United States Cattle Inventory: Cattle & Calves: Cows & Heifers That Have Calved: At the Beginning of the Yr: Milk Cows data was reported at 9,349.300 Head th in 2025. This records an increase from the previous number of 9,346.800 Head th for 2024. United States Cattle Inventory: Cattle & Calves: Cows & Heifers That Have Calved: At the Beginning of the Yr: Milk Cows data is updated yearly, averaging 9,349.300 Head th from Dec 1926 (Median) to 2025, with 17 observations. The data reached an all-time high of 9,450.400 Head th in 2021 and a record low of 9,208.600 Head th in 2014. United States Cattle Inventory: Cattle & Calves: Cows & Heifers That Have Calved: At the Beginning of the Yr: Milk Cows data remains active status in CEIC and is reported by Economic Research Service. The data is categorized under Global Database’s United States – Table US.RI018: Cattle Inventory.

This dataset contains the most up to date version of GLW 4 for the reference year 2020 for the following species: buffalo, cattle, sheep, goats, pigs and chicken. The individual species datasets are available at global extent and 5 minutes of arc resolution (approx. 10 km at the equator).

The fourth version of GLW, compared to the previous ones, reflects the most recently compiled and harmonized subnational livestock distribution data and much more detailed metadata.

The layers contain the density of animals per km², with weight estimated by the Random Forest model. The livestock species modelled include: buffaloes, cattle, chickens, goats, pigs and sheep.

All datasets are licensed through a Creative Commons Attribution 4.0 International License.

References

• Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010

• Income Disparities and the Global Distribution of Intensively Farmed Chicken and Pigs

• Using Random Forest to Improve the Downscaling of Global Livestock Census Data

Data publication: 2024-07-15

Supplemental Information:

Unit: head/pixel or birds/pixel

Data type: Float64

No data value: No data

Spatial resolution: Approximately 10km (0.08333 degrees)

Spatial extent: World

Spatial Reference System (SRS): EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)

Contact points:

Resource Contact: Dominik Wisser (FAO-NSAL)

Metadata Contact: Giuseppina Cinardi (FAO-NSAL)

Data lineage:

Recommentations on data representation

The standard lat/long visualisation of the global raster datasets tends to visually over-represent animal densities in pixels located in northern latitudes as they cover a much lower surface on earth than those close to the equator. Thus, altough the data files are distributed in lat/long, we recommend the use of an equal-area projection for a proper representation of densities of our livestock data.

Resource constraints:

Public-use data under the CC BY-NC-SA 3.0 IGO license.

Online resources:

Buffalo: metadata

Chicken: metadata

Cattle: metadata

Goats: metadata

Pigs: metadata

Sheep: metadata

Data for download: All species density

Data for download: Buffalo density

Data for download: Chicken density

Data for download: Cattle density

Data for download: Goats density

Data for download: Pigs density

Data for download: Sheep density

Whole genome sequence data for Bovidae Bos taurus - beef Angus, 30 animals in total. The data is in "fastq" format. There are two versions of each file because we did paired end sequencing. There are two reads for each of the 210 data lines (a forward and a reverse read) summing to 420 total. A diagram of this is attached. In the diagram, the two reads would correspond to read 1 and read 3. Resources in this dataset:Resource Title: CSU_136201_SampleSheet.csv - list of all Angus sequence files. File Name: CSU_136201_SampleSheet.csvResource Description: This spreadsheet lists all 210 data files associated with the sequencing of these 30 Angus animals Resource Title: Sequence Reads Diagram. File Name: SequenceReads.pngResource Description: There are two reads for each of the 210 data lines (a forward and a reverse read) summing to 420 total. In the diagram, the two reads would correspond to read 1 and read 3.

The Census of Agriculture, produced by the USDA National Agricultural Statistics Service (USDA), provides a complete count of America's farms, ranches and the people who grow our food. The census is conducted every five years, most recently in 2017, and provides an in-depth look at the agricultural industry.This layer summarizes cattle production from the 2017 Census of Agriculture at the county level.This layer was produced from data downloaded using the USDA's QuickStats Application. The data was transformed using the Pivot Table tool in ArcGIS Pro and joined to the county boundary file provided by the USDA. The layer was published as feature layer in ArcGIS Online. Dataset SummaryPhenomenon Mapped: 2017 Cattle ProductionCoordinate System: Web Mercator Auxiliary SphereExtent: 48 Contiguous United States, Alaska, and HawaiiVisible Scale: All ScalesSource: USDA National Agricultural Statistics Service QuickStats ApplicationPublication Date: 2017AttributesThis layer provides values for the following attributes. Note that some values are not disclosed (coded as -1 in the layer) to protect the privacy of producers in areas with limited production.Cattle - Operations with SalesCattle - Sales in US DollarsCattle - Sales in HeadDairy - Operations with SalesDairy - Sales in US DollarsAdditionally attributes of State Name, State Code, County Name and County Code are included to facilitate cartography and use with other layers.What can you do with this layer?This layer can be used throughout the ArcGIS system. Feature layers can be used just like any other vector layer. You can use feature layers as an input to geoprocessing tools in ArcGIS Pro or in Analysis in ArcGIS Online. Combine the layer with others in a map and set custom symbology or create a pop-up tailored for your users. For the details of working with feature layers the help documentation for ArcGIS Pro or the help documentation for ArcGIS Online are great places to start. The ArcGIS Blog is a great source of ideas for things you can do with feature layers. This layer is part of ArcGIS Living Atlas of the World that provides an easy way to find and explore many other beautiful and authoritative layers, maps, and applications on hundreds of topics.

