Quick Stats is the National Agricultural Statistics Service's (NASS) online, self-service tool to access complete results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.

A collection of over 75 charts and maps presenting key statistics on the farm sector, food spending and prices, food security, rural communities, the interaction of agriculture and natural resources, and more.

How much do you know about food and agriculture? What about rural America or conservation? ERS has assembled more than 75 charts and maps covering key information about the farm and food sectors, including agricultural markets and trade, farm income, food prices and consumption, food security, rural economies, and the interaction of agriculture and natural resources.

How much, for example, do agriculture and related industries contribute to U.S. gross domestic product? Which commodities are the leading agricultural exports? How much of the food dollar goes to farmers? How do job earnings in rural areas compare with metro areas? How much of the Nation’s water is used by agriculture? These are among the statistics covered in this collection of charts and maps—with accompanying text—divided into the nine section titles.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: Ag and Food Sectors and the Economy Land and Natural Resources Farming and Farm Income Rural Economy Agricultural Production and Prices Agricultural Trade Food Availability and Consumption Food Prices and Spending Food Security and Nutrition Assistance For complete information, please visit https://data.gov.

Graph and download economic data for Employment Level - Agriculture and Related Industries (LNS12034560) from Jan 1948 to May 2025 about agriculture, 16 years +, household survey, employment, industry, and USA.

This table contains 664 series, with data for years 2009 - 2015 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (8 items: Canada; Atlantic provinces; Quebec; Ontario; ...) Statistical variables (2 items: Total, all farms; Average per farm) Agriculture balance sheets, revenue and expenses (42 items: Number of farms; Total assets; Current assets; Cash and short term investments, current assets; ...).

This table contains data at regional level on the number of persons employed on agricultural holdings, the corresponding annual work units (AWUs) and the number of holdings with workers.

The figures in this table are derived from the agricultural census. Data collection for the agricultural census is part of a combined data collection for a.o. agricultural policy use and enforcement of the manure law.

Regional breakdown is based on the main location of the holding. Due to this the region where activities (crops, animals) are allocated may differ from the location where these activities actually occur.

The agricultural census is also used as the basis for the European Farm Structure Survey (FSS). Data from the agricultural census do not fully coincide with the FSS. In the FSS years (2000, 2003, 2005, 2007 and 2010) additional information was collected to meet the requirements of the FSS.

Data on labour force refer to the period April to March of the year preceding the agricultural census.

In 2022, equidae are not part of the Agricultural Census. This affects the farm type and the total number of farms in the Agricultural Census. Farms with horses, ponies and donkeys that were previously classified as ‘specialist grazing livestock' could be classified, according to their dominant activity, as another farm type in 2022.

From 2018 onwards the number of calves for fattening, pigs for fattening, chicken and turkey are adjusted in the case of temporary breaks in the production cycle (e.g. sanitary cleaning). The agricultural census is a structural survey, in which adjustment for temporary breaks in the production cycle is a.o. relevant for the calculation of the economic size of the holding, and its farm type. In the livestock surveys the number of animals on the reference day is relevant, therefore no adjustment for temporary breaks in the production cycle are made. This means that the number of animals in the tables of the agricultural census may differ from those in the livestock tables (see ‘links to relevant tables and relevant articles).

From 2017 onwards, animal numbers are increasingly derived from I&R registers (Identification and Registration of animals), instead of by means of the combined data collection. The I&R registers are the responsibility of RVO (Netherlands Enterprise Agency). Since 2017, cattle numbers are derived from I&R cattle, and from 2018 sheep, goats and poultry are also derived from the relevant I&R registers. The registration of cattle, sheep and goats takes place directly at RVO. Poultry data is collected via the designated database Poultry Information System Poultry (KIP) from Avined. Avined is a branch organization for the egg and poultry meat sectors. Avined passes the data on to the central database of RVO. Due to the transition to the use of I&R registers, a change in classification will occur for sheep and goats from 2018 onwards.

