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.

Quick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing 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.

The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). It allows you to customize your query by commodity, location, or time period. You can then visualize the data on a map, manipulate and export the results as an output file compatible for updating databases and spreadsheets, or save a link for future use. Quick Stats contains official published aggregate estimates related to U.S. agricultural production. County level data are also available via Quick Stats. The data include the total crops and cropping practices for each county, and breakouts for irrigated and non-irrigated practices for many crops, for selected States. The database allows custom extracts based on commodity, year, and selected counties within a State, or all counties in one or more States. The county data includes totals for the Agricultural Statistics Districts (county groupings) and the State. The download data files contain planted and harvested area, yield per acre and production. NASS develops these estimates from data collected through:

hundreds of sample surveys conducted each year covering virtually every aspect of U.S. agriculture

the Census of Agriculture conducted every five years providing state- and county-level aggregates Resources in this dataset:Resource Title: Quick Stats database. File Name: Web Page, url: https://quickstats.nass.usda.gov/ Dynamic drill-down filtered search by Commodity, Location, and Date range, beginning with Census or Survey data. Filter lists are refreshed based upon user choice allowing the user to fine-tune the search.

Brochure Theme: S5 – Statistical data – Agriculture Under Theme: S510.A1 – Agricultural statistics

The Census of Agriculture is a complete count of U.S. farms and ranches and the people who operate them. Even small plots of land - whether rural or urban - growing fruit, vegetables or some food animals count if $1,000 or more of such products were raised and sold, or normally would have been sold, during the Census year. The Census of Agriculture, taken only once every five years, looks at land use and ownership, operator characteristics, production practices, income and expenditures. For America's farmers and ranchers, the Census of Agriculture is their voice, their future, and their opportunity. The Census Data Query Tool (CDQT) is a web-based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. The data found via the CDQT may also be accessed in the NASS Quick Stats database. The CDQT is unique in that it automatically displays data from the past five Census of Agriculture publications. The CDQT is presented as a "2017 centric" view of the Census of Agriculture data. All data series that are present in the 2017 dataset are available within the CDQT, and any matching data series from prior Census years will also display (back to 1997). If a data series is not included in the 2017 dataset, then data cells will remain blank in the tool. For example, one of the data series had a label change from "Operator" to "Producer." This means that data from prior Census years labelled "Operator" will not show up where the label has changed to “Producer” for 2017. The new Census Data Query Tool application can be used to query Census data from 1997 through 2017. Data are searchable by Census table and are downloadable as CSV or PDF files. 2017 Census Ag Atlas Maps are also available for download. Resources in this dataset:Resource Title: 2017 Census of Agriculture - Census Data Query Tool (CDQT). File Name: Web Page, url: https://www.nass.usda.gov/Quick_Stats/CDQT/chapter/1/table/1 The Census Data Query Tool (CDQT) is a web based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. The data found via the CDQT may also be accessed in the NASS Quick Stats database. The CDQT is unique in that it automatically displays data from the past five Census of Agriculture publications. The CDQT is presented as a "2017 centric" view of the Census of Agriculture data. All data series that are present in the 2017 dataset are available within the CDQT, and any matching data series from prior Census years will also display (back to 1997). If a data series is not included in the 2017 dataset, then data cells will remain blank in the tool. For example, one of the data series had a label change from "Operator" to "Producer." This means that data from prior Census years labelled "Operator" will not show up where the label has changed to "Producer" for 2017. Using CDQT:

Upon entering the CDQT, a data table is present. Changing the parameters at the top of the data table will retrieve different combinations of Census Chapter, Table, State, or County (when selecting Chapter 2). For the U.S., Volume 1, US/State Chapter 1 will include only U.S. data; Chapter 2 will include U.S. and State level data. For a State, Volume 1 US/State Level Data Chapter 1 will include only the State level data; Chapter 2 will include the State and county level data. Once a selection is made, press the “Update Grid” button to retrieve the new data table. Comma-separated values (CSV) download, compatible with most spreadsheet and database applications: to download a CSV file of the data as it is currently presented in the data grid, press the "CSV" button in the "Export Data" section of the toolbar. When CSV is chosen, data will be downloaded as numeric. To view the source PDF file for the data table, press the "View PDF" button in the toolbar.

Statistics on agriculture in Massachusetts

The Census of Agriculture is disseminated by Statistics Canada's standard geographic units (boundaries). Since these census units do not reflect or correspond with biophysical landscape units (such as ecological regions, soil landscapes or drainage areas), Agriculture and Agri-Food Canada in collaboration with Statistics Canada's Agriculture Division, have developed a process for interpolating (reallocating or proportioning) Census of Agriculture information from census polygon-based units to biophysical polygon-based units.

