The average size of farms in the United States has seen a steady increase over the last decade. In 2024, the average farm size reached 466 acres, up from 418 acres in 2007. Between 2006 and 2007 there was a sudden drop in average farm size, but in recent years it has recovered and once again reached the same levels as its peak in 2006. Agriculture in the United States In 2023, there were about 1.9 million farms in the United States, down from 2.2 million in 2007. It appears that as average farm size has increased, the number of individual farms in the United States has decreased. Texas is home to the highest number of farms of any U.S. state, with 231,000 farms as of 2023. Major crops in the United States The United States produces a wide variety of crops. Though the production volumes of some major crops, such as wheat, have fluctuated considerably since 2000, the production of vegetables for processing has been on the rise in recent years. Grapes, apples, and oranges are the most produced fruits in the United States, with the majority of grapes being grown in California.

This statistic depicts the number and average size of farms in the United States from 2012 to 2024. The total number of farms in the U.S. in 1900 was *********, as compared to1,880,000 in 2024.

This statistic shows the average size of U.S. farms from 2019 to 2024, sorted by economic sales class. In 2024, farms belonging to the sales class between 100,000 to 249,999 U.S. dollars had an average size of 799 acres of land.

State fact sheets provide information on population, income, education, employment, federal funds, organic agriculture, farm characteristics, farm financial indicators, top commodities, and exports, for each State in the United States. Links to county-level data are included when available.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Query tool For complete information, please visit https://data.gov.

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.

This dataset contains estimates of proportional area of 18 major crops for each county in the United States at roughly decadal time steps between 1840 and 2017, and was used for analyses of historical changes in crop area, diversity, and distribution published in:Crossley, MS, KD Burke, SD Schoville, VC Radeloff. (2020). Recent collapse of crop belts and declining diversity of US agriculture since 1840. Global Change Biology (in press).The original data used to curate this dataset was derived by Haines et al. (ICPSR 35206) from USDA Agricultural Census archives (https://www.nass.usda.gov/AgCensus/). This dataset builds upon previous work in that crop values are georeferenced and rectified to match 2012 county boundaries, and several inconsistencies in the tabular-formatted data have been smoothed-over. In particular, smoothing included conversion of values of production (e.g. bushels, lbs, typical of 1840-1880 censuses) into values of area (using USDA NASS yield data), imputation of missing values for certain crop x county x year combinations, and correcting values for counties whose crop totals exceeded the possible land area.Please contact the PI, Mike Crossley, with any questions or requests: mcrossley3@gmail.com

Agricultural land (% of land area) in United States was reported at 45.09 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Agricultural land (% of land area) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Statistics on agriculture in Massachusetts

The US agricultural industry has been shaped by fluctuations in crop prices, production levels and yields. While prices for core US crops such as corn and wheat remain above historical averages, they have moderated from the peaks seen in 2021-2022. This moderation has clashed with high production costs, particularly for inputs like seeds and fertilizers, which have not decreased in line with prices and revenues. Purchase costs also stand to worsen as tariffs imposed by the US have the potential to drive up prices for imported agricultural inputs. As a result, farmers are encountering tighter profit, even as industry revenue has grown overall. Despite the pressures from input costs, technological advancements such as precision agriculture are helping to offset some challenges by improving efficiency and production. Overall, revenue has grown at a CAGR of 2.7% to reach an estimated $586.5 billion after a decrease of 2.6% in 2025. In tandem with these price and production shifts, consumer preferences are exerting significant influence over the agricultural landscape. The demand for sustainable and ethically produced livestock products is rising, prompting producers to adapt their practices to meet changing consumer expectations. This shift comes amid severe drought conditions forcing cattle herd liquidations, a move that has boosted revenues through higher prices and sales volumes but ultimately stresses long-term supplies. Meanwhile, climate change continues to introduce strong production fluctuations, as evidenced by altering pest and disease patterns and extreme weather events disrupting traditional farming cycles. Adaptation strategies, such as planting drought-resistant crops and investing in climate-smart technologies, are becoming increasingly common as farmers strive to maintain resilience. In the coming five years, the sector will struggle to maintain revenue as prices decline in key segments and climate change adds a great deal of volatility. Sector revenue is forecast to decline at a CAGR of 0.5% to reach $573.3 billion in 2030. Crop prices are projected to decline over the next decade, while yields are expected to trend upward due to ongoing technological advancements. Despite drops in overall export revenue and competition from producers such as China and Brazil, emerging markets, particularly in Asia and Africa, will present new avenues for growth as demand for diverse agricultural products increases. Additionally, the potential for income generation through participation in carbon markets and adoption of nature-positive farming practices offers promising revenue diversification. The increasing frequency of extreme seasons and weather events, however, will make production planning challenging and exaggerate farmers' dependence on agricultural services, agrochemicals, irrigation and other expenses, putting pressure on profit as farmers try to maintain yields.

