This EnviroAtlas dataset summarizes by county the number of farm operations with cattle and the number of heads they manage. The data come from the Census of Agriculture, which is administered every five years by the US Department of Agriculture (USDA), and include the years 2002, 2007, 2012, and 2017. The Census classifies cattle managed on operations as beef cows, dairy cows, or other cattle (which encompasses heifers, steers, bulls, and calves). Data regarding all three categories are displayed in this layer. Operations are categorized into small, medium, or large, based on how many heads they manage. For each county and Census year, the dataset reports the number of farm operations that manage cattle, the number of heads on their property at the end of the Census year, and a breakdown of the operations into small, medium, and large. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

The Census of Agriculture, produced by the United States Department of Agriculture (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 2022, and provides an in-depth look at the agricultural industry. This layer was produced from data obtained from the USDA National Agriculture Statistics Service (NASS) Large Datasets download page. The data were transformed and prepared for publishing using the Pivot Table geoprocessing tool in ArcGIS Pro and joined to county boundaries. The county boundaries are 2022 vintage and come from Living Atlas ACS 2022 feature layers.Dataset SummaryPhenomenon Mapped: Cattle productionGeographic Extent: 48 contiguous United States, Alaska, Hawaii, and Puerto RicoProjection: Web Mercator Auxiliary SphereSource: USDA National Agricultural Statistics ServiceUpdate Frequency: 5 yearsData Vintage: 2022Publication Date: April 2024AttributesNote that some values are suppressed as "Withheld to avoid disclosing data for individual operations", "Not applicable", or "Less than half the rounding unit". These have been coded in the data as -999, -888, and -777 respectively. You should account for these values when symbolizing or doing any calculations.Many cattle production commodity fields are broken out into 6 or 7 ranges based on the number of head of cattle. For space reasons, a general sample of the fields is listed here.Commodities included in this layer: Cattle, (Excl Cows) - Inventory - Inventory of Cattle, (Excl Cows): (By number of head)Cattle, (Excl Cows) - InventoryCattle, (Excl Cows) - Operations with Inventory - Inventory of Cattle, (Excl Cows): (By number of head)Cattle, (Excl Cows) - Operations with InventoryCattle, Calves - Operations with Sales - Sales of Calves: (By number of head)Cattle, Calves - Operations with SalesCattle, Calves - Sales, Measured in Head - Sales of Calves: (By number of head)Cattle, Calves - Sales, Measured in HeadCattle, Calves, Veal, Raised or Sold - Number of OperationsCattle, Cows - Inventory; Cattle, Cows - Operations with InventoryCattle, Cows, Beef - Inventory - Inventory of Beef Cows: (By number of head)Cattle, Cows, Beef - InventoryCattle, Cows, Beef - Operations with Inventory - Inventory of Beef Cows: (By number of head)Cattle, Cows, Beef - Operations with InventoryCattle, Cows, Milk - Inventory - Inventory of Milk Cows: (By number of head)Cattle, Cows, Milk - InventoryCattle, Cows, Milk - Operations with Inventory - Inventory of Milk Cows: (By number of head)Cattle, Cows, Milk - Operations with InventoryCattle, >= 500 lbs - Operations with Sales - Sales of Cattle >= 500 lbs: (By number of head)Cattle, >= 500 lbs - Operations with SalesCattle, >= 500 lbs - Sales, Measured in Head - Sales of Cattle >= 500 lbs: (By number of head)Cattle, >= 500 lbs - Sales, Measured in HeadCattle, Heifers, >= 500 lbs, Milk Replacement, Production Contract - Operations with ProductionCattle, Heifers, >= 500 lbs, Milk Replacement, Production Contract - Production, Measured in HeadCattle, Incl Calves - Inventory - Inventory of Cattle, Incl Calves: (By number of head)Cattle, Incl Calves - InventoryCattle, Incl Calves - Operations with Inventory - Inventory of Cattle, Incl Calves: (By number of head)Cattle, Incl Calves - Operations with InventoryCattle, Incl Calves - Operations with Sales - Sales of Cattle, Incl Calves: (By number of head)Cattle, Incl Calves - Operations with SalesCattle, Incl Calves - Sales, Measured in US Dollars ($)Cattle, Incl Calves - Sales, Measured in Head - Sales of Cattle, Incl Calves: (By number of head)Cattle, Incl Calves - Sales, Measured in HeadCattle, On Feed - Inventory - Inventory of Cattle On Feed: (By number of head)Cattle, On Feed - InventoryCattle, On Feed - Operations with Inventory - Inventory of Cattle On Feed: (By number of head)Cattle, On Feed - Operations with InventoryCattle, On Feed - Operations with Sales For Slaughter - Sales of Cattle On Feed: (By number of head)Cattle, On Feed - Operations with Sales For SlaughterCattle, On Feed - Sales For Slaughter, Measured in Head - Sales of Cattle On Feed: (By number of head)Cattle, On Feed - Sales For Slaughter, Measured in HeadCattle, Production Contract, On Feed - Operations with ProductionCattle, Production Contract, On Feed - Production, Measured in HeadGeography NoteIn Alaska, one or more county-equivalent entities (borough, census area, city, municipality) are included in an agriculture census area.What can you do with this layer?This layer is designed for data visualization. Identify features by clicking on the map to reveal the pre-configured pop-up. You may change the field(s) being symbolized. When symbolizing other fields, you will need to update the popup accordingly. Simple summary statistics are supported by this data.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

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.

Live Cattle fell to 231.80 USd/Lbs on September 26, 2025, down 0.11% from the previous day. Over the past month, Live Cattle's price has fallen 3.23%, but it is still 26.10% higher than a year ago, 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 September of 2025.

This dataset provides information on the number of milk cows, production of milk per cow and total milk production by state and region in the United States from the year 1970 to 2021.

This dataset displays the annual import and export figures of cattle to and from the United States. Data is primarily available for Canada and Mexico. These statistics represent the head count of cattle traded.

Feeder Cattle rose to 356.96 USd/Lbs on September 26, 2025, up 0.82% from the previous day. Over the past month, Feeder Cattle's price has fallen 2.31%, but it is still 44.37% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Feeder Cattle - values, historical data, forecasts and news - updated on September of 2025.

The Census of Agriculture provides a detailed picture every five years of U.S. farms and ranches and the people who operate them. Conducted by USDA's National Agricultural Statistics Service, the 2012 Census of Agriculture collected more than six million data items directly from farmers. The Ag Census Web Maps application makes this information available at the county level through a few clicks. The maps and accompanying data help users visualize, download, and analyze Census of Agriculture data in a geospatial context. Resources in this dataset:Resource Title: Ag Census Web Maps. File Name: Web Page, url: https://www.nass.usda.gov/Publications/AgCensus/2012/Online_Resources/Ag_Census_Web_Maps/Overview/index.php/ The interactive map application assembles maps and statistics from the 2012 Census of Agriculture in five broad categories:

Crops and Plants – Data on harvested acreage for major field crops, hay, and other forage crops, as well as acreage data for vegetables, fruits, tree nuts, and berries. Economics – Data on agriculture sales, farm income, government payments from conservation and farm programs, amounts received from loans, a broad range of production expenses, and value of buildings and equipment. Farms – Information on farm size, ownership, and Internet access, as well as data on total land in farms, land use, irrigation, fertilized cropland, and enrollment in crop insurance programs. Livestock and Animals – Statistics on cattle and calves, cows and heifers, milk cows, and other cattle, as well as hogs, sheep, goats, horses, and broilers. Operators – Statistics on hired farm labor, tenure, land rented or leased, primary occupation of farm operator, and demographic characteristics such as age, sex, race/ethnicity, and residence location.

The Ag Census Web Maps application allows you to:

Select a map to display from a the above five general categories and associated subcategories. Zoom and pan to a specific area; use the inset buttons to center the map on the continental United States; zoom to a specific state; and show the state mask to fade areas surrounding the state. Create and print maps showing the variation in a single data item across the United States (for example, average value of agricultural products sold per farm). Select a county and view and download the county’s data for a general category. Download the U.S. county-level dataset of mapped values for all categories in Microsoft ® Excel format.

The environmental impacts of beef cattle production and their effects on the overall sustainability of beef have become a national and international concern. Our objective was to quantify important environmental impacts of beef cattle production in the United States. Surveys and visits of farms, ranches and feedlots were conducted throughout seven regions (Northeast, Southeast, Midwest, Northern Plains, Southern Plains, Northwest and Southwest) to determine common practices and characteristics of cattle production. These data along with other information sources were used to create about 150 representative production systems throughout the country, which were simulated with the Integrated Farm System Model using local soil and climate data. The simulations quantified the performance and environmental impacts of beef cattle production systems for each region. A farm-gate life cycle assessment was used to quantify resource use and emissions for all production systems including traditional beef breeds and cull animals from the dairy industry. Regional and national totals were determined as the sum of the production system outputs multiplied by the number of cattle represented by each simulated system. The average annual greenhouse gas and reactive N emissions associated with beef cattle production over the past five years were determined to be 243 ± 26 Tg carbon dioxide equivalents (CO2e) and 1760 ± 136 Gg N, respectively. Total fossil energy use was found to be 569 ± 53 PJ and blue water consumption was 23.2 ± 3.5 TL. Environmental intensities expressed per kg of carcass weight produced were 21.3 ± 2.3 kg CO2e, 155 ± 12 g N, 50.0 ± 4.7 MJ, and 2034 ± 309 L, respectively. These farm-gate values are being combined with post farm-gate sources of packing, processing, distribution, retail, consumption and waste handling to produce a full life cycle assessment of U.S. beef. This study is the most detailed, yet comprehensive, study conducted to date to provide baseline measures for the sustainability of U.S. beef. Resources in this dataset:Resource Title: Appendix A. Supplementary Data - Tables S1 to S8 (docx). File Name: Web Page, url: https://ars.els-cdn.com/content/image/1-s2.0-S0308521X18305675-mmc1.docx Direct download, docx.

Table S1. Important characteristics of farms and ranches simulated throughout seven regions of the U.S.

Table S2. Important characteristics of representative finishing facilities simulated in seven regions of the U.S.

Table S3. Important characteristics of dairy farms simulated throughout seven regions of the U.S.

Table S4. Summary of 25 years of weather data (daily solar radiation, daily mean temperature, annual precipitation and daily wind speed)1 used to simulate beef cattle operations in each area of the eastern regions.

Table S5. Soil characteristics used for locations simulated across the U.S.

Table S6. Cattle numbers by state and region as obtained or estimated from NASS (2017).

Table S7. Cattle numbers by state and region divided between traditional beef and dairy breeds as obtained or estimated from NASS (2017).

Table S8. Important resource inputs and emissions from representative cow-calf, stocker / background and feedlot operations expressed per unit of final carcass weight (CW) produced.

Beef rose to 302.95 BRL/15KG on September 26, 2025, up 0.31% from the previous day. Over the past month, Beef's price has fallen 2.70%, but it is still 10.61% higher than a year ago, 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 September of 2025.

This data set illustrates the number of cattle, by thousand heads, per country from 1961-2004. A value of -1 means that no data was available. Cattle stock can be further defined as including "all cattle in the country, regardless of place or purpose of their breeding. Cattle figures include the common ox (Bos taurus), zebu, humped ox (Bos indicus), Asiatic ox (subgenus Bibos) and Tibetan yak (Poephagus grunniens)" (Earth Trends). Date Accessed: October 5th, 2007 Source URL: http://earthtrends.wri.org/searchable_db/index.php?step=countries&ccID%5B%5D=0&allcountries=checkbox&theme=8&variable_ID=338&action=select_years

Body conformation traits are directly associated with longevity, fertility, health, and workability in dairy cows and have been under direct genetic selection for many decades in various countries worldwide. The main objectives of this study were to perform genome-wide association studies and functional enrichment analyses for fourteen body conformation traits using imputed high-density single nucleotide polymorphism (SNP) genotypes. The traits analyzed include body condition score (BCS), body depth (BD), bone quality (BQ), chest width (CW), dairy capacity (DC), foot angle (FAN), front legs view (FLV), heel depth (HDe), height at front end (HFE), locomotion (LOC), rear legs rear view (RLRV), rear legs side view (RLSV), stature (ST), and a composite feet and legs score index (FL) of Holstein cows scored in Canada. De-regressed estimated breeding values from a dataset of 39,135 North American Holstein animals were used as pseudo-phenotypes in the genome-wide association analyses. A mixed linear model was used to estimate the SNP effects, which ranged from 239,533 to 242,747 markers depending on the trait analyzed. Genes and quantitative trait loci (QTL) located up to 100 Kb upstream or downstream of the significant SNPs previously cited in the Animal QTLdb were detected, and functional enrichment analyses were performed for the candidate genes identified for each trait. A total of 20, 60, 13, 17, 27, 8, 7, 19, 4, 10, 13, 15, 7, and 13 genome-wide statistically significant SNPs for Bonferroni correction based on independent chromosomal segments were identified for BCS, BD, BQ, CW, DC, FAN, FLV, HDe, HFE, LOC, RLRV, RLSV, ST, and FL, respectively. The significant SNPs were located across the whole genome, except on chromosomes BTA24, BTA27, and BTA29. Four markers (for BCS, BD, HDe, and RLRV) were statistically significant when considering a much stricter threshold for the Bonferroni correction for multiple tests. Moreover, the genomic regions identified overlap with various QTL previously reported for the trait groups of exterior, health, meat and carcass, milk, production, and reproduction. The functional enrichment analyses revealed 27 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously reported as linked to bone development, metabolism, as well as infectious and immunological diseases.

This dataset explores Canada cattle inventories by province as of July 1, 2007. Values by thousand head. Notes: - Bull: An uncastrated male bovine - Heifer: Female cow that has never borne young - Steer: A castrated male bovine Source: Statistics Canada, CANSIM, table (for fee) 003-0032 and Catalogue no. 23-012-X (free). Last modified: 2008-02-14.

Anaplasmosis is a costly livestock disease that persists across the United States and the world. While the traditional control options of feed additives, vaccination, and post-infection antibiotic treatments exist, the highly infectious, often asymptomatic onset of anaplasmosis in cattle makes the optimal combination of disease control measures uncertain. Reducing the infection uncertainty through early detection may help producer management decisions and reduce the economic impact of anaplasmosis. To address this, we calculate the costs of applying a range of anaplasmosis control decisions for a representative cow-calf producer in the United States and extend existing analyses to incorporate early detection through diagnostic testing. We use parameters from extant literature, including for mortality, morbidity, and treatment costs to populate a stochastic, dynamic model. Updating the cost estimates finds that production losses account for the majority of anaplasmosis costs, following previous empirical estimates. Using these estimates in our decision model, the outcomes suggest that diagnostic testing with preventative treatments is the optimal herd management strategy. By further framing our findings in the context of three anaplasmosis infection regions in the United States (endemic, disease free, non-endemic buffer), we show that additional considerations exist, which can make sub-optimal control strategies competitive. Our analysis provides an initial exploration of the economic feasibility of diagnostic testing, while helping to assess the burden of anaplasmosis more accurately.

Purpose: The need to assess the sustainability attributes of the United States beef industry is underscored by its importance to food security locally and globally. A life cycle assessment (LCA) of the US beef value chain was conducted to develop baseline information on the environmental impacts of the industry including metrics of the cradle-to-farm gate (feed production, cow-calf, and feedlot operations) and post-farm gate (packing, case-ready, retail, restaurant, and consumer) segments. Methods: Cattle production (cradle-to-farm gate) data were obtained using the integrated farm system model (IFSM) supported with production data from the Roman L. Hruska US Meat Animal Research Center (USMARC). Primary data for the packing and case-ready phases were obtained from packers that jointly processed nearly 60% of US beef while retail and restaurant primary data represented 8 and 6%, respectively, of each sector. Consumer data were obtained from public databases and literature. The functional unit or consumer benefit (CB) was 1 kg of consumed, boneless, edible beef. The relative environmental impacts of processes along the full beef value chain were assessed using a third party validated BASF Corporation Eco-Efficiency Analysis methodology. Results and discussion: Value chain LCA results indicated that the feed and cattle production phases were the largest contributors to most environmental impact categories. Impact metrics included water emissions (7005 L diluted water eq/CB), cumulative energy demand (1110 MJ/CB), and land use (47.4 m2a eq/CB). Air emissions were acidification potential (726 g SO2 eq/CB), photochemical ozone creation potential (146.5 g C2H4 eq/CB), global warming potential (48.4 kg CO2 eq/CB), and ozone depletion potential (1686 μg CFC11 eq/CB). The remaining metrics calculated were abiotic depletion potential (10.3 mg Ag eq/CB), consumptive water use (2558 L eq/CB), and solid waste (369 g municipal waste eq/CB). Of the relative points adding up to 1 for each impact category, the feed phase contributed 0.93 to the human toxicity potential. Conclusions: This LCA is the first of its kind for beef and has been third party verified in accordance with ISO 14040:2006a and 14044:2006b and 14045:2012 standards. An expanded nationwide study of beef cattle production is now being performed with region-specific cattle production data aimed at identifying region-level benchmarks and opportunities for further improvement in US beef sustainability. Resources in this dataset:Resource Title: Electronic Supplementary Material ESM 1 - Tables S1 to S11 (docx). File Name: Web Page, url: https://static-content.springer.com/esm/art:10.1007/s11367-018-1464-6/MediaObjects/11367_2018_1464_MOESM1_ESM.docx Direct download, docx. Table S1: Feed phase input data (resource use and emissions) from USMARC and IFSM simulations used in the U.S. beef life cycle impact assessment and sources of their life-cycle inventories (LCI). Table S2: Cattle phase input data (resource use and emissions) from USMARC and IFSM simulations in the U.S. beef life cycle impact assessment and the sources of their respective life-cycle inventories (LCI). Table S3: Packing and case-ready phases input data (resource use and emissions) used in the U.S. beef life cycle impact assessment and the sources of their respective life-cycle inventories (LCI). Allocation factor of case-ready (i.e. % packaged at case ready) = 0.63. Table S4: Retail and consumer phases input data (resource use and emissions) used in U.S. beef life cycle impact assessment and their respective life-cycle inventory (LCI) sources. Allocation factor for retail and consumer (i.e. at-home consumption portion of total consumption sold through retail) = 0.47. Table S5: Restaurant phase input data (resource use and emissions) used in U.S. beef life cycle impact assessment and their respective life-cycle inventory (LCI) sources. Allocation factor (i.e. restaurant fraction of total beef consumption) = 0.53. Table S6: Essential raw materials considered in the U.S. beef life cycle impact assessment and respective weighting factors used for the determination of their Abiotic Depletion Potential (ADP). Table S7: Scoring system for toxic properties described by H-phrases for U.S. beef life cycle impact assessment (Landsiedel and Saling (2002) before our modification). Table S8: Land occupation and transformation weighting factors for U.S. beef life cycle impact assessment based on Ecosystem Damage Potentials (EDPs) from the Ecoinvent 2.2 life cycle inventory database (Frischknecht et al. 2005). Table S9: Air emissions and their respective weighting (equivalence) factors used in U.S. beef life cycle impact assessment. Table S10: Solid waste relative disposal costs used in U.S. beef life cycle impact assessment (Klein 2011). Table S11: Water emissions categories and their respective weighting factors based on regional regulatory limits used in the U.S. beef life cycle assessment.

aSingle-step genomic-BLUP was used to obtain marker effects.bGenes linked to clinical mastitis are in bold face. Any genes with start and stop positions within or across the window were considered.Summary of the 10 windows that explained the most of genetic variance for clinical mastitis in US Holstein dairy cows, with a list of annotated genes in the proximity of each window.