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.

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 National Agricultural Statistics Service 2012 Census of Agriculture - FarmsPrepared by Larry Heard, NMCDC, larryheard@gmail.comSource: United States Department of Agriculture 2012 Census of Agriculture, http://www.agcensus.usda.gov/The Census of Agriculture provides a detailed picture every five years of U.S. farms and ranches and the people who operate them.Maps and statistics from the 2012 Census of Agriculture are organized into 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.ArcGIS Map Service: http://arcgis-ersarcgism3xl-1157953884.us-east-1.elb.amazonaws.com/arcgis/rest/services/NASS/farms/MapServer

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 5,739,657, as compared to1,880,000 in 2024.

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.

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.

In 2024, there were about 1.88 million farms in the United States. However, the number of farms has been steadily dropping since the year 2007, when there were about 2.2 million farms in the United States. U.S. farms In 2007, the average size of farms in the United States was the smallest it had been since the year 2000. As the number of farms in the United States decrease, the average size of farms increases. Texas, the largest state in the contiguous United States, also contains the highest number of farms, at 231 thousand in 2023. Organic farming in the United States The United States has over 2.3 million hectares of organic agricultural land as of 2021. In 2022, organic food sales in the United States amounted to almost 59 billion euros, making it the largest market for organic food worldwide. In 2021, the number of certified organic farms in the United States reached 17,445, up from about 14,185 farms in 2016.

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).

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

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

Abstract

The sample design of the Production Methods and the Environment module survey is based on the sample of the current Survey of Agricultural Holdings, so firstly given the design of the current Survey. The main purpose of the Survey of Agricultural Holdings as well as Production Methods and the Environment module is to produce official indicators in line with agricultural sector. The survey allows the compilation of statistics on crops and animal husbandry, of which information annual and permanent crops, sown area, average yield of annual crops, farming practices and their linkages with the natural environment, crop and livestock production methods, access to and use of information services, infrastructure and communal resources and etc. Statistical tables are accessible through the following link: https://www.geostat.ge/en/modules/categories/196/agriculture. Production Methods and the Environment Module is part of main Survey of Agricultural Holdings. One round of the main survey (reference year) includes 5 inquiries: The Inception interview is carried out using the inception questionnaire during the period of January-February of the reference year. During this interview the sampled holdings are identified and situation existing at the holding as of first January is recorded. I, II and III quarter interviews are conducted by means of quarterly questionnaire at the beginning of the following month of the corresponding quarter of the reference year. Based on these surveys, the information about agricultural activities during the corresponding quarter is collected. The final interview is conducted by means of final questionnaire in January of the following year of the reference year. During this interview, the information about agricultural activities at the holding during IV quarter of the reference year and the summery information about agricultural activities at the holding during the whole reference year (from 1 January to 31 December of the previous year) are collected. During all five interviews, the same agricultural holdings (about 12000) are interviewed which are selected by a two-stage stratified cluster random sampling procedure out of about 642 000 agricultural holdings operated in Georgia. On the first stage, clusters (settlements) are selected. On the second stage, holdings are selected within the selected clusters. The survey completely covers the territory of Georgia, excluding the occupied territories of Autonomous Republic of Abkhazia and Tskhinvali region. Each year a new sample is selected based on a rotational design (on a 3-year basis). In particular, every year approximately 4000 holdings out of the 12000 sampled holdings are replaced by new holdings. Sampled holdings participate in the survey for 3 years. Large agricultural holdings are sampled every year with complete coverage. The statistical unit of the survey is the agricultural holding (family holdings and agricultural enterprises) - which is defined as an economic unit of agricultural production under single management comprising all livestock kept and all land used wholly or partly for agricultural production purposes, without regard to title, legal form or size. Agricultural activities are conducted under the supervision of a holder (in case of households - a member of household, in case of agricultural enterprises - director or authorized person), who is responsible for making decisions and takes all economic risks and expenses related to agricultural activities. More than 270 interviewers participate in the survey fieldwork. For the Data collection, computer-assisted personal interviewing method (CAPI) is used in the family holdings. In case of agricultural enterprises, the authorized persons of the enterprises (respondent) fill the electronic (online) questionnaires by themselves (CAWI). Coordination of the interviewers and the primary control of the collected data during the field is carried out by coordinators. Their working area covers several municipalities. The function of the coordinators also includes consultation for agricultural enterprises on methodological and technical issues related to the survey. Production Methods and Environment module field work was carried out from May 5th to May 20th of 2022. 200 field staff participated in the survey, 22 of which were field supervisors. In total 5,880 agricultural holdings were selected for the PME survey. Such are the extra-large farms that are continuously participating in the survey and the third rotation farms that have been participating in the survey since 2019. Currently 943 extra-large farms and 3,899 third rotation farms are participating in the survey. Therefore, we have a total of 4,842 farm data for the last three years. The rest of the holdings will be selected from the first rotation clusters where interviews have been conducted for two years. In particular, using simple random sampling approximately 30% of the working clusters of the first rotation are selected in each stratum. This will give us about 1,038 farms. A total of about 5,880 farms will be selected.

