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.

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.

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 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.

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

Cattle markets, where livestock producers may buy and sell cattle and calves, act as major hubs in the shipment network that connect cattle populations across the United States (U.S.). Cattle markets can then provide insight into the integration of the U.S. cattle industry, thus informing how regional price fluctuations can influence cattle prices nationally. Despite biosecurity measures and regulatory compliance from livestock markets, commingling and re-distribution of animals from multiple sources may elevate the risk of disease spread and make tracing animal movements more complex, which could pose significant challenges if a transboundary animal disease (TAD) were introduced into the U.S. Therefore, knowing the size and location of cattle markets in the U.S. is critical to understanding cattle industry market dynamics and enhancing pandemic scenario modeling efforts. In this article, we present a list of cattle markets, their locations, and estimated quarterly cattle sales. We compiled a list of 1,619 known cattle markets with and without market sales data from 1,131 counties across the U.S. from 2012-2016. To estimate unknown market sales data, we fit a spatial autoregressive lag model to annual county-level market sales data and used the fit to predict annual sales in counties that lacked sales information. County-level sales data provide important insight into the structure of the U.S. cattle industry. The dataset can be used to improve national-scale cattle movement models, livestock disease models, and inform TAD surveillance efforts.

This statistic shows the number of milk cows in the U.S. from 1999 to 2024. According to the report, there were approximately *** million milk cows in the United States in 2024, down from about *** million milk cows in 2022.

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.

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.

In 2025, Brazil was the leading cattle producer in Latin America and the Caribbean, with an estimate of about 47.8 million heads of cattle. Ranking second was Argentina, with about 14.8 million heads of cattle, and it was followed by Mexico, where cattle production reached over 8.7 million heads.

Forecast: Whole Fresh Cow Milk Producing Population in the US 2024 - 2028 Discover more data with ReportLinker!

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.

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

[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/

Explore the ongoing challenges in the US cattle industry as low cattle numbers and high beef prices impact consumers and major companies. Learn about the factors influencing the market and future expectations.

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.

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.

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The objective of the project is the standardization of micro-satellite markers used within participating laboratories, use of DNA markers to define genetic diversity and to enable monitoring of breeds to promote conservation programs where required, and the determination of diversity present in rare and local breeds across Europe. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project (See BovMaP). Work with micro-satellite markers has shown that they are valuable tools for examining genetic diversity and phylogeny in many species. However, for work carried out in different laboratories to be comparable, it is essential that the same markers are used. To maintain the compatibility of data generated by the various typing labs, it is essential that all laboratories adopt the same markers and typing protocols. It is therefore of paramount importance that the blood typing laboratories and research labs that are examining the genetic structure of the cattle populations adopt a common panel of the best micro-satellite markers available. Some pilot comparative work has been undertaken through the International Society for Animal Genetics, but so far this has only involved the blood typing laboratories. One objective of this project is to facilitate the comparison of the micro-satellite markers currently in use in the different types of laboratory and determine the efficiency of the markers available in revealing genetic differences within and among breeds. It will also be important to compare the use of markers in different laboratories to determine how robust they are and how easily results can be compared. From comparison of the markers, those that are most suitable will be selected to form a panel which will be recommended for pedigree validation and genetic surveys. Cattle are an important source of food in Europe, and intense selection has resulted in the development of specialized breeds. Selection for high-producing dairy cattle has been successful, but one associated drawback is that the cattle population, both in Europe and North America, has been skewed dramatically towards one breed, the Holstein/Friesian. So there has been a decline in the number of individuals of other breeds, and hence a general erosion of the genetic base of the cattle population. The progressive move towards the North American-type Holstein animals has also resulted in the requirement for high input/high output farming and intensive management schemes. The impact of this on the environment has been significant, e.g. pollution problems arising from the need for high nitrogen fertilizers to produce sufficient high quality fodder, and disposal problems associated with slurry waste. Poorer areas of the community have been unable to compete with such farming systems, and are more suited to low input/low output farming using traditional stock. It is however the future perspective that is of greatest concern. It is impossible to predict requirements for cattle production - quality, production type, management systems, etc. The ability to switch rapidly to alternative production will be dependent on the genetic base of the population available to selection programs. It is therefore essential to maintain the greatest genetic diversity possible in the cattle population. Whilst current farming practices are perceived to be both efficient and acceptable, the breeds less favored by commercial farmers will dwindle. It is therefore important that on an European scale efficient management of these breeds maintains the widest genetic base possible. This project aims to carry out a survey of the current genetic base of the European cattle population and to provide the tools to assist breeding programs to maintain a broad base. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project. Early work to measure genetic diversity used blood groups to show differences between breeds and the diversity present. Unfortunately, the number of loci available are limited, with only the B system being sufficiently polymorphic to be really useful. However, since there is a wealth of information available from such typing, this information can be used to estimate changes in the genetic structure of cattle populations across Europe over the past twenty years. More recently mini-satellite probes have been used to generate ''genetic fingerprints'' which have been used to show differences between individuals. Such fingerprints have been used to estimate genetic diversity - the greater the number of bands revealed by the fingerprint being equated with greater diversity. This is valid within limits. The main disadvantage of the fingerprint approach is that the chromosomal location and number of loci being sampled, and so the proportion of the genome examined, is unknown. The allelic bands on the gel cannot be easily identified, so allele inheritance cannot be addressed making it impossible to trace ancestry. Through the EC funded BovMaP project, large numbers of highly polymorphic micro-satellite markers have become available, which are being mapped on the bovine genome. These markers are particularly suited to measuring genetic diversity, and markers can be selected to cover the entire genome.

GEMMA output containing summary statistics for generation proxy selection mapping (GPSM) and environmental GWAS (envGWAS) selection analyses from
Rowan et al. "Powerful detection of polygenic selection and environmental adaptation in US beef cattle" 2021
https://doi.org/10.1101/2020.03.11.988121

File names identify the analysis run, for example
"Gelbvieh_envgwas_desert_summary_stats.txt.gz"
Is the Gelbvieh dataset analyzed using the Desert ecoregion as the dependent variable
in a univariate envGWAS model.

Files are formated according to GEMMA output.

High prices have consistently elevated revenues for Canadian cattle producers over the current period, but also discouraged herd rebuilding and drained cattle supplies. Cattle prices have surged due to reduced herds in North America, influenced by persistent droughts impeding effective herd rebuilding. Although producers are generally inclined to rebuild, the volatility of high prices, along with the unpredictability of future drought impacts, has discouraged extensive retention practices. Profit has also been pressured by elevated input costs, particularly feed, but extreme cattle prices have allowed profit to recover and expand since its low in 2022. Compounding these challenges is the difficulty in passing increased costs onto consumers, who have shown a growing propensity to switch to alternative proteins. This, combined with the inherent volatility in agricultural outputs due to extreme weather events, continues to strain the financial health of producers despite elevated cattle prices. Overall, revenue has climbed at a CAGR of 4.4% since 2020, including an increase of 2.0% to reach an estimated $25.6 billion in 2025 as beef prices remain on the rise. Consumer behaviour around beef is being reshaped by health perceptions and sustainability concerns, as well as high beef prices. Persistent health advisories recommending reduced red meat consumption influence both domestic and global market demands, pushing consumers towards substitute proteins. Awareness around sustainability is intensifying interest in plant-based alternatives as environmentally friendly consumption gains traction. While inflation has moderated overall, beef prices continue to rise in response to supply-related constraints, making the protein more costly and steering some consumers toward more affordable options like pork and poultry. Industry associations and producers are focusing on marketing beef’s value, quality and affordability to retain consumer interest amid these shifts. The future outlook for the cattle industry will be strongly influenced by red meat prices, which will see initial short-term price increases and then are expected to ease over time, ultimately resulting in higher price levels in 2030 compared to 2025. These trends are driven by supply constraints and shifting global demands, while herd rebuilding efforts will gradually moderate the huge price increases of the current period. Concurrently, sustained pressures from consumer sustainability concerns are likely to continue spurring interest in alternative proteins, propelling producers toward adopting emission-reducing production methods. Nonetheless, rising disposable incomes, especially in emerging beef export markets, present opportunities for Canadian producers by increasing demand for premium beef products. Expanding into new markets will be particularly important for beef producers and the cattle farmers supplying them as US-Canada trade tensions and tariffs shake the stability of this major buyer. Additionally, anticipated global population growth will support heightened protein demand overall. Revenue is expected to climb at a CAGR of 0.1% to reach $25.8 billion over the five years to 2030.