Since 2016, information of the Dutch Business Register is used to define the agricultural census. Registration in the Business Register with an agricultural standard industrial classification code, related to NACE/ISIC, (in Dutch SBI: ‘Standaard BedrijfsIndeling’) is leading to determine whether there is an agricultural holding. This aligns the agricultural census as closely as possible to the statistical regulations of Eurostat and the (Dutch) implementation of the definition of 'active farmer' as described in the common agricultural policy.

The definition of the agricultural census based on information from the Dutch Business Register mainly affects the number of holdings, a clear deviation of the trend occurs. The impact on areas (except for other land and rough grazing) and the number of animals (except for sheep, and horses and ponies) is limited. This is mainly due to the holdings that are excluded as a result of the new delimitation of agricultural holdings (such as equestrian centres, city farms and organisations in nature management).

In 2011 there were changes in geographic assignment of holdings with a foreign main seat. This may influence regional figures, mainly in border regions.

Until 2010 the economic size of agricultural holdings was expressed in Dutch size units (in Dutch NGE: 'Nederlandse Grootte Eenheid'). From 2010 onwards this has become Standard Output (SO). This means that the threshold for holdings in the agricultural census has changed from 3 NGE to 3000 euro SO. For comparable time series the figures for 2000 up to and including 2009 have been recalculated, based on SO coefficients and SO typology. The latest update was in 2016.

Data available from: 2000

Status of the figures: The figures are final.

Changes as of March 28, 2025: the final figures for 2024 have been added.

When will new figures be published? According to regular planning provisional figures for the current year are published in November and the definite figures will follow in March of the following year.

Longitude and latitude, state, address, name, and zip code of Farmers Markets in the United States

The number of all farms in Denmark declined to 29,554 in 2023. Therefore, the number in Denmark saw its lowest number in that year with 29,554. Find more statistics on all farms in Denmark with key insights such as Number of farms with both cattle and pigs and Number of livestock farms.

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.

From 2000 onwards, the total area of land in U.S. farms has decreased annually, aside from a small increase in 2012. Over the time period displayed, the total farmland area has decreased by over 66 million acres, reaching a total of 876.5 million acres as of 2024. Farming in the U.S. Not only has the land for farming been decreasing in the U.S., but so has the total number of farms. From 2000 to 2021, the number of farms in the U.S. decreased from about 2.17 million farms in 2000 to just under 1.9 million in 2023. Texas has more than double the number of farms compared to other U.S. states, with 231,000 farms in 2023. U.S. agricultural exports The U.S. is known for agriculture production and is the leading exporter of agricultural products worldwide. The total U.S. agricultural exports were valued at over 178 billion U.S. dollars in 2023. Over 4.8 billion dollars’ worth of agricultural exports came from fresh or processed vegetables in 2022.

This table contains data on land use, arable farming, horticulture, grassland, grazing livestock and housed animals, at regional level, by general farm type.

The figures in this table are derived from the agricultural census. Data collection for the agricultural census is part of a combined data collection for a.o. agricultural policy use and enforcement of the manure law.

Regional breakdown is based on the main location of the holding. Due to this the region where activities (crops, animals) are allocated may differ from the location where these activities actually occur.

The agricultural census is also used as the basis for the European Farm Structure Survey (FSS). Data from the agricultural census do not fully coincide with the FSS. In the FSS years (2000, 2003, 2005, 2007 and 2010) additional information was collected to meet the requirements of the FSS.

Reference date for livestock is 1 April and for crops 15 May.

In 2022, equidae are not part of the Agricultural Census. This affects the farm type and the total number of farms in the Agricultural Census. Farms with horses, ponies and donkeys that were previously classified as ‘specialist grazing livestock' could be classified, according to their dominant activity, as another farm type in 2022.

From 2020 onwards, the SO2017, based on the years 2015 to 2019, will apply (see also the explanation for SO: Standard Output).

From 2018 onwards the number of calves for fattening, pigs for fattening, chicken and turkey are adjusted in the case of temporary breaks in the production cycle (e.g. sanitary cleaning). The agricultural census is a structural survey, in which adjustment for temporary breaks in the production cycle is a.o. relevant for the calculation of the economic size of the holding, and its farm type. In the livestock surveys the number of animals on the reference day is relevant, therefore no adjustment for temporary breaks in the production cycle are made. This means that the number of animals in the tables of the agricultural census may differ from those in the livestock tables (see ‘links to relevant tables and relevant articles).