Belgium Number of Livestock: Cows data was reported at 2,240,623.000 Unit in 2022. This records a decrease from the previous number of 2,353,418.000 Unit for 2021. Belgium Number of Livestock: Cows data is updated yearly, averaging 2,596,542.000 Unit from Apr 1997 (Median) to 2022, with 26 observations. The data reached an all-time high of 3,157,095.000 Unit in 1997 and a record low of 2,240,623.000 Unit in 2022. Belgium Number of Livestock: Cows data remains active status in CEIC and is reported by Directorate-General Statistics - Statistics Belgium. The data is categorized under Global Database’s Belgium – Table BE.B012: Number of Livestock.

Live Cattle increased 15.12 USd/Lbs or 7.89% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Live Cattle - values, historical data, forecasts and news - updated on March of 2025.

This dataset contains the digitized treatments in Plazi based on the original journal article Chemyreva, Vasilisa G., Vasilenko, Dmitry V., Perkovsky, Evgeny E. (2024): ‘ Where there are many cattle’ in the Eocene of Ukraine: Review of Ambositra Masner (Hymenoptera, Diapriidae, Ambositrinae) from Rovno amber, with the description of three new species. Zootaxa 5446 (4): 499-516, DOI: 10.11646/zootaxa.5446.4.3, URL: http://dx.doi.org/10.11646/zootaxa.5446.4.3

Livestock may be raised primarily for subsistence or local sales, or may be raised to supply international markets with large quantities of produce. The scale, purpose and nature of livestock enterprises is known as the production system. Ruminant livestock – such as cattle, buffaloes, sheep and goats –generally dependent directly on the environment in which they live for fodder and feed resources though some are raised or finished in feed lots. Their production systems therefore are largely determined by agro-ecology and land-use, but also influenced by capital investment, degree of specialisation and whether they are raised on grasslands, feedlots or as part of mixed crop-livestock farming systems. Seré and Steinfeld (1996) developed a farm-level ruminant systems classification based on the origins of feed, stocking rates, amount of irrigation and length of growing period. Spatial variables were found to proxy these factors and used to cast these systems to a map for the developing world by Thornton et al. (2002). This original map has been continually developed, as described in Robinson et al. (2011), resulting in the current Version 5 of the Global Ruminant Production Systems (GRPS 5). This classification is widely used; finding applications in the fields of food and nutrition security; livelihoods and economic growth; human and animal health and welfare; and natural resources and environment.

The Livestock dataset contains four variables which provide census data for Cattle, Hogs, Horses (horses, donkeys and camels), and Sheep (sheep and goats). These census data are based on 1990 statistics.

See the references for the sources of these data.

China County Data collection contains seven datasets which were compiled in the early 1990s for use as inputs to the DNDC (Denitrification-Decomposition) model at UNH. DNDC is a computer simulation model for predicting carbon (C) and nitrogen (N) biogeochemistry in agricultural ecosystems. The datasets were compiled from multiple Chinese sources and all are at the county scale for 1990. The datasets which comprise this collection are listed below.

1) Agricultural Management 2) Crops 3) N-Deposition 4) Geography and Population 5) Land Use 6) Livestock 7) Soil Properties

Bulgaria Agricultural Production: Livestock: Cattle: ow Cows data was reported at 355,600.000 Unit in 2023. This records a decrease from the previous number of 361,476.000 Unit for 2022. Bulgaria Agricultural Production: Livestock: Cattle: ow Cows data is updated yearly, averaging 358,844.500 Unit from Dec 1992 (Median) to 2023, with 32 observations. The data reached an all-time high of 574,899.000 Unit in 1992 and a record low of 231,953.000 Unit in 2019. Bulgaria Agricultural Production: Livestock: Cattle: ow Cows data remains active status in CEIC and is reported by National Statistical Institute. The data is categorized under Global Database’s Bulgaria – Table BG.B013: Agricultural Production and Other Accounts.

Beef decreased 4.45 BRL/15Kg or 1.40% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Beef - values, historical data, forecasts and news - updated on March of 2025.

Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.

