbbf3277b91dab426","is_open_access":true,"citations":163,"published_at":"","score":72.89},{"id":"ss_99893a00cdb73b99570ef7cb5cf6c3f868107d59","title":"1000 Bull Genomes Project to Map Simple and Complex Genetic Traits in Cattle: Applications and Outcomes.","authors":[{"name":"B. Hayes"},{"name":"H. Daetwyler"}],"abstract":"The 1000 Bull Genomes Project is a collection of whole-genome sequences from 2,703 individuals capturing a significant proportion of the world's cattle diversity. So far, 84 million single-nucleotide polymorphisms (SNPs) and 2.5 million small insertion deletions have been identified in the collection, a very high level of genetic diversity. The project has greatly accelerated the identification of deleterious mutations for a range of genetic diseases, as well as for embryonic lethals. The rate of identification of causal mutations for complex traits has been slower, reflecting the typically small effect size of these mutations and the fact that many are likely in as-yet-unannotated regulatory regions. Both the deleterious mutations that have been identified and the mutations associated with complex trait variation have been included in low-cost SNP array designs, and these arrays are being genotyped in tens of thousands of dairy and beef cattle, enabling management of deleterious mutations in these populations as well as genomic selection.","source":"Semantic Scholar","year":2019,"language":"en","subjects":["Medicine","Biology"],"doi":"10.1146/annurev-animal-020518-115024","url":"https://www.semanticscholar.org/paper/99893a00cdb73b99570ef7cb5cf6c3f868107d59","is_open_access":true,"citations":326,"published_at":"","score":72.78},{"id":"ss_35b0735511fbc8a04976915b35c297bc1112664a","title":"Review: Genetic selection of high-yielding dairy cattle toward sustainable farming systems in a rapidly changing world.","authors":[{"name":"L. Brito"},{"name":"N. Bédère"},{"name":"F. Douhard"},{"name":"H. R. Oliveira"},{"name":"M. Arnal"},{"name":"F. Peñagaricano"},{"name":"A. Schinckel"},{"name":"C. Baes"},{"name":"F. Miglior"}],"abstract":"The massive improvement in food production, as a result of effective genetic selection combined with advancements in farming practices, has been one of the greatest achievements of modern agriculture. For instance, the dairy cattle industry has more than doubled milk production over the past five decades, while the total number of cows has been reduced dramatically. This was achieved mainly through the intensification of production systems, direct genetic selection for milk yield and a limited number of related traits, and the use of modern technologies (e.g., artificial insemination and genomic selection). Despite the great betterment in production efficiency, strong drawbacks have occurred along the way. First, across-breed genetic diversity reduced dramatically, with the worldwide use of few common dairy breeds, as well as a substantial reduction in within-breed genetic diversity. Intensive selection for milk yield has also resulted in unfavorable genetic responses for traits related to fertility, health, longevity, and environmental sensitivity. Moving forward, the dairy industry needs to continue refining the current selection indexes and breeding goals to put greater emphasis on traits related to animal welfare, health, longevity, environmental efficiency (e.g., methane emission and feed efficiency), and overall resilience. This needs to be done through the definition of criteria (traits) that (a) represent well the biological mechanisms underlying the respective phenotypes, (b) are heritable, and (c) can be cost-effectively measured in a large number of animals and as early in life as possible. The long-term sustainability of the dairy cattle industry will also require diversification of production systems, with greater investments in the development of genetic resources that are resilient to perturbations occurring in specific farming systems with lesser control over the environment (e.g., organic, agroecological, and pasture-based, mountain-grazing farming systems). The conservation, genetic improvement, and use of local breeds should be integrated into the modern dairy cattle industry and greater care should be taken to avoid further genetic diversity losses in dairy cattle populations. In this review, we acknowledge the genetic progress achieved in high-yielding dairy cattle, closely related to dairy farm intensification, that reaches its limits. We discuss key points that need to be addressed toward the development of a robust and long-term sustainable dairy industry that maximize animal welfare (fundamental needs of individual animals and positive welfare) and productive efficiency, while also minimizing the environmental footprint, inputs required, and sensitivity to external factors.","source":"Semantic Scholar","year":2021,"language":"en","subjects":["Medicine"],"doi":"10.1016/j.animal.2021.100292","url":"https://www.semanticscholar.org/paper/35b0735511fbc8a04976915b35c297bc1112664a","pdf_url":"https://doi.org/10.1016/j.animal.2021.100292","is_open_access":true,"citations":237,"published_at":"","score":72.11},{"id":"ss_90831636968ae8b55c9df5c7715916bdc602f715","title":"Climate Impacts of Cultured Meat and Beef Cattle","authors":[{"name":"J. Lynch"},{"name":"R. Pierrehumbert"}],"abstract":"Improved greenhouse