From 2017 onwards, animal numbers are increasingly derived from I&R registers (Identification and Registration of animals), instead of by means of the combined data collection. The I&R registers are the responsibility of RVO (Netherlands Enterprise Agency). Since 2017, cattle numbers are derived from I&R cattle, and from 2018 sheep, goats and poultry are also derived from the relevant I&R registers. The registration of cattle, sheep and goats takes place directly at RVO. Poultry data is collected via the designated database Poultry Information System Poultry (KIP) from Avined. Avined is a branch organization for the egg and poultry meat sectors. Avined passes the data on to the central database of RVO. Due to the transition to the use of I&R registers, a change in classification will occur for sheep and goats from 2018 onwards.

Since 2016, information of the Dutch Business Register is used to define the agricultural census. Registration in the Business Register with an agricultural standard industrial classification code (SIC), related to NACE/ISIC, (in Dutch SBI: ‘Standaard BedrijfsIndeling’) is leading to determine whether there is an agricultural holding. This aligns the agricultural census as closely as possible to the statistical regulations of Eurostat and the (Dutch) implementation of the definition of 'active farmer' as described in the common agricultural policy.

The definition of the agricultural census based on information from the Dutch Business Register mainly affects the number of holdings, a clear deviation of the trend occurs. The impact on areas (except for other land and rough grazing) and the number of animals (except for sheep, horses and ponies) is limited. This is mainly due to the holdings that are excluded as a result of the new delimitation of agricultural holdings (such as equestrian centres, city farms and organisations in nature management).

In 2011 there were changes in geographic assignment of holdings with a foreign main seat. This may influence regional figures, mainly in border regions.

Until 2010 the economic size of agricultural holdings was expressed in Dutch size units (in Dutch NGE: 'Nederlandse Grootte Eenheid'). From 2010 onwards this has become Standard Output (SO). This means that the threshold for holdings in the agricultural census has changed from 3 NGE to 3000 euro SO. For comparable time series the figures for 2000 up to and including 2009 have been recalculated, based on SO coefficients and SO typology. The latest update took place in 2016.

Data available from: 2000

Status of the figures: The figures are final.

Changes as of March 28, 2025: the final figures for 2024 have been added.

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.

These files from Statistics Canada present Census of Agriculture data allocated by standard census geographic polygons: Provinces and Territories (PR), Census Agricultural Regions (CAR), Census Divisions (CD) and Census Consolidated Subdivisions (CCS). Five datasets are provided: 1. Agricultural operation characteristics: includes information on farm type, operating arrangements, paid agricultural work and financial characteristics of the agricultural operation. 2. Land tenure and management practices: includes information on land use, land tenure, agricultural practices, land inputs, technologies used on the operation and the renewable energy production on the operation. 3. Crops: includes information on hay and field crops, vegetables (excluding greenhouse vegetables), fruits, berries, nuts, greenhouse productions and other crops. 4. Livestock, poultry and bees: includes information on livestock, poultry and bees. 5. Characteristics of farm operators: includes information on age, sex and the hours of works of farm operators. Note: For all the datasets, confidential values have been assigned a value of -1. Correction notice: On January 18, 2023, selected estimates have been corrected for selected variables in the following 2021 Census of Agriculture domains: Direct sales of agricultural products to consumers (Agricultural operations category), Succession plan for the agricultural operation (Agricultural operators category), and Renewable energy production (Use, tenure and practices category).

Artificial intelligence is deployed in agriculture mainly in field, livestock, and indoor farming in 2019. Field farming is the main farming type where AI is used in agriculture, with a market share of more than ***. The overall AI in agriculture market had a size of almost *** billion U.S. dollars in 2019 and is forecast to grow to more than *** billion U.S. dollars by 2024.

Census of Agriculture, 2001 to date. Farms classified by farm type.

The size of the farm management software and data analytics market worldwide from 2021 to 2026 is expected grow with a CAGR of 17.47 percent. In 2020, the global farm management software and data analytics market was valued at 1.1 billion U.S. dollars worldwide. North America has a significant presence in the market due to quicker development and implementation of data based technology applied towards agriculture, with a market size of almost half a billion U.S. dollars.