This EnviroAtlas data set depicts estimates for mean cash rent paid for land by farmers, sorted by county for irrigated cropland, non-irrigated cropland, and pasture by for most of the conterminous US. This data comes from national surveys which includes approximately 240,000 farms and applies to all crops. According to the USDA (U.S. Department of Agriculture) National Agricultural Statistics Service (NASS), these surveys do not include land rented for a share of the crop, on a fee per head, per pound of gain, by animal unit month (AUM), rented free of charge, or land that includes buildings such as barns. For each land use category with positive acres, respondents are given the option of reporting rent per acre or total dollars paid. 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 US farm equipment industry is a robust sector projected to experience significant growth in the coming years. With a 2025 market size of $39.56 billion and a Compound Annual Growth Rate (CAGR) of 6.30% from 2025 to 2033, the industry demonstrates consistent expansion. This growth is fueled by several key factors. Increased adoption of precision farming technologies, including GPS-guided machinery and automated systems, enhances efficiency and yields, driving demand for advanced equipment. Furthermore, government initiatives promoting sustainable agricultural practices and supporting farmers through subsidies contribute to market expansion. The rising global population and increasing demand for food security further bolster the industry's growth trajectory. However, challenges such as fluctuating commodity prices, potential supply chain disruptions, and the increasing cost of raw materials for equipment manufacturing present some headwinds. The leading players in this market, including Deere & Company, AGCO Corporation, and CNH Industrial, are actively investing in research and development to innovate and introduce technologically advanced equipment. This competition drives innovation and enhances the overall quality and capabilities of farm machinery available to farmers. Market segmentation, likely categorized by equipment type (tractors, harvesters, planters, etc.), and farm size, influences the specific growth dynamics within various niches. Regional variations in agricultural practices and government policies further shape the market's development. Analyzing these segments and regional differences is crucial for understanding the specific opportunities and challenges within the US farm equipment industry, and tailoring strategies for success. Key drivers for this market are: Low Availability of Skilled Labor, Technological Advancements. Potential restraints include: Increasing Farm Expenditure, Security Concerns in Modern Farming Machinery. Notable trends are: Increasing Average Farm Size.

Graph and download economic data for Net farm income, USDA (B1448C1A027NBEA) from 1967 to 2023 about USDA, agriculture, Net, income, GDP, and USA.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Farmland, IN, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Farmland did not include 6, or 7-person households. Across the different household sizes in Farmland the mean income is $55,513, and the standard deviation is $32,932. The coefficient of variation (CV) is 59.32%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $33,007. It then further increased to $113,127 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/farmland-in-median-household-income-by-household-size.jpeg" alt="Farmland, IN median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Farmland median household income. You can refer the same here