gas (GHG) emission efficiency of production has been proposed as one of the biggest potential advantages of cultured meat over conventional livestock production systems. Comparisons with beef are typically highlighted, as it is a highly emissions intensive food product. In this study we present a more rigorous comparison of the potential climate impacts of cultured meat and cattle production than has previously been made. Warming impacts are evaluated using a simple climate model that simulates the different behaviours of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), rather than relying on carbon dioxide equivalent (CO2e) metrics. We compare the temperature impact of beef cattle and cultured meat production at all times to 1000 years in the future, using four synthetic meat GHG footprints currently available in the literature and three different beef production systems studied in an earlier climate modelling paper. Cattle systems are associated with the production of all three GHGs above, including significant emissions of CH4, while cultured meat emissions are almost entirely CO2 from energy generation. Under continuous high global consumption, cultured meat results in less warming than cattle initially, but this gap narrows in the long term and in some cases cattle production causes far less warming, as CH4 emissions do not accumulate, unlike CO2. We then model a decline in meat consumption to more sustainable levels following high consumption, and show that although cattle systems generally result in greater peak warming than cultured meat, the warming effect declines and stabilises under the new emission rates of cattle systems, while the CO2 based warming from cultured meat persists and accumulates even under reduced consumption, again overtaking cattle production in some scenarios. We conclude that cultured meat is not prima facie climatically superior to cattle production; its relative impact instead depends on the availability of decarbonised energy generation and the specific production systems that are realised.","source":"Semantic Scholar","year":2019,"language":"en","subjects":["Environmental Science","Medicine"],"doi":"10.3389/fsufs.2019.00005","url":"https://www.semanticscholar.org/paper/90831636968ae8b55c9df5c7715916bdc602f715","pdf_url":"https://www.frontiersin.org/articles/10.3389/fsufs.2019.00005/pdf","is_open_access":true,"citations":285,"published_at":"","score":71.55},{"id":"ss_2b11be802d403d2df7b228607efd5d22815a81ea","title":"Control of antral follicle development and selection in sheep and cattle.","authors":[{"name":"B. Campbell"},{"name":"R. Scaramuzzi"},{"name":"R. Webb"}],"abstract":"The development of antral follicles in sheep and cattle is dependent on FSH, but large antral follicles can shift their gonadotrophic dependence from FSH to LH. The mechanisms that result in the selection of at least one ovulatory follicle from identical follicular cohorts, exposed to the same endocrine environment, still remain to be elucidated. The aim of this research was to extend in vitro results from the rodent to sheep and cattle and, using both in vivo and in vitro models, to identify factors that can enhance or attenuate the action of gonadotrophins in stimulating follicle development. Using sheep with ovarian autotransplants, we have obtained evidence to show that a number of factors inhibit ovarian function in vivo, whereas only insulin-like growth factor I (IGF-I) has a stimulatory effect. Further study of the mechanism of action of these factors at a cellular level has been made possible by the development of a serum-free granulosa cell culture system for both sheep and cattle that allows induction and maintenance of oestradiol production. Using this model system, we have confirmed many of the results from out studies in vivo and have shown that IGF-I and insulin interact at physiological concentrations to influence both cellular proliferation and oestradiol production. Overall, these data support the hypothesis that the physiological basis of follicle selection is the differential expression of factors that modulate the action of gonadotrophins on follicular cells at key points during the process of follicle development.","source":"Semantic Scholar","year":2019,"language":"en","subjects":["Biology","Medicine"],"doi":"10.1530/BIOSCIPROCS.3.026","url":"https://www.semanticscholar.org/paper/2b11be802d403d2df7b228607efd5d22815a81ea","pdf_url":"http://www.biosciproceedings.org/bp/0003/pdf/bp0003rdr26.pdf","is_open_access":true,"citations":285,"published_at":"","score":71.55},{"id":"doaj_10.3390/vetsci13030210","title":"Life Stage-Specific Burdens and Impacts of Gastrointestinal Nematodes in Beef Cattle in the United States: A Review of Diagnostics, Impacts on Productivity, and Immune Response","authors":[{"name":"Brooklyn L. Laubinger"},{"name":"Kelsey M. Harvey"},{"name":"William Isaac Jumper"}],"abstract":"Gastrointestinal nematodes (GINs) remain a significant challenge to productivity and sustainability in beef cattle systems in the United States, contributing to subclinical reductions in growth, reproductive performance, and overall herd health across production stages. Control programs have historically relied on routine anthelmintic use; however, increasing reports of anthelmintic resistance highlight the need for alternative