Hasil untuk "Cattle"

R. M. Koch, L. A. Swiger, D. Chambers et al.

R. Gibbs, Jeremy F. Taylor, C. V. Van Tassell et al.

A survey of genetic diversity of cattle suggests two domestication events in Asia and selection by husbandry. Not Just Dinner on Legs Several thousand years ago, human beings realized the virtues of domesticating wild animals as easy meat. Soon other possibilities became apparent, and as revealed in a series of papers in this issue, early pastoralists became selective about breeding for wool, leather, milk, and muscle power. In two papers, Gibbs et al. report on the bovine genome sequence (p. 522; see the cover, the Perspective by Lewin, and the Policy Forum by Roberts) and trace the diversity and genetic history of cattle (p. 528), while Chessa et al. (p. 532) survey the occurrence of endogenous retroviruses in sheep and map their distribution to historical waves of human selection and dispersal across Europe. Finally, Ludwig et al. (p. 485) note the origins of variation in the coat-color of horses and suggest that it is most likely to have been selected for by humans in need of good-looking transport. The imprints of domestication and breed development on the genomes of livestock likely differ from those of companion animals. A deep draft sequence assembly of shotgun reads from a single Hereford female and comparative sequences sampled from six additional breeds were used to develop probes to interrogate 37,470 single-nucleotide polymorphisms (SNPs) in 497 cattle from 19 geographically and biologically diverse breeds. These data show that cattle have undergone a rapid recent decrease in effective population size from a very large ancestral population, possibly due to bottlenecks associated with domestication, selection, and breed formation. Domestication and artificial selection appear to have left detectable signatures of selection within the cattle genome, yet the current levels of diversity within breeds are at least as great as exists within humans.

E. Davidson, L. Verchot, I. Ackerman

L. Schaeffer

T. Mader, M. Davis, T. Brown-Brandl

T. Nagaraja, E. Titgemeyer

B. Hoffmann, M. Scheuch, D. Höper et al.

In 2011, an unidentified disease in cattle was reported in Germany and the Netherlands. Clinical signs included fever, decreased milk production, and diarrhea. Metagenomic analysis identified a novel orthobunyavirus, which subsequently was isolated from blood of affected animals. Surveillance was initiated to test malformed newborn animals in the affected region.

D. Purfield, D. Berry, S. McParland et al.

BackgroundRuns of homozygosity (ROH) are contiguous lengths of homozygous genotypes that are present in an individual due to parents transmitting identical haplotypes to their offspring. The extent and frequency of ROHs may inform on the ancestry of an individual and its population. Here we use high density (n = 777,962) bi-allelic SNPs in a range of cattle breed samples to correlate ROH with the pedigree-based inbreeding coefficients and to validate subsequent analyses using 54,001 SNP genotypes. This study provides a first testing of the inference drawn from ROH through comparison with estimates of inbreeding from calculations based on the detailed pedigree data available for several breeds.ResultsAll animals genotyped on the HD panel displayed at least one ROH that was between 1–5 Mb in length with certain regions of the genome more likely to be involved in a ROH than others. Strong correlations (r = 0.75, p  0.5 KB and suggests that in the absence of an animal’s pedigree data, the extent of a genome under ROH may be used to infer aspects of recent population history even from relatively few samples.ConclusionsOur findings suggest that ROH are frequent across all breeds but differing patterns of ROH length and burden illustrate variations in breed origins and recent management.

Phoenix Yu, Tilo Burghardt, Andrew W Dowsey et al.

Holstein-Friesian detection and re-identification (Re-ID) methods capture individuals well when targets are spatially separate. However, existing approaches, including YOLO-based species detection, break down when cows group closely together. This is particularly prevalent for species which have outline-breaking coat patterns. To boost both effectiveness and transferability in this setting, we propose a new detect-segment-identify pipeline that leverages the Open-Vocabulary Weight-free Localisation and the Segment Anything models as pre-processing stages alongside Re-ID networks. To evaluate our approach, we publish a collection of nine days CCTV data filmed on a working dairy farm. Our methodology overcomes detection breakdown in dense animal groupings, resulting in a 98.93% accuracy. This significantly outperforms current oriented bounding box-driven, as well as SAM species detection baselines with accuracy improvements of 47.52% and 27.13%, respectively. We show that unsupervised contrastive learning can build on this to yield 94.82% Re-ID accuracy on our test data. Our work demonstrates that Re-ID in crowded scenarios is both practical as well as reliable in working farm settings with no manual intervention. Code and dataset are provided for reproducibility.

D. Alexander, J. D. Ferguson, A. Glatzle et al.

Methane emissions by livestock have a negligible effect on Earth's temperature. For example, killing all of the approximately 1.6 billion cattle on Earth in the year 2025, when this paper was written, would only reduce atmospheric methane concentrations enough to change the temperature by -0.04 C. Killing all 1.3 billion sheep would lead to a temperature change of -0.004 C. New Zealand's pledge to reduce methane emissions of their livestock by 14% to 24% from those in the year 2017 would change the temperature by -0.000005 to -0.000008 C, far too small to measure. These are maximum temperature savings where methane emissions from domestic livestock are not replaced by other sources (such as wild ruminants and termites) during the inevitable rewilding of managed grasslands and rangelands.