What? A dataset containing 315 total variables from 33 secondary sources. There are 262 unique variables, and 53 variables that have the same measurement but are reported for a different year; e.g. average farm size in 2017 (CapitalID: N27a) and 2022 (N27b). Variables were grouped by the community capital framework's seven capitals—Natural (96 total variables), Cultural (38), Human (39), Social (40), Political (18), Financial (67), & Built (15)—and temporally and thematically ordered. The geographic boundary is NOAA NCEI's corn and soybean belt (figure below), which stretches across 18 states and includes N=860 counties/observations. Cover crop data for the 80 Crop Reporting Districts in the boundary are also included for 2015-2021. Why? Comprehensively assessing how community capital clustered variables, for both farmers and nonfarmers, impact conservation practices (and perennial groundcover) over time helps to examine county-level farm conservation agriculture practices in the context of community development. We contribute to the robust U.S. cover crop literature a better understanding of how overarching cultural, social, and human factors influence conservation agriculture practices to encourage better farm management practices. Analyses of this Dataverse will be presented as recomendations for farmers, nonfarmers, ag-adjacent stakeholders, and community leaders. How? Variables used in this dataset range 20 years, from 2004-2023, though primary analyses focus on data collected between 2017-2024, primarily 2017 and 2022 (NASS Ag Census years). First, JAM-K requested, accessed, and downloaded data, most of which was already publically available. Next, JAM-K cleaned the data and aggregated into one dataset, and made it publically available on Google Drive and Zenodo. What is 'new' or corrected in version 2.2? Edited/amended: Carroll, KY is now spelled correctly (two 'l's, not one); variable names, full and abbreviated, were updated to include the data year; Pike County's (IL) FIPS has been corrected from its wrong 17153 (same as Pulaski County) to 17149 (correct fips), and all Pike County (IL) data has been correctly amended; Farming dependent (ERS) updated for all variables; Data for built capital variables irrCorn17, irrSoy17, irrHcrp17, tractor17, and combine17 were incorrect for v.1, but were corrected for v.2; Several variable labels aggregated by Wisconsin University's Population Health Institute's County Health Rankings and Roadmaps were corrected to have the data's original source and years included, rather than citing CHR&R as the source (except for CHR&R's originally-produced values such as quartiles or rank scores); variables were reorganized by hypothesized community capital clusters (Natural -> Built), and temporally within each cluster. Added: 55 variables, mostly from the 2022 Ag Census, and v 2.2 added a .pdf file with descriptives of data sources and years, and a .sav file. Omitted: Four variables deemed irrelevant to the study; V1 codebook's "years internally available" column. Variable herbac22 for 55079, Milwaukee, WI, incorrectly had the value 2,049.612. That value was correctly changed to missing, with no data in the cell. CRediT: conceptualization, CBF, JAM-K; methodology, JAM-K; data aggregation and curation, JAM-K; formal analysis, JAM-K; visualization, JAM-K; supervision, CBF; funding acquisition, CBF; project administration, CBF; resources, CBF, JAM-K Acknowledgements: This research was funded by the Agriculture and Food Research Initiative Competitive Grant No. 2021-68012-35923 from the United States Department of Agriculture National Institute for Food and Agriculture. Any opinions, findings, conclusions, or recommendations expressed in this presentation are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture. Much thanks to Corteva for granting data access of OpTIS 2.0 (2005-2019), and Austin Landini for STATA code and visualization assistance.

This collection includes county-level data from the United States Censuses of Agriculture for the years 1840 to 2012. The files provide data about the number, types, output, and prices of various agricultural products, as well as information on the amount, expenses, sales, values, and production of machinery. Most of the basic crop output data apply to the previous harvest year. Data collected also included the population and value of livestock, the number of animals slaughtered, and the size, type, and value of farms. Part 46 of this collection contains data from 1980 through 2010. Variables in part 46 include information such as the average value of farmland, number and value of buildings per acre, food services, resident population, composition of households, and unemployment rates.