In the “Interpolated census of agriculture”, suppression confidentiality procedures were applied by Statistics Canada to the custom tabulations to prevent the possibility of associating statistical data with any specific identifiable agricultural operation or individual. Confidentiality flags are denoted where "-1" appears in data cell. This indicates information has been suppressed by Statistics Canada to protect confidentiality. Null values/cells simply indicate no data is reported.

A direct internet link to Solomon Island's agriculture statistics at a glance and other related information.

Abstract

For more than 150 years, the U.S. Department of Commerce, Bureau of the Census, conducted the census of agriculture. However, the 2002 Appropriations Act transferred the responsibility from the Bureau of the Census to the U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). The 2007 Census of Agriculture for the U.S. Virgin Islands is the second census in the U.S. Virgin Islands conducted by NASS. The census of agriculture is taken to obtain agricultural statistics for each county, State (including territories and protectorates), and the Nation. The first U.S. agricultural census data were collected in 1840 as a part of the sixth decennial census. From 1840 to 1920, an agricultural census was taken as a part of each decennial census. Since 1920, a separate national agricultural census has been taken every 5 years. The 2007 census is the 14th census of agriculture of the U.S. Virgin Islands. The first, taken in 1920, was a special census authorized by the Secretary of Commerce. The next agriculture census was taken in 1930 in conjunction with the decennial census, a practice that continued every 10 years through 1960. The 1964 Census of Agriculture was the first quinquennial (5-year) census to be taken in the U.S. Virgin Islands. In 1976, Congress authorized the census of agriculture to be taken for 1978 and 1982 to adjust the data-reference year to coincide with the 1982 Economic Censuses covering manufacturing, mining, construction, retail trade, wholesale trade, service industries, and selected transportation activities. After 1982, the agriculture census reverted to a 5-year cycle. Data in this publication are for the calendar year 2007, and inventory data reflect what was on hand on December 31, 2007. This is the same reference period used in the 2002 census. Prior to the 2002 census, data was collected in the summer for the previous 12 months, with inventory items counted as what was on hand as of July 1 of the year the data collection was done.

Objectives: The census of agriculture is the leading source of statistics about the U.S. Virgin Islands’s agricultural production and the only source of consistent, comparable data at the island level. Census statistics are used to measure agricultural production and to identify trends in an ever changing agricultural sector. Many local programs use census data as a benchmark for designing and evaluating surveys. Private industry uses census statistics to provide a more effective production and distribution system for the agricultural community.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was a farm, defined as "any place from which USD 500 or more of agricultural products were produced and sold, or normally would had been sold, during the calendar year 2007". According to the census definition, a farm is essentially an operating unit, not an ownership tract. All land operated or managed by one person or partnership represents one farm. In the case of tenants, the land assigned to each tenant is considered a separate farm, even though the landlord may consider the entire landholding to be one unit rather than several separate units.

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Method of Enumeration As in the previous censuses of the U.S. Virgin Islands, a direct enumeration procedure was used in the 2007 Census of Agriculture. Enumeration was based on a list of farm operators compiled by the U.S. Virgin Islands Department of Agriculture. This list was compiled with the help of the USDA Farm Services Agency located in St. Croix. The statistics in this report were collected from farm operators beginning in January of 2003. Each enumerator was assigned a list of individuals or farm operations from a master enumeration list. The enumerators contacted persons or operations on their list and completed a census report form for all farm operations. If the person on the list was not operating a farm, the enumerator recorded whether the land had been sold or rented to someone else and was still being used for agriculture. If land was sold or rented out, the enumerator got the name of the new operator and contacted that person to ensure that he or she was included in the census.

(b) Frame The census frame consisted of a list of farm operators compiled by the U.S. Virgin Islands DA. This list was compiled with the help of the USDA Farm Services Agency, located in St. Croix.

(c) Complete and/or sample enumeration methods The census was a complete enumeration of all farm operators registered in the list compiled by the United States of America in the CA 2007.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire (report form) for the CA 2007 was prepared by NASS, in cooperation with the DA of the U.S. Virgin Islands. Only one questionnaire was used for data collection covering topics on:

• Land owned
• Land use
• Irrigation
• Conservation programs and crop insurance
• Field crops
• Bananas, coffee, pineapples and plantain crops
• Hay and forage crops
• Nursery, Greenhouse, Floriculture, Sod and tree seedlings
• Vegetables and melons
• Hydroponic crops
• Fruit
• Root crops
• Cattle and calves
• Poultry
• Hogs and pigs
• Aquaculture
• Other animals and livestock products
• Value of sales
• Organic agriculture
• Federal and commonwealth agricultural program payments
• Income from farm-related sources
• Production expenses
• Farm labour
• Fertilizer and chemicals applied
• Market value of land and buildings
• Machinery, equipment and buildings
• Practices
• Type of organization
• Operator characteristics

The questionnaire of the 2007 CA covered 12 of the 16 core items' recommended for the WCA 2010 round.