Geographic coverage

Entire country (Georgia), excluding occupied regions (Abkhazia and Tskhinvali region)

Analysis unit

Agricultural holding – economic unit of agricultural production under single management comprising all livestock kept and all land used wholly or partly for agricultural production purposes, without regard to title, legal form or size in which agricultural activities are conducted under the supervision of a holder, who is responsible for making decisions and takes all economic risks and expenses related to agricultural activities.

Universe

Survey sampling frame includes about 642 000 agriculture holdings (households and agricultural enterprises) operated in country. The Agricultural Census 2014 is the main source of the sample frame. Sampling frame is updated on a permanent basis in according to the results of survey of agricultural holdings, business register and different administrative sources.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design of the Production Methods and the Environment module survey is based on the sample of the current Survey of Agricultural Holdings, so firstly given the design of the current Survey. • Main Source of the sample frame since 2016 - Agricultural Census 2014; • Sample frame contained 642 000 holding - sample size 12 000 (1.9%); • Sample Design: two-stage stratified cluster random sampling; - First stage - selection of cluster (Settlement); - Second stage - Selection of holdings within the selected clusters; • Each year a new sample is selected based on a rotational design; - Every year 1/3 of holdings (4 000) selected a year before are replaced (Sampled holdings participate in the survey during 3 years); • Extremely large agricultural holdings are sampled every year with complete coverage; • Additional Sources for updating sample frame: Sample Survey of Agricultural Holdings, Statistical Business Register, Administrative data existing in MEPA (large agricultural holdings); Sampling error of main indicators do not exceed 5% for a country level and 10% for a regional level; The sample design of the Production Methods and the Environment module survey: • Sample Design:Two-stage cluster sampling was used for the survey. -Sample is formed separately in each stratum. At first, clusters are selected in every stratum, and then holdings from selected clusters are selected for survey. -Extra-large holdings will be in the sample by probability 1. That is, all clusters of extra-large holdings and all extra-large holdings from these clusters fall into sample. -Primary sampling unit in the rest of the strata is the cluster. The same number of holdings will be interviewed in all the selected clusters of a stratum. Specifically, in small holding strata, 12 holdings will be interviewed in each selected cluster. This number is 8 for medium-sized strata and 4 for large strata. -In each stratum the number of clusters that have to be selected is calculated by dividing the number of holdings to be selected in the stratum by the number of holdings to be interviewed in each cluster of the stratum. -In each stratum selection of clusters is done by the PPS method (Probability Proportionally to Size). -The selection of holdings in each selected cluster is made using a random systematic sample. • Rotational design: Survey has a panel design. Holdings, which will get into the sample, will stay there for three years. After this, they will be substituted by holdings from the same stratum. -The database lists 943 extra-large holdings. All of them will constantly participate in the survey. Their rotation group number will be "0". Of the remaining holdings each of them will belong to one of the three rotation groups. Holdings selected from the same cluster will fall in the same rotation group. Each rotation group will have more or less the same number of holdings. Each rotation group represents an independent random sample. -When holdings change by rotation , holding from the sample will be substituted by the new one from the same cluster. If the cluster does not have enough holdings to make the full rotation, then the cluster is deemed exhausted and is substituted by a randomly selected cluster from the same stratum. -Newly introduced holdings will belong to the same rotation group which its predecessor belonged to

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Detailed information on structure, and sections of questionnaires used in the survey of agricultural holdings available in following link:

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 July of 2025.