The United States Precision Farming Software Market size was valued at USD 521.3 Million in 2023 and is projected to reach USD 1000.3 Million by 2032, exhibiting a CAGR of 11.10 % during the forecasts periods. The market is driven by various factors such as the increasing adoption of smart farming practices, technological advancements, government initiatives, and rising food security concerns. Key drivers for this market are: Increasing Legalization of Cannabis, Growing Focus on Health Benefits of Cannabis. Potential restraints include: Lack of Data on Dosages and Results, Lack of Access to Financial Assistance. Notable trends are: Farm Labor Shortage and Rise in Average Farm Size.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Brownsboro Farm, KY, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Brownsboro Farm did not include 6, or 7-person households. Across the different household sizes in Brownsboro Farm the mean income is $132,428, and the standard deviation is $39,089. The coefficient of variation (CV) is 29.52%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $79,177. It then further increased to $134,214 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/brownsboro-farm-ky-median-household-income-by-household-size.jpeg" alt="Brownsboro Farm, KY median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brownsboro Farm median household income. You can refer the same here

About this dataset

Context

The dataset presents median household incomes for various household sizes in Prairie Farm, WI, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Prairie Farm did not include 3, 4, 6, or 7-person households. Across the different household sizes in Prairie Farm the mean income is $70,710, and the standard deviation is $41,212. The coefficient of variation (CV) is 58.28%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $29,725. It then further increased to $112,145 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/prairie-farm-wi-median-household-income-by-household-size.jpeg" alt="Prairie Farm, WI median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Prairie Farm median household income. You can refer the same here

The U.S. Indoor Farming Market size was valued at USD 4.40 billion in 2023 and is projected to reach USD 9.67 billion by 2032, exhibiting a CAGR of 11.9 % during the forecasts period. This evidence indicates that the U. S. indoor farming market is expanding as the population evolves to require an adequate method of food sustenance. Agriculture that is conducted in controlled environments such as closed structures, green houses, hydroponics, aeration, and aqua ponds. It makes it possible to harvest all around the year, increased production and little or no use of water in production as compared to normal farming. Application include cultivation of vegetables and fruits, herbs in the urban setting, which can be either in vertical farming or in the greenhouse. Uses cover such areas as local food supply, special crops, among others. Some of the major trends that the current market has witnessed are; the development of AI and IoT for better farming or cropping, progress in lighting solution for plant i. e. LED lighting and shifting towards on professional, organic farming and pest-free mode of cultivation. With the increase in concern over the freshness of food and the local food security, indoor farming is a viable solution in realizing these needs. Recent developments include: In March 2023, Elevate Farms announced the commencement of operations at its first wholly-owned US farm, located in Orange, New Jersey ("Elevate New Jersey"). The entire Elevate New Jersey facility measures 14,000 square feet which includes 4,750 square feet of unmanned, fully autonomous, grow room space along with processing, packaging, and administration. The farm can produce up to 11,000,000 plants, or equal to 500,000 pounds of plants, annually. , In January 2024, Forever Feed Technologies, announced a definitive agreement with Dr. Greenhouse, Inc., to design the controlled environment for an enterprise-scale indoor feed mill at the River Ranch Dairy in Hanford, California. The feed mill will grow Automated Sprouted Grain (ASG) to enrich the diets of over 5,000 dairy cows. FFT anticipates the indoor feed mill will begin production in late 2024. .

Simplification of agricultural landscapes is expected to have positive effects on many crop pests and negative effects on their natural enemies, potentially leading to increased pest pressure, decreased crop yield, and increased insecticide use. While many intermediate links in this causal chain have empirical support, there is mixed evidence for ultimate relationships between landscape simplification, crop yield, and insecticide use, especially at large spatial and temporal scales. We explored relationships between landscape simplification (proportion of a county in harvested cropland) and insecticide use (proportion of harvested cropland treated with insecticides), using county-level data from the US Census of Agriculture and a variety of standard and spatiotemporal regression techniques. The best model indicated that insecticide use across the US has increased between 1997 and 2012, was strongly dependent on the crops grown in a county, increased with average farm income and size, and increased with annual growing degree days. After accounting for those variables, and other unidentified spatial and temporal structure in the data, there remained a statistically significant, moderate, positive relationship between insecticide use and landscape simplification. These results lend general support to the causal chain outlined above, and to the notion that a landscape perspective is useful for managing ecosystem services that are provided by mobile organisms and valuable to agriculture.