Samantha M. Lawler, Michele T. Bannister, Laura E. Revell

The commercial space industry is launching more satellites into Low Earth Orbit every year. Aotearoa New Zealand (NZ) has a thriving dairy and cattle industry. Unfortunately, these industries could come into (high speed) cow-llision, as the rapid launch rate and short operational lifetimes of satellites in megaconstellations like Starlink result in a high reentry rate at NZ's latitudes. This could intersect with NZ's famously large population of livestock. We predict this will be an udder disaster for any cows that are hit, as they are squishy and moo-ve much more slowly than space debris. Using a global bovine density dataset, previously published satellite casualty probability code, and a complete lack of funding to do this calculation carefully enough for submission to a peer-reviewed journal, we calculate a $\simeq 0.3-1% chance of a cow-sualty in NZ from reentering Starlink Gen2 debris over the next 5 years.

Van-Ba Hoa, Won-Seo Park, Ja-Yeon Yoo et al.

Abstract Increasing the use and cycling of meat by-products is essential to increase economic benefits and reduce environmental pollution. Among the meat by-products, bones are widely used as food for human consumption and are important raw materials in other related industries (e.g., pharmaceuticals). However, their shelf-life during storage and nutritional composition have not been evaluated. The main objective of this study was to assess the collagen content, amino acid and fatty acid composition, and shelf-life of bones during refrigerated storage. For this study, the leg, brisket, and pelvic bones of Hanwoo cattle collected 24 h after slaughter were used. The bones were prepared into 1 cm thick pieces, placed on trays, overwrapped with plastic film, and stored at 4 °C for 21 days. The samples were then analyzed for aerobic plate count (APC), color, total volatile basic nitrogen (TVBN), lipid oxidation, collagen, amino acid, and fatty acid composition. After 21 d of storage, the APC increased faster in brisket bone (by 5.67 log10 CFU/cm2). Brisket bone also showed a faster increase in TVBN (by 16.79 mg/100 g) and TBARS (by 4.08 mg malondialdehyde/kg) compared to other remaining bones after 21 d of storage. The a* (redness) values significantly decreased with increased storage time in all the bones. The total collagen and essential amino acid contents ranged among the bones from 7.09 to 7.54 g/100 g and 501.92 to 853.20 mg/100 g, respectively. The unsaturated fatty acid (UFA) content among the bones varied from 46.75% to 52.38%.

J. Decker, S. McKay, M. Rolf et al.

The domestication and development of cattle has considerably impacted human societies, but the histories of cattle breeds and populations have been poorly understood especially for African, Asian, and American breeds. Using genotypes from 43,043 autosomal single nucleotide polymorphism markers scored in 1,543 animals, we evaluate the population structure of 134 domesticated bovid breeds. Regardless of the analytical method or sample subset, the three major groups of Asian indicine, Eurasian taurine, and African taurine were consistently observed. Patterns of geographic dispersal resulting from co-migration with humans and exportation are recognizable in phylogenetic networks. All analytical methods reveal patterns of hybridization which occurred after divergence. Using 19 breeds, we map the cline of indicine introgression into Africa. We infer that African taurine possess a large portion of wild African auroch ancestry, causing their divergence from Eurasian taurine. We detect exportation patterns in Asia and identify a cline of Eurasian taurine/indicine hybridization in Asia. We also identify the influence of species other than Bos taurus taurus and B. t. indicus in the formation of Asian breeds. We detect the pronounced influence of Shorthorn cattle in the formation of European breeds. Iberian and Italian cattle possess introgression from African taurine. American Criollo cattle originate from Iberia, and not directly from Africa with African ancestry inherited via Iberian ancestors. Indicine introgression into American cattle occurred in the Americas, and not Europe. We argue that cattle migration, movement and trading followed by admixture have been important forces in shaping modern bovine genomic variation.

Gemma Team, Aishwarya Kamath, Johan Ferret et al.

We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters. This version introduces vision understanding abilities, a wider coverage of languages and longer context - at least 128K tokens. We also change the architecture of the model to reduce the KV-cache memory that tends to explode with long context. This is achieved by increasing the ratio of local to global attention layers, and keeping the span on local attention short. The Gemma 3 models are trained with distillation and achieve superior performance to Gemma 2 for both pre-trained and instruction finetuned versions. In particular, our novel post-training recipe significantly improves the math, chat, instruction-following and multilingual abilities, making Gemma3-4B-IT competitive with Gemma2-27B-IT and Gemma3-27B-IT comparable to Gemini-1.5-Pro across benchmarks. We release all our models to the community.

Sima Farokhnejad, Angélica S. da Mata, Mariana Macedo et al.