management strategies. This narrative review synthesizes peer-reviewed literature identified through targeted searches of major scientific databases spanning approximately seven decades, with articles selected for relevance to GIN epidemiology, diagnostics, and control in beef cattle. Particular emphasis is placed on life stage-specific susceptibility, host immune development, and the role of diagnostic tools in guiding evidence-based interventions. The review further examines non-anthelmintic strategies such as grazing management, nutritional supplementation, selective breeding, and integrated parasite management practices adapted from small ruminant systems. Across studies, young and immunologically developing cattle experience the greatest productivity losses, while mature animals contribute disproportionately to pasture contamination, reinforcing the importance of targeted control measures. Overall, the literature supports a transition toward integrated, diagnostics-driven parasite control programs that sustain productivity and animal well-being while preserving long-term anthelmintic efficacy.","source":"DOAJ","year":2026,"language":"","subjects":["Veterinary medicine"],"doi":"10.3390/vetsci13030210","url":"https://www.mdpi.com/2306-7381/13/3/210","is_open_access":true,"published_at":"","score":70},{"id":"ss_9d53b212dd36e259ea047c9c3086c8fa4f086ba6","title":"Impact of heat stress on dairy cattle and selection strategies for thermotolerance: a review","authors":[{"name":"S. Cartwright"},{"name":"J. Schmied"},{"name":"N. Karrow"},{"name":"B. Mallard"}],"abstract":"Climate change is a problem that causes many environmental issues that impact the productivity of livestock species. One of the major issues associated with climate change is an increase of the frequency of hot days and heat waves, which increases the risk of heat stress for livestock species. Dairy cattle have been identified as being susceptible to heat stress due to their high metabolic heat load. Studies have shown heat stress impacts several biological processes that can result in large economic consequences. When heat stress occurs, dairy cattle employ several physiological and cellular mechanisms in order to dissipate heat and protect cells from damage. These mechanisms require an increase and diversion in energy toward protection and away from other biological processes. Therefore, in turn heat stress in dairy cattle can lead numerous issues including reductions in milk production and reproduction as well as increased risk for disease and mortality. This indicates a need to select dairy cattle that would be thermotolerant. Various selection strategies to confer thermotolerance have been discussed in the literature, including selecting for reduced milk production, crossbreeding with thermotolerant breeds, selecting based on physiological traits and most recently selecting for enhanced immune response. This review discusses the various issues associated with heat stress in dairy cattle and the pros and cons to the various selection strategies that have been proposed to select for thermotolerance in dairy cattle.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Medicine"],"doi":"10.3389/fvets.2023.1198697","url":"https://www.semanticscholar.org/paper/9d53b212dd36e259ea047c9c3086c8fa4f086ba6","pdf_url":"https://www.frontiersin.org/articles/10.3389/fvets.2023.1198697/pdf","is_open_access":true,"citations":91,"published_at":"","score":69.72999999999999},{"id":"ss_99139ad71acac642ce66a0a352b04c8afa05171b","title":"The Economic Impact of Parasitism from Nematodes, Trematodes and Ticks on Beef Cattle Production","authors":[{"name":"T. Strydom"},{"name":"R. Lavan"},{"name":"Siddhartha Torres"},{"name":"K. Heaney"}],"abstract":"Simple Summary Cattle parasites live inside or on the body of beef cattle. The most common beef parasites include intestinal roundworms, flatworms and ticks. The act of parasitizing cattle reduces the health of the animals and reduces the economic value to the farmer through reduced body weight, milk production, coat and hide quality and ability to give birth to healthy calves. As a result, beef cattle producers lose billions of dollars in the value of their herds each year due to parasitism. Preventing and treating parasites is an important step in increasing the farmers’ ability to raise healthy beef cattle, make a profit and meet the world’s need for sustainable protein and other cattle products. Abstract Global human population growth requires the consumption of more meat such as beef to meet human needs for protein intake. Cattle parasites are a constant and serious threat to the development of the beef cattle industry. Studies have shown that parasites not only reduce the performance of beef cattle, but also negatively affect the profitability of beef agriculture and have many other impacts, including contributing to the production of greenhouse gases. In addition, some zoonotic parasitic diseases may also threaten human health. Therefore, ongoing cattle parasite research is crucial for continual parasite control and the development of the beef cattle industry. Parasitism challenges profitable beef production by reducing feed efficiency, immune function, reproductive efficiency, liveweight, milk yield, calf yield and carcass weight, and leads to liver condemnations and disease transmission. Globally, beef cattle producers incur billions (US$) in losses due to parasitism annually, with gastrointestinal nematodes (GIN) and cattle ticks causing the greatest economic impact. The enormity of losses justifies parasitic control measures to protect profits and improve animal welfare. Geographical differences in production environment, management practices, climate, cattle age and genotype, parasite epidemiology and susceptibility to chemotherapies necessitate control methods customized for each farm. Appropriate use of anthelmintics, endectocides and acaricides have widely been shown to result in net positive return on investment. Implementing strategic parasite control measures, with thorough knowledge of parasite risk, prevalence, parasiticide resistance profiles and prices can result in positive economic returns for beef cattle farmers in all sectors.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Medicine"],"doi":"10.3390/ani13101599","url":"https://www.semanticscholar.org/paper/99139ad71acac642ce66a0a352b04c8afa05171b","pdf_url":"https://www.mdpi.com/2076-2615/13/10/1599/pdf?version=1683704546","is_open_access":true,"citations":82,"published_at":"","score":69.46000000000001},{"id":"arxiv_2510.09203","title":"Cattle-CLIP: A Multimodal Framework for Cattle Behaviour Recognition","authors":[{"name":"Huimin Liu"},{"name":"Jing Gao"},{"name":"Daria Baran"},{"name":"AxelX Montout"},{"name":"Neill W Campbell"},{"name":"Andrew W Dowsey"}],"abstract":"Cattle behaviour is a crucial indicator of an individual animal health, productivity and overall well-being. Video-based monitoring, combined with deep learning techniques, has become a mainstream approach in animal biometrics, and it can offer high accuracy in some behaviour recognition tasks. We present Cattle-CLIP, a multimodal deep learning framework for cattle behaviour recognition, using semantic cues to improve the performance of video-based visual feature recognition. It is adapted from the large-scale image-language model CLIP by adding a temporal integration module. To address the domain gap between web data used for the pre-trained model and real-world cattle surveillance footage, we introduce tailored data augmentation strategies and specialised text prompts. Cattle-CLIP is evaluated under both fully-supervised and few-shot learning scenarios, with a particular focus on data-scarce behaviour recognition - an important yet under-explored goal in livestock monitoring. To evaluate the proposed method, we release the CattleBehaviours6 dataset, which comprises six types of indoor behaviours: feeding, drinking, standing-self-grooming, standing-ruminating, lying-self-grooming and lying-ruminating. The dataset consists of 1905 clips collected from our John Oldacre Centre dairy farm research platform housing 200 Holstein-Friesian cows. Experiments show that Cattle-CLIP achieves 96.1% overall accuracy across six behaviours in a supervised setting, with nearly 100% recall for feeding, drinking and standing-ruminating behaviours, and demonstrates robust generalisation with limited data in few-shot scenarios, highlighting the potential of multimodal learning in agricultural and animal behaviour analysis.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CV"],"url":"https://arxiv.org/abs/2510.09203","pdf_url":"https://arxiv.org/pdf/2510.09203","is_open_access":true,"published_at":"2025-10-10T09:43:12Z","score":69},{"id":"arxiv_2501.05209","title":"MHAFF: Multi-Head Attention Feature Fusion of CNN and Transformer for Cattle Identification","authors":[{"name":"Rabin Dulal"},{"name":"Lihong Zheng"},{"name":"Muhammad Ashad Kabir"}],"abstract":"Convolutional Neural Networks (CNNs) have drawn researchers' attention to identifying cattle using muzzle images. However, CNNs often fail to capture long-range dependencies within the complex patterns of the muzzle. The transformers handle these challenges. This inspired us to fuse the strengths of CNNs and transformers in muzzle-based cattle identification. Addition and concatenation have been the most commonly used techniques for feature fusion. However, addition fails to preserve discriminative information, while concatenation results in an increase in dimensionality. Both methods are simple operations and cannot discover the relationships or interactions between fusing features. This research aims to overcome the issues faced by addition and concatenation. This research introduces a novel approach called Multi-Head Attention Feature Fusion (MHAFF) for the first time in cattle identification. MHAFF captures relations between the different types of fusing features while preserving their originality. The experiments show that MHAFF outperformed addition and concatenation techniques and the existing cattle identification methods in accuracy on two publicly available cattle datasets. MHAFF demonstrates excellent performance and quickly converges to achieve optimum accuracy of 99.88% and 99.52% in two cattle datasets simultaneously.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CV"],"url":"https://arxiv.org/abs/2501.05209","pdf_url":"https://arxiv.org/pdf/2501.05209","is_open_access":true,"published_at":"2025-01-09T13:00:01Z","score":69}],"total":494058,"page":1,"page_size":20,"sources":["CrossRef","arXiv","DOAJ","Semantic Scholar"],"query":"Cattle"}