Abstract

The Annual Agricultural Sample Survey (AASS) for the year 2022/23 aimed to enhance the understanding of agricultural activities across Tanzania by collecting comprehensive data on various aspects of the agricultural sector. This survey is crucial for policy formulation, development planning, and service delivery, providing reliable data to monitor and evaluate national and international development frameworks.

The 2022/23 survey is particularly significant as it informs the monitoring and evaluation of key agricultural development strategies and frameworks. The collected data will contribute to the Tanzania Development Vision 2025, Zanzibar Development Vision 2020, the Five-Year Development Plan 2021/22–2025/26, the National Strategy for Growth and Reduction of Poverty (NSGRP) known as MKUKUTA, and the Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP) known as MKUZA. The survey data also supports the evaluation of Sustainable Development Goals (SDGs) and Comprehensive Africa Agriculture Development Programme (CAADP). Key indicators for agricultural performance and poverty monitoring are directly measured from the survey data.

The 2022/23 AASS provides a detailed descriptive analysis and related tables on the main thematic areas. These areas include household members and holder identification, field roster, seasonal plot and crop rosters (Vuli, Masika, and Dry Season), permanent crop production, crop harvest use, seed and seedling acquisition, input use and acquisition (fertilizers and pesticides), livestock inventory and changes, livestock production costs, milk and eggs production, other livestock products, aquaculture production, and labor dynamics. The 2022/23 AASS offers an extensive dataset essential for understanding the current state of agriculture in Tanzania. The insights gained will support the development of policies and interventions aimed at enhancing agricultural productivity, sustainability, and the livelihoods of farming communities. This data is indispensable for stakeholders addressing challenges in the agricultural sector and promoting sustainable agricultural development.

STATISTICAL DISCLOSURE CONTROL (SDC) METHODS HAVE BEEN APPLIED TO THE MICRODATA, TO PROTECT THE CONFIDENTIALITY OF THE INDIVIDUAL DATA COLLECTED. USERS MUST BE AWARE THAT THESE ANONYMIZATION OR SDC METHODS MODIFY THE DATA, INCLUDING SUPPRESSION OF SOME DATA POINTS. THIS AFFECTS THE AGREGATED VALUES DERIVED FROM THE ANONYMIZED MICRODATA, AND MAY HAVE OTHER UNWANTED CONSEQUENCES, SUCH AS SAMPLING ERROR AND BIAS. ADDITIONAL DETAILS ABOUT THE SDC METHODS AND DATA ACESS CONDITIONS ARE PROVIDED IN THE DATA PROCESSING AND DATA ACESS CONDITIONS BELOW.

Geographic coverage

National, Mainland Tanzania and Zanzibar, Regions

Analysis unit

Households for Smallholder Farmers and Farm for Large Scale Farms

Universe

The survey covered agricultural households and large-scale farms.

Agricultural households are those that meet one or more of the following two conditions: a) Have or operate at least 25 square meters of arable land, b) Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agriculture year.

Large-scale farms are those farms with at least 20 hectares of cultivated land, or 50 herds of cattle, or 100 goats/sheep/pigs, or 1,000 chickens. In addition to this, they should fulfill all of the following four conditions: i) The greater part of the produce should go to the market, ii) Operation of farm should be continuous, iii) There should be application of machinery / implements on the farm, and iv) There should be at least one permanent employee.

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used to extract the sample for the Annual Agricultural Sample Survey (AASS-2022/23) in Tanzania was derived from the 2022 Population and Housing Census (PHC-2022) Frame that lists all the Enumeration Areas (EAs/Hamlets) of the country. The AASS 2022/23 used a stratified two-stage sampling design which allows to produce reliable estimates at regional level for both Mainland Tanzania and Zanzibar.

In the first stage, the EAs (primary sampling units) were stratified into 2-3 strata within each region and then selected by using a systematic sampling procedure with probability proportional to size (PPS), where the measure of size is the number of agricultural households in the EA. Before the selection, within each stratum and domain (region), the Enumeration Areas (EAs) were ordered according to the codes of District and Council which reflect the geographical proximity, and then ordered according to the codes of Constituency, Division, Wards, and Village. An implicit stratification was also performed, ordering by Urban/Rural type at Ward level.