This EnviroAtlas dataset shows the acres of land enrolled in the US Department of Agriculture (USDA)'s Conservation Reserve Program (CRP). The CRP is administered by the Farm Service Agency; farmers in the program receive annual payments and establishment cost share to remove environmentally sensitive land from crop production and instead plant perennial species that provide environmental benefits. This dataset was produced by the USDA 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).

This map shows the relationship between Federal payments toward conservation and wetlands and payments toward producers not including conservation/wetlands. The data is produced by the USDA National Agricultural Statistics Service (USDA).Areas in yellow show where there are high amounts of Federal payments toward Conservation in comparison to other types, whereas areas in light blue have a higher amount of Federal payments toward all other agriculture in comparison to Conservation. Areas in black have an overall high amount of both types of payments. The map uses size to emphasize which counties received the overall largest receipts in US dollars.In 2017, the average farm received an average of $13,906, and conservation/wetland programs received and average of $6,980. These are the central colors of the map in order to anchor the map around the national figure. Areas with a pattern above or below the national average are highlighted by the colors along the edges of the legend (mentioned in the previous paragraph). For more information about Federal payments in 2017, visit this summary table from the USDA.For more information about the relationship mapping style used in this map, visit this blog. About the data and source:The Census of Agriculture, produced by the USDA National Agricultural Statistics Service (USDA), provides a complete count of America's farms, ranches and the people who grow our food. The census is conducted every five years, most recently in 2017, and provides a in-depth look at the agricultural industry.This layer summarizes payments made to producers by the Federal government from the 2017 Census of Agriculture at the county level.This layer was produced from data downloaded using the USDA's QuickStats Application. The data was transformed using the Pivot Table tool in ArcGIS Pro and joined to the county boundary file provided by the USDA. The layer was published as feature layer in ArcGIS Online.Dataset SummaryPhenomenon Mapped: Payments made to producers by the Federal governmentCoordinate System: Web Mercator Auxiliary SphereExtent: United States including Hawaii and AlaskaVisible Scale: All ScalesSource: USDA National Agricultural Statistics Service QuickStats ApplicationPublication Date: 2017AttributesThis layer provides values for the following attributes. Note that some values are not disclosed (coded as -1 in the layer) to protect the privacy of producers in areas with limited production.Federal Payments - Operations with ReceiptsFederal Payments - Receipts in US DollarsFederal Payments - Receipts in US Dollars per OperationFederal Payments not Including Conservation and Wetland Programs - Operations with ReceiptsFederal Payments not Including Conservation and Wetland Programs - Receipts in US DollarsFederal Payments not Including Conservation and Wetland Programs - Receipts in US Dollars per OperationFederal Payments for Conservation and Wetland Programs - Operations with ReceiptsFederal Payments for Conservation and Wetland Programs - Receipts in US DollarsFederal Payments for Conservation and Wetland Programs - Receipts in US Dollars per OperationConservation and wetland programs include:Conservation Reserve Program (CRP)Wetlands Reserve Program (WRP)Farmable Wetlands Program (FWP)Conservation Reserve Enhancement Program (CREP)Other programs with payments to producers include:2014 Agricultural Act (Farm Bill)Agriculture Risk Coverage (ARC)Price Loss Coverage (PLC)Commodity Credit Corporation (CCC)Loan Deficiency PaymentsDisaster Assistance ProgramsState and local government agricultural program payments and Federal crop insurance payments are not included.Additionally, attributes of State Name, State Code, County Name and County Code are included to facilitate cartography and use with other layers.

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.

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.

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).

According to Cognitive Market Research, the global Smart Agriculture Farming market size will be USD 17254.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 9.70% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 6901.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 5176.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.2% from 2024 to 2031.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 3968.47 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.7% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 862.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.1% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 345.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.4% from 2024 to 2031.
The Hardware held the highest Smart Agriculture Farming market revenue share in 2024.

Market Dynamics of Smart Agriculture Farming Market

Key Drivers

Increasing the use of modern technologies in agriculture products to propel market growth

Utilizing its full potential, smart agriculture can assist farmers in minimizing the adverse impacts of climate change on crops by collecting geospatial data on planting, soil, livestock, and other data between and within fields. Reducing resource waste, smart agriculture also provides information on the proper dosage of irrigation, liquid fertilizer, insecticides, and herbicides. Modern agricultural technologies like yield mapping software (YMS), data management software, global positioning system (GPS), variable rate technology (VRT), and mapping software help boost soil fertility, boost profitability, lower farming costs, and support sustainable agriculture. Smart agriculture tools have two main benefits: increased productivity for businesses through automated procedures and superior output at reduced farming costs. Smart agriculture technology is projected to make agribusiness more profitable than it has ever been. Thus, in an effort to increase crop yields and profitability, business-minded farmers have started utilizing a variety of smart agricultural instruments. The worldwide smart agriculture market is expected to expand quickly over the anticipated time due to the increasing adoption of modern technology in agricultural goods by business-oriented farmers.

Internet of Things (IoT) adoption in agriculture is growing to propel market growth

The increasing adoption of Internet of Things (IoT) technology in agriculture provides real-time support through IoT apps, assisting farmers in tracking the development of new products. By using IoT applications with traditional agriculture processes, producers can focus on providing their consumers with high-quality food instead of spending time and money on resources like land, electricity, and water. Precision farming enhances crop and soil health and allows organic food to be distributed to a wide range of end consumers. IoT-based agricultural equipment helps reduce the use of pesticides and fertilizers in this way. The extensive use of IoT technology in agriculture helps farmers adapt to major variations in weather, humidity, and air efficiency. It uses data analytics, visualization, and a variety of management tools and solutions to automate conventional farming activities. The application of IoT technology in agriculture reduces carbon emissions and boosts farm productivity by utilizing cutting-edge sustainable technologies to conserve energy and water.

Key Restraint

Fragmented agriculture sector to hinder market growth

Decentralized, the agricultural sector comprises a multitude of autonomously operated large, medium, and small-scale farms. A standardized machine-to-machine (M2M) solution is challenging to implement because of this fragmentation since each farm may have distinct needs and operate differently. Due to the incorrect distribution of inputs and resources caused by land fragmentation, costs are subsequently elevated. Encouraging, m...

The US Farm Equipment Industry size was valued at USD 39.56 Million in 2023 and is projected to reach USD 60.67 Million by 2032, exhibiting a CAGR of 6.30 % during the forecasts periods. This growth is primarily driven by the rising demand for hybrid seeds, which offer superior yield and disease resistance. Government initiatives to promote agricultural innovation and technology adoption, along with increasing food security concerns, have further fueled industry growth. Technological advancements, such as precision farming and autonomous equipment, are transforming operations, enhancing efficiency, and driving demand for farm equipment. Major players in the hybrid seed market include Syngenta, Bayer CropScience, DuPont Pioneer, and Corteva Agriscience. Recent developments include: December 2022: CNH Industrial added new Automation and Autonomy Solutions to the Ag Tech portfolio in Phoenix, Arizona, and the USA. These New Driverless Tillage and Driver Assist Harvest solutions from Raven, and Baler Automation from Case IH and New Holland, can deliver automation and autonomous equipment enhancements and help solve farmers' most significant challenges to increasing productivity., May 2022: AGCO acquired JCA Industries to increase engineering and software development capabilities and to accelerate the development of highly automated and autonomous machines., April 2022: Deere & Company and GUSS Automation formed a joint venture with an LLC in Kingsburg, Calif. Global Unmanned Spray System (GUSS) is a pioneer in semi-autonomous sprayers for orchards and vineyards.. 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.