These data is related to the analysis of the article "Spatial Exploration of The Impact of Livestock on Malaria Transmission Using Data from A Cluster Randomized Clinical Trial" (abstract below). Aggregated values of variables considered for the model are presented here. for participants' privacy safety, the full anonymized dataset is only available upon request to the corresponding author.ABSTRACTAfter remarkable success from 2000 to 2015, the progress in reducing the global malaria burden has stalled and even reversed in the last few years according to the World Health Organization. Vector control is currently the single most powerful intervention against malaria, but there is evidence that elimination is not feasible with the available vector controls tools in most settings. As there are ongoing global efforts to develop and test novel methods, zooprophylaxis refers to the use of livestock to divert mosquito vectors away from humans, potentially reducing malaria transmission. However, conflicting evidence highlights the concept of zoopotentiation, where livestock may instead increase vector populations and enhance malaria transmission. This controversy raises ongoing debates about the role of cattle in malaria. Here, we implemented a novel spatial approach to explore the role of cattle on malaria transmission in coastal Kenya. Using data with high granularity from a recent clinical trial, we explore variables beyond ownership. We show that the cattle-to-human ratio measured at 400 and at 500 meters around the household is significantly related to higher odds of testing positive for malaria. Cattle kept within 200 m of households do not impact malaria prevalence. Furthermore, we demonstrate that livestock can and should be considered a contributing environmental factor in malaria transmission and not only a family asset.

Argentina Industrial Production: Cattle Slaughtering data was reported at 1,136.153 Head th in May 2020. This records a decrease from the previous number of 1,165.251 Head th for Apr 2020. Argentina Industrial Production: Cattle Slaughtering data is updated monthly, averaging 1,048.122 Head th from Jan 1994 (Median) to May 2020, with 317 observations. The data reached an all-time high of 1,458.327 Head th in Jul 2009 and a record low of 722.024 Head th in Mar 2008. Argentina Industrial Production: Cattle Slaughtering data remains active status in CEIC and is reported by Ministry of Treasury. The data is categorized under Global Database’s Argentina – Table AR.B010: Industrial Production.

Saliva is easily obtainable from a large number of animals in a noninvasive manner and contains a wide diversity of compounds including hormones, metabolites, and proteins that may be a good source of biomarkers of health and disease. Here we have used a combination of multidimensional prefractionation, targeted, and glycocapture methodologies to profile the bovine salivary proteome. The nontargeted approach used four different separation methodologies consisting of SDS-PAGE, Off-gel fractionation, RP-HPLC, and SCX-HPLC. In the targeted approach, we’ve employed a hypothesis-based methodology by only selecting extracellular proteins from in silico data. Finally, the hydrazide capture methodology not only enabled us to identify formerly N-linked glycoproteins but it also provided a selective enrichment process for the identification of low abundance proteins. Together, the three different approaches identified 402 salivary proteins and 45 N-linked glycoproteins. A large number of these proteins have previously been uncharacterized in bovine saliva. To date, this is the largest global survey of the bovine salivary proteome and expands the potential of the diagnostic utility of this fluid to guide development of experiments seeking biomarkers for health traits (i.e., disease resistance) as well as feed conversion efficiency and productivity traits in dairy and beef cattle.

United States Cattle Production: On Feed data was reported at 11,823.000 Head th in Jan 2025. This records a decrease from the previous number of 11,982.000 Head th for Dec 2024. United States Cattle Production: On Feed data is updated monthly, averaging 11,693.000 Head th from May 2021 (Median) to Jan 2025, with 45 observations. The data reached an all-time high of 12,209.000 Head th in Feb 2022 and a record low of 11,064.000 Head th in Aug 2023. United States Cattle Production: On Feed data remains active status in CEIC and is reported by Economic Research Service. The data is categorized under Global Database’s United States – Table US.RI017: Cattle Production.

No of Animal Slaughtered: Caprine data was reported at 278.000 Head in Jan 2025. This records an increase from the previous number of 72.000 Head for Dec 2024. No of Animal Slaughtered: Caprine data is updated monthly, averaging 83.000 Head from Jan 1998 (Median) to Jan 2025, with 325 observations. The data reached an all-time high of 1,208.000 Head in Jan 2017 and a record low of 0.000 Head in Oct 2024. No of Animal Slaughtered: Caprine data remains active status in CEIC and is reported by Office of Agricultural Studies and Policy. The data is categorized under Global Database’s Chile – Table CL.B030: Livestock Production. [COVID-19-IMPACT]

China Livestock: Number: Cow data was reported at 105,085.102 Unit th in 2023. This records an increase from the previous number of 102,158.520 Unit th for 2022. China Livestock: Number: Cow data is updated yearly, averaging 103,974.569 Unit th from Dec 1989 (Median) to 2023, with 35 observations. The data reached an all-time high of 132,060.000 Unit th in 1995 and a record low of 88,344.899 Unit th in 2016. China Livestock: Number: Cow data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Agriculture Sector – Table CN.RID: Number of Livestock: Large Animals: Cow .