Cleaning operations

DATA PROCESSING The processing of the 2007 Census of Agriculture for the U.S. Virgin Islands was done in St. Croix. Each report form was reviewed and coded prior to data keying. Report forms not meeting the census farm definition were voided. The remaining report forms were examined for clarity and completeness. Reporting errors in units of measures, illegible entries, and misplaced entries were corrected. After all the report forms had been reviewed and coded, the data were keyed and subjected to a thorough computer edit. The edit performed comprehensive checks for consistency and reasonableness, corrected erroneous or inconsistent data, supplied missing data based on similar farms, and assigned farm classification codes necessary for tabulating the data. All substantial changes to the data generated by the computer edits were reviewed and verified by analysts. Inconsistencies identified, but not corrected by the computer, were reviewed, corrected, and keyed to a correction file. The corrected data were then tabulated by the computer and reviewed by analysts. Prior to publication, tabulated totals were reviewed by analysts to identify inconsistencies and potential coverage problems. Comparisons were made with previous census data, as well as other available data. The computer system provided the capability to review up-to-date tallies of all selected data items for various sets of criteria which included, but were not limited to, geographic levels, farm types, and sales levels. Data were examined for each set of criteria and any inconsistencies or potential problems were then researched by examining individual data records contributing to the tabulated total. W hen necessary, data inconsistencies were resolved by making corrections to individual data records.

Sampling error estimates

The accuracy of these tabulated data is determined by the joint effects of the various nonsampling errors. No direct measures of these effects have been obtained; however, precautionary steps were taken in all phases of data collection, processing, and tabulation of the data in an effort to minimize the effects of nonsampling errors.

Abstract

The agricultural survey in its current form covers all regions of the country and all 45 departments of Senegal. The agricultural survey is an annual statistical operation whose general objective is to estimate the level of the main agricultural output of family-type agricultural holdings. It also provides information on the physical characteristics of cultivated plots (geo-location, area) and major investments made in them (agricultural inputs, cultivation operations, soil management and restoration). The main indicators relate to yield levels, areas sown, production and means of production.

Following a modular approach, the 2022-2023 edition of the annual agricultural survey is characterized by the integration of the MEA module (Machines, Equipment and other Agricultural Assets). In addition, the basic module of the 50x2030 questionnaire allows the collection of data for the calculation of SDG 5.a.1.

Geographic coverage

The annual agricultural survey covers all 45 departments of Senegal. However, for reasons related to anonymization, the variable "Department" has been replaced by the variable "Agroecological Zone" which constitutes groupings in relation to the departments. The variable "Region" remains in the anonymized version of the data.

Analysis unit

Households and agricultural plots

Universe

The agricultural survey covers all households and plots in the 45 departments of Senegal.

Kind of data

Sample survey data [ssd]

Sampling procedure

The AAS was built on a two-stage survey, with census districts (CDs) as primary units (PUs) and agricultural households as secondary units (SUs), as defined during the general census of population and l'Habitat, de l'Agriculture et de l'Élevage (RGPHAE) of 2013. In line with the broadening of the scope of the survey recommended by the AGRIS approach, from this campaign onwards the sample design incorporated a first-stage stratification, induced by the second-stage stratification, to better reflect the various agricultural activities and improve the efficiency of the estimates. The choice of a first-degree stratification induced by that of the second degree, although less efficient than an independent first-degree stratification, was guided by the constraint of non-existence of relevant variables of interest in the sampling frame of the RGPHAE to discriminate against the CDs. The stratification took into account the relative importance of the main agricultural activities (in terms of household size) identified during the 2013 RGPHAE, namely rainfed agriculture, livestock and horticulture.

Thus, four strata were formed as follows: - the "rainfed only" stratum which groups together all the households practicing only rainfed crops; - the "livestock only" stratum for households that practice animal husbandry only; - the "Horticulture and other crops" stratum, which includes households that mainly practice horticulture and secondarily other crops (forestry, fruit growing, etc.); - the "Rainfed-livestock" stratum made up of households that practice both rainfed agriculture and livestock breeding.

The size of the sample of agricultural households to be surveyed was calculated by department (area of study) by setting a relative error of 10% on the variable of interest. The distribution of the sample of each department in the strata was made using the Bankier method (1988) developed in the methodological guide to the main sampling frame practices (pp. 79-81) of the Global Strategy for Agricultural and Rural Statistics (GSARS).

At the national level, the total theoretical sample is equal to 7,450 households, spread over 1,460 physical CDs, with 5 households per CD. At the end of the enumeration operation carried out in the physical sample CