How many cattle are in the world? The global live cattle population amounted to about 1.57 billion heads in 2023, up from approximately 1.51 million in 2021. Cows as livestock The domestication of cattle began as early as 10,000 to 5,000 years ago. From ancient times up to the present, cattle are bred to provide meat and dairy. Cattle are also employed as draft animals to plow the fields or transport heavy objects. Cattle hide is used for the production of leather, and dung for fuel and agricultural fertilizer. In 2022, India was home to the highest number of milk cows in the world. Cattle farming in the United States Cattle meat such as beef and veal is one of the most widely consumed types of meat across the globe, and is particularly popular in the United States. The United States is the top producer of beef and veal of any country worldwide. In 2021, beef production in the United States reached 12.6 million metric tons. Beef production appears to be following a positive trend in the United States. More than 33.07 million cattle were slaughtered both commercially and in farms annually in the United States in 2019, up from 33 million in the previous year.

West Bengal had the highest cattle population across India, at about 19 million in 2019. Uttar Pradesh ranked second that year, followed by Madhya Pradesh. Cattle population across the country grew by 0.8 percent between 2012 and 2019. Furthermore, livestock population amounted to nearly 535.8 million with cattle, buffaloes and goats making up the largest share.

In 2017, the state of Pahang had the most amount of beef cattle in Malaysia, amounting to ***** thousand. Malaysia's beef cattle production had been declining in the past few years, and has not been able to meet its increasing beef consumption demand.

Data from: United States Cattle Market Location and Annual Market Sales Estimate Data

Overview

This dataset contains information on cattle market locations and estimated annual cattle sales in the United States from 2012 to 2016. The data were compiled to enhance the understanding of cattle market dynamics and improve modeling efforts related to livestock movement and disease spread.

Repository Contents

• MarketList_final.csv: Contains detailed information about each cattle market, including location data and unique identifiers.
• Market_Volume_Estimates.csv: Provides county-level annual cattle sales estimates, including known and predicted values where data were not available.

Data Description

MarketList_final.csv

• RecordID: Unique identifier for each record (matches MarketID column in the Carroll and Bansal de-duplicated market list).
• premises.CB: Premises designations from Carroll and Bansal [1].
• premises.Beck-Johnson: Corrected premises designations.
• FI...

California was the leading U.S. state in terms of the overall number of milk cows, with a total of over 1.7 million milk cows as of 2024. The total number of milk cows on farms in the United States shows that California holds a significant share of the total number of milk cows in the country. Unsurprisingly, California is also the leading milk producing state in the United States. Dairy industry in the U.S. According to the USDA, milk from U.S. farms is 90 percent water, with milk fat and skim solids making up the remaining 10 percent. Cow milk is a component of several dietary staples, such as cheese, butter, and yoghurt. Dairy is a very important industry in the United States, with this sector alone creating significant employment throughout the United States. The overall income of dairy farms in the U.S. amounted to about 51.3 billion U.S. dollars. Holtsein is the most popular breed of dairy cow farmed in the United States. Holstein have the highest milk production per cow in comparison to any other breed. Where is the U.S. positioned in the global dairy market? Topped only by the EU-27, the United States ranks as the second largest cow milk producer in the world, followed by India, Russia, and China. The United States also features among the top ten global milk exporters. The outlook for the future of the industry is also good, with milk production in the United States projected to steadily increase over the next years.

The dataset contains year-, state-, region- and breed-wise compiled census data on livestock animals such as Bovine, Buffalo, Cattle, Sheep, Goats, Mules, Donkeys, Mithun, Pig, Camels, Horses, Ponies, Yak , etc. and poultry birds such as Cock, Hen, Chicken, Quail, Turkey, Layer, Broiler, Duck, Ducklings, Emu, Ostrich, etc., by their different breeds such as desi, exotic, indigenous, improved, etc., during the period of 2012 to 2019. The dataset also contains separate data on population of stray cattle and dogs

This dataset provides livestock data for US Counties within the contiguous US. Census data of cattle, poultry (fowl), hogs, horses and sheep are provided. These data are estimated counts for 1990 based on an average of 1987 and 1992 census data from US Dept. of Agriculture (USDA) Natural Resources Conservation Service (NRCS) and the US Census Bureau.

EOS-WEBSTER provides seven datasets which provide county-level data on agricultural management, crop production, livestock, soil properties, geography and population. These datasets were assembled during the mid-1990's to provide driving variables for an assessment of greenhouse gas production from US agriculture using the DNDC agro-ecosystem model [see, for example, Li et al. (1992), J. Geophys. Res., 97:9759-9776; Li et al. (1996) Global Biogeochem. Cycles, 10:297-306]. The data (except nitrogen fertilizer use) were all derived from publicly available, national databases. Each dataset has a separate DIF.

The US County data has been divided into seven datasets.

US County Data Datasets:

1) Agricultural Management 2) Crop Data (NASS Crop data) 3) Crop Summary (NASS Crop data) 4) Geography and Population 5) Land Use 6) Livestock Populations 7) Soil Properties

How many cows are in the U.S.? The United States is home to approximately **** million cattle and calves as of 2024, dropping slightly from the 2023 value. Cattle farming in the United States There are over ***** times more beef cows than milk cows living in the United States. Raising cattle is notoriously expensive, not only in terms of land, feed, and equipment, but also in terms of the environmental impact of consuming beef. Beef and milk have the highest carbon footprints of any type of food in the United States. U.S. milk market The volume of milk produced in the United States has been steadily increasing over the last several years. In 2023, total milk production in the U.S. was about ***** billion pounds, up from ***** billion pounds in 2010. ********** is the leading producer of milk of any U.S. state, generating approximately ** billion pounds of milk in 2022. Wisconsin came in second, producing about **** billion pounds of milk in that year.

The US beef cattle production industry is currently marked by tight supply conditions and elevated prices. Over recent years, persistent drought conditions have led to significant herd liquidation, with beef cow numbers falling to historic lows. This contraction has created a bottleneck in calf production and feeder cattle availability, sustaining high cattle prices. In tandem, elevated feed costs have pressured prices upwards and profit down, driving revenue as cattle producers seek to pass on costs and prevent further profit declines. As herd rebuilding has remained slow, cattle supplies have remained low and kept prices high even as feed, energy and other key agricultural input costs have declined from their highs in 2022. Industry revenue has grown at a CAGR of 6.0% during the current period to reach an estimated $95.9 billion after declining by 2.4% in 2025 as reduced consumption and supplies limit sales. Consumer preferences are shifting in the beef cattle production industry. There is an increasing awareness of environmental and health-related concerns associated with beef consumption. Consequently, many consumers are reducing their intake of conventional beef, turning instead towards more sustainable options and alternatives that are perceived as healthier or higher quality, such as grass-fed and organic beef. This shift has spurred growth in these segments as consumers look for transparency and ethical farming practices. Retailers and restaurants have responded accordingly by offering more options that align with these consumer preferences. However, these trends also pose challenges, especially for smaller producers who face significant costs associated with transitioning to sustainable practices or achieving certifications like organic or "sustainably raised." Though opportunities for growth will continue to present themselves, the outlook for the industry as a whole does not look as positive in the next five years. Poultry, pork and plant-based proteins will threaten beef demand as they appeal to health-conscious customers, particularly as cattle prices are elevated. Climate change will also continue to introduce environmental pressures, demanding resilience and adaptability from producers. Periods of stable weather could facilitate herd rebuilding, leading to increased cattle supplies and dropping prices, but continued climatic fluctuations and extreme weather events could reduce the consistency of production and increase revenue volatility. Advancements in technology, such as drones and wearable sensors, promise to help optimize cattle management, improving operational efficiencies and animal welfare. These innovations, however, require investment and broader accessibility through government support to ensure equitable adoption across the industry. Additionally, while global trade disruptions remain a concern due to disease outbreaks and geopolitical tensions, US producers will have opportunities in niche market segments to differentiate themselves, counterbalancing some of these pressures. Overall, revenue for cattle producers is forecast to decline through 2030 at a CAGR of 0.4% to $94.0 billion.

[NOTE - 11/24/2021: this dataset supersedes an earlier version https://doi.org/10.15482/USDA.ADC/1518654 ] Data sources. Time series data on cattle fever tick incidence, 1959-2020, and climate variables January 1950 through December 2020, form the core information in this analysis. All variables are monthly averages or sums over the fiscal year, October 01 (of the prior calendar year, y-1) through September 30 of the current calendar year (y). Annual records on monthly new detections of Rhipicephalus microplus and R. annulatus (cattle fever tick, CFT) on premises within the Permanent Quarantine Zone (PQZ) were obtained from the Cattle Fever Tick Eradication Program (CFTEP) maintained jointly by the United States Department of Agriculture (USDA), Animal Plant Health Inspection Service and the USDA Animal Research Service in Laredo, Texas. Details of tick survey procedures, CFTEP program goals and history, and the geographic extent of the PQZ are in the main text, and in the Supporting Information (SI) of the associated paper. Data sources on oceanic indicators, on local meteorology, and their pretreatment are detailed in SI. Data pretreatment. To address the low signal-to-noise ratio and non-independence of observations common in time series, we transformed all explanatory and response variables by using a series of six consecutive steps: (i) First differences (year y minus year y-1) were calculated, (ii) these were then converted to z scores (z = (x- μ) / σ, where x is the raw value, μ is the population mean, σ is the standard deviation of the population), (iii) linear regression was applied to remove any directional trends, (iv) moving averages (typically 11-year point-centered moving averages) were calculated for each variable, (v) a lag was applied if/when deemed necessary, and (vi) statistics calculated (r, n, df, P<, p<). Principal component analysis (PCA). A matrix of z-score first differences of the 13 climate variables, and CFT (1960-2020), was entered into XLSTAT principal components analysis routine; we used Pearson correlation of the 14 x 60 matrix, and Varimax rotation of the first two components. Autoregressive Integrated Moving Average (ARIMA). An ARIMA (2,0,0) model was selected among 7 test models in which the p, d, and q terms were varied, and selection made on the basis of lowest RMSE and AIC statistics, and reduction of partial autocorrelation outcomes. A best model linear regression of CFT values on ARIMA-predicted CFT was developed using XLSTAT linear regression software with the objective of examining statistical properties (r, n, df, P<, p<), including the Durbin-Watson index of order-1 autocorrelation, and Cook’s Di distance index. Cross-validation of the model was made by withholding the last 30, and then the first 30 observations in a pair of regressions. Forecast of the next major CFT outbreak. It is generally recognized that the onset year of the first major CFT outbreak was not 1959, but may have occurred earlier in the decade. We postulated the actual underlying pattern is fully 44 years from the start to the end of a CFT cycle linked to external climatic drivers. (SI Appendix, Hypothesis on CFT cycles). The hypothetical reconstruction was projected one full CFT cycle into the future. To substantiate the projected trend, we generated a power spectrum analysis based on 1-year values of the 1959-2020 CFT dataset using SYSTAT AutoSignal software. The outcome included a forecast to 2100; this was compared to the hypothetical reconstruction and projection. Any differences were noted, and the start and end dates of the next major CFT outbreak identified. Resources in this dataset: Resource Title: CFT and climate data. File Name: climate-cft-data2.csv Resource Description: Main dataset; see data dictionary for information on each column Resource Title: Data dictionary (metadata). File Name: climate-cft-metadata2.csv Resource Description: Information on variables and their origin Resource Title: fitted models. File Name: climate-cft-models2.xlsx Resource Software Recommended: Microsoft Excel,url: https://www.microsoft.com/en-us/microsoft-365/excel; XLSTAT,url: https://www.xlstat.com/en/; SYStat Autosignal,url: https://www.systat.com/products/AutoSignal/

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources.

The U.S. Geological Survey (USGS) is developing SPARROW models (SPAtially Related Regressions On Watershed Attributes) to assess the transport of contaminants (e.g., nutrients) through the Pacific drainages of the United States (the Columbia River basin; the coastal drainages of Washington, Oregon, and California; the Klamath River basin; the Central Valley of California, and the west slopes of the Sierra Nevada Mountains). SPARROW relates instream water quality measurements to spatially referenced characteristics of watersheds, including contaminant sources and the factors influencing terrestrial and aquatic transport. The population of livestock within a watershed is a potential factor affecting nutrient delivery to streams. The spatial data set “County-level livestock data for the Pacific drainages of the United States (2012)" summarizes livestock populations and the associated generation of manure nutrients for each county lying partially or fully within Pacific drainages of the United States. This data set was created by combining an existing data set of county-level livestock and manure nutrient data for the United States with regional information on cattle housed in dairies and feedlots.

The dataset contains year-, state-, region-, breed-, gender- and age-group-wise contains compiled data on number of livestock animals and poultry birds by their different types and status of uses such as milk production, dry state, not calved, agriculture, breeding, draught, cart, agriculture operation, sport, commercial or backyard poultry, etc. The livestock animals and poultry birds for which data has been covered include Bovine, Buffalo, Cattle, Sheep, Goats, Mules, Donkeys, Mithun, Pig, Camels, Horses, Ponies, Yak, Cock, Hen, Chicken, Quail, Turkey, Layer, Broiler, Duck, Ducklings, Emu, Ostrich, etc., during the period of 2012 to 2019. The dataset also contains separate data on population of stray cattle and dogs

In the U.S., there have been approximately three times more beef cows than dairy cows each year since 2001. As of 2024, it was estimated that there were about 28 million beef cows and only about 9.3 million dairy cows. Beef vs. dairy cows Both beef and dairy cows are bred for their respective purposes and farmers often look for different qualities in each. Dairy cows are often bigger, as they can produce a larger volume of milk. Beef cows on the other hand are generally shorter and there is more emphasis on their muscle growth, among other qualities. In 2022, over 28 billion pounds of beef were produced in the United States. U.S. milk production and consumption The United States was among the top consumers of milk worldwide in 2022, surpassed only by India and the European Union. The annual consumption of milk in the U.S. that year was just under 21 million metric tons. To keep up with this level of consumption, milk production in the U.S. has increased by over 60 billion pounds since 1999 and is expected to exceed 228 billion pounds by 2023. California and Wisconsin were the top producing states as of 2022, producing about 41.8 and 31.9 billion pounds of milk, respectively.

The dataset contains year-, state-, region- and breed-wise compiled data on total number of livestock animals such as Bovine, Buffalo, Cattle, Sheep, Goats, Mules, Donkeys, Mithun, Pig, Camels, Horses, Ponies, Yak , etc. and poultry birds such as Cock, Hen, Chicken, Quail, Turkey, Layer, Broiler, Duck, Ducklings, Emu, Ostrich, etc., which existed in India during the period of 2012 to 2019. The dataset also contains separate data on population of stray cattle and dogs

The primary greenhouse gas (GHG) sources for agriculture are nitrous oxide (N2O) emissions from cropped and grazed soils, methane (CH4) emissions from ruminant livestock production and rice cultivation, and CH4 and N2O emissions from managed livestock waste. The management of cropped, grazed, and forestland has helped offset GHG emissions by promoting the biological uptake of carbon dioxide (CO2) through the incorporation of carbon into biomass, wood products, and soils, yielding a U.S. net emissions of 5,903 MMT CO2 eq (million metric tonnes of carbon dioxide equivalents). Net emissions equate to total greenhouse gas emissions minus CO2 sequestration in growing forests, wood products, and soils. The report 'U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018' serves to estimate U.S. GHG emissions for the agricultural sector, to quantify uncertainty in emission estimates, and to estimate the potential of agriculture to mitigate U.S. GHG emissions. This dataset contains tabulated data from the figures and tables presented in Chapter 2, Livestock and Grazed Lands Emissions, of the report. This chapter covers carbon dioxide, methane, and nitrous oxide emissions and removals due to enteric fermentation, animal waste management, and land use for confined and grazed animals. Please refer to the report for full descriptions of and notes on the data. Resources in this dataset:Resource Title: Table 2-1. File Name: Table2_1.csvResource Description: Greenhouse Gas Emission Estimates and Uncertainty in the United States, 2018 for enteric fermentation, managed waste, grazed land, grazed land remaining grazed land, and land converted to grazed land, in MMT CO2 eq. Measured in Millions of Metric Tons, Carbon Dioxide Equivalent (MMT CO2 eq.) and also displayed in percentage units.Resource Title: Table 2-2. File Name: Table2_2.csvResource Description: Greenhouse Gas Emissions by Livestock Category and Source, 2018. For enteric fermentation, managed livestock waste, and grazed land, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent)Resource Title: Table 2-3. File Name: Table2_3.csvResource Description: Descriptions of livestock waste deposition and storage pathways.Resource Title: Table 2-4. File Name: Table2_4.csvResource Description: Methane emissions from enteric fermentation, 1990-2018, from beef cattle, dairy cattle, sheep, poultry, swine, horses, goats, American bison, and mules and asses in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent)Resource Title: Table 2-5. File Name: Table2_5.csvResource Description: Greenhouse Gas Emissions from Managed Livestock Waste in 1990, 1995, 2000, 2005, 2010-2018. In MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Table 2-6. File Name: Table2_6.csvResource Description: Greenhouse Gas Emissions from Grazed Lands in 1990, 1995, 2000, 2005, 2010-2018, for nitrous oxide and methane, presented in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Data for Figure 2-1. File Name: Figure2_1.csvResource Description: Greenhouse Gas Emissions from Livestock, 2018. MMT CO2 eq. emissions from beef cattle, dairy cattle, sheep, poultry, swine, horses, goats, bison, and mules. Measured in Millions of Metric Tons, Carbon Dioxide Equivalent (MMT CO2 eq.) and also displayed in percentage units.Resource Title: Data for Figure 2-2. File Name: Figure2_2.csvResource Description: Greenhouse Gas Emissions from Managed Livestock Waste by Livestock Type, 2018. MMT CO2 eq. emissions from beef cattle, dairy cattle, sheep, poultry, swine, horses, goats, bison, and mules. Measured in Millions of Metric Tons, Carbon Dioxide Equivalent (MMT CO2 eq.) and also displayed in percentage units.Resource Title: Data for Figure 2-3. File Name: Figure2_3.csvResource Description: Greenhouse Gas Emission from Managed Livestock Waste, 1990-2018. MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent) for N2O and CH4.Resource Title: Data for Figure 2-4. File Name: Figure2_4.csvResource Description: Estimated Reductions in Methane Emissions from Anaerobic Digesters, 2000-2018 in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Data for Map 2-1. File Name: Map2_1.csvResource Description: GHG Emission from Livestock Production in 2018, by U.S. State, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent)Resource Title: Data for Map 2-2. File Name: Map2_2.csvResource Description: Map 2-2 Methane Emissions from Enteric Fermentation in 2018, by U.S. State, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Data for Map 2-3. File Name: Map2_3.csvResource Description: GHG Emission from Managed Livestock Waste in 2018, by U.S. State, in MMT CO2 eq. (Millions of Metric Tons, Carbon Dioxide Equivalent).Resource Title: Chapter 2 Appendix Tables. File Name: Chapter2_Appendix_Tables.xlsxResource Description: Chapter 2 includes 27 appendix tables, that include data on, inter alia, the population of animals by state, emission factors for livestock, state level GHG emissions from enteric fermentation, state level methane and nitrous oxide emissions from managed manure, and state volatile solids production rates for 2018.Resource Title: Figures, maps, tables and appendices from Chapter 2. File Name: Chapter 2 Data.zip

A combination of social and environmental variables related to wolf management and specifically lethal removal of wolves in the north western United States. The study area includes Washington, Oregon, Idaho, and Montana and the study period ranges from 2009-2021. Variables of interest include cattle density, forest cover, percent of federally owned protected areas, population size, number of cattle operations, median income, and livestock predation. Variables in the dataset have been compiled from a variety of government agencies such as US census bureau, USDA NASS, USGS, USDA APHIS, and state wildlife agency reports. Data were used to analyze social and environmental determinants of lethal removal of wolves.

Demographics of beef producers on survey of the perceptions of tennessee beef producers regarding the veterinary feed directive.

Relative growth of cattle numbers and percentage (standard error) in Brazil from 1977 to 2011 in 5-year periods by region.