In the second stage, a simple random sampling selection was conducted . In hamlets with more than 200 households, twelve (12) agricultural households were drawn from the PHC 2022 list with a simple random sampling without replacement procedure in each sampled hamlet. In hamlets with 200 households or less, a listing exercise was carried out in each sampled hamlet, and twelve (12) agricultural households were selected with a simple random sampling without replacement procedure. A total of 1,352 PSUs were selected from the 2022 Population and Housing Census frame, of which 1,234 PSUs were from Mainland Tanzania and 118 from Zanzibar. A total number of 16,224 agricultural households were sampled (14,808 households from Mainland Tanzania and 1,416 from Zanzibar).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2022/23 Annual Agricultural Survey used two main questionnaires consolidated into a single questionnaire within the CAPIthe CAPI System, Smallholder Farmers and Large-Scale Farms Questionnaire. Smallholder Farmers questionnaire captured information at household level while Large Scale Farms questionnaire captured information at establishment/holding level. These questionnaires were used for data collection that covered core agricultural activities (crops, livestock, and fish farming) in both short and long rainy seasons. The 2022/23 AASS questionnaire covered 23 sections which are:

1. COVER; The cover page included the title of the survey, survey year (2022/23), general instructions for both the interviewers and respondents. It sets the context for the survey and also it shows the survey covers the United Republic of Tanzania.

2. SCREENING: Included preliminary questions designed to determine if the respondent or household is eligible to participate in the survey. It checks for core criteria such as involvement in agricultural activities.

3. START INTERVIEW: The introductory section where basic details about the interview are recorded, such as the date, location, and interviewer’s information. This helped in the identification and tracking of the interview process.

4. HOUSEHOLD MEMBERS AND HOLDER IDENTIFICATION: Collected information about all household members, including age, gender, relationship to the household head, and the identification of the main agricultural holder. This section helped in understanding the demographic composition of the agriculture household.

5. FIELD ROSTER: Provided the details of the various agricultural fields operated by the agriculture household. Information includes the size, location, and identification of each field. This section provided a comprehensive overview of the land resources available to the household.

6. VULI PLOT ROSTER: Focused on plots used during the Vuli season (short rainy season). It includes details on the crops planted, plot sizes, and any specific characteristics of these plots. This helps in assessing seasonal agricultural activities.

7. VULI CROP ROSTER: Provided detailed information on the types of crops grown during the Vuli season, including quantities produced and intended use (e.g., consumption, sale, storage). This section captures the output of short rainy season farming.

8. MASIKA PLOT ROSTER: Similar to Section 4 but focuses on the Masika season (long rainy season). It collects data on plot usage, crop types, and sizes. This helps in understanding the agricultural practices during the primary growing season.

9. MASIKA CROP ROSTER: Provided detailed information on crops grown during the Masika season, including production quantities and uses. This section captures the output from the main agricultural season.

10. PERMANENT CROP PRODUCTION: Focuses on perennial or permanent crops (e.g., fruit trees, tea, coffee). It includes data on the types of permanent crops, area under cultivation, production volumes, and uses. This section tracks long-term agricultural investments.

11. CROP HARVEST USE: In this, provided the details how harvested crops are utilized within the household. Categories included consumption, sale, storage, and other uses. This section helps in understanding food security and market engagement.

12. SEED AND SEEDLINGS ACQUISITION: Collected information on how the agriculture household acquires seeds and seedlings, including sources (e.g., purchased, saved, gifted) and types (local, improved, etc). This section provided insights into input supply chains and planting decisions based on the households, or head.

13. INPUT USE AND ACQUISITION (FERTILIZERS AND PESTICIDES): It provided the details of the use and acquisition of agricultural inputs such as fertilizers and pesticides. It included information on quantities used, sources, and types of inputs. This section assessed the input dependency and agricultural practices.

14. LIVESTOCK IN STOCK AND CHANGE IN STOCK: The questionnaire recorded the