Commodities, including livestock, flow through trade networks globally, with trajectories that can be effectively captured using mobility pattern modelling approaches similar to those used in human mobility studies. However, documenting these movements comprehensively presents significant challenges; it can be unrealistic, costly, and may conflict with data protection regulations. As a result, mobility datasets typically contain uncertainties due to sparsity and limitations in data collection. Origin-destination (OD) representations offer a powerful framework for modelling movement patterns and are widely adopted in mobility studies. However, these matrices possess inherent limitations: locations absent from the OD framework lack spatial information on potential mobility directions and intensities. This spatial incompleteness creates analytical gaps across different geographical scales, constraining our ability to characterise movement patterns in underrepresented areas. In this study, we introduce a vector-field-based method to address these data challenges, transforming OD data into vector fields capturing spatial flow patterns comprehensively enabling us to study mobility directions solidly. We use cattle trade data from Minas Gerais, Brazil, as our case study for commodity flows. This region's large livestock trading network makes it an ideal test case. Cattle movements are significant as they affect disease transmission, including foot-and-mouth disease. Accurately modelling these flows allows better surveillance and control strategies. Our vector-field approach reveals fundamental patterns in commodity mobility and can infer movement information for unrepresented locations. Our approach offers an alternative to traditional network-based models, enhancing our capacity to infer mobility patterns from incomplete datasets and advancing our understanding of large-scale commodity trades.

Surya Jayakumar, Kieran Sullivan, John McLaughlin et al.

This study introduces a novel data-driven framework and the first-ever county-scale application of Spatio-Temporal Graph Neural Networks (STGNN) to forecast composite sustainability indices from herd-level operational records. The methodology employs a novel, end-to-end pipeline utilizing a Variational Autoencoder (VAE) to augment Irish Cattle Breeding Federation (ICBF) datasets, preserving joint distributions while mitigating sparsity. A first-ever pillar-based scoring formulation is derived via Principal Component Analysis, identifying Reproductive Efficiency, Genetic Management, Herd Health, and Herd Management, to construct weighted composite indices. These indices are modelled using a novel STGNN architecture that explicitly encodes geographic dependencies and non-linear temporal dynamics to generate multi-year forecasts for 2026-2030.

Seval Eliş

Sustainable agriculture necessitates the exploration of organic fertilizers to promote both crop productivity and soil health. The objective of this two-year study was to evaluate the effects of different combinations of processed cattle manure on the yield and quality of cotton crops, with a focus on determining the optimal dosage of these fertilizers. Parameters including seed cotton yield, lint yield, ginning percentage, and physiological traits such as chlorophyll content and normalized difference vegetation index (NDVI) were analyzed. Results revealed significant differences in yield and physiological traits among fertilizer treatments. Notably, combinations involving cattle manure as base fertilizer exhibited superior performance compared to synthetic fertilizer alone. The application of 230 kg da-1 of cattle manure as base fertilizer, in particular, resulted in optimal yield and quality, highlighting the potential of organic fertilizers in enhancing crop productivity. While synthetic fertilizers tended to enhance chlorophyll content, cattle manure applications promoted a more balanced improvement in yield components without compromising plant vigor. Integrating processed cattle manure into fertilizer regimes emerges as a promising strategy for sustainable cotton production. The dose of processed manure fertilizer will provide ten times less use than the dose of normal manure fertilizer. This will make the use of manure fertilizers more active and the use of organic fertilizers more widespread.

Carlos Navarro Marcos, Mónica Gutiérrez-Rivas, Idoia Goiri et al.

Abstract Enteric methane production in ruminants is a major environmental concern, yet its association with the ruminal virome remains largely unexplored. Here, we conduct a bioinformatic analysis on previously published ruminal metagenomes from 448 Holstein cows to investigate the virome and its association with methane production. We identify 8933 viral operational taxonomic units (vOTUs), including bacteriophages, archaeophages, megaviruses, and virophages. Differences between high- and low-emitting cows are observed. Low emitters show greater abundance (mean log-FC = 0.72, P adj  ≤ 0.049) of some vOTUs infecting bacteria like Prevotella, whereas greater abundance (mean log-FC = 0.70, P adj  ≤ 0.047) of archaeophages and megaviruses infecting Methanobrevibacter, ciliates, and fungi, all microorganisms linked to methane production, are observed in high emitters. Associations between viruses and microorganisms might suggest viruses influence methane emissions by modulating key microbial populations. Although mechanisms remain unclear, rumen viruses could serve as biomarkers for selecting low-emission animals or developing microbial interventions.

Silvia García-Méndez, Francisco de Arriba-Pérez, María del Carmen Somoza-López

Artificial Intelligence (AI) can potentially transform the industry, enhancing the production process and minimizing manual, repetitive tasks. Accordingly, the synergy between high-performance computing and powerful mathematical models enables the application of sophisticated data analysis procedures like Machine Learning. However, challenges exist regarding effective, efficient, and flexible processing to generate valuable knowledge. Consequently, this work comprehensively describes industrial challenges where AI can be exploited, focusing on the dairy industry. The conclusions presented can help researchers apply novel approaches for cattle monitoring and farmers by proposing advanced technological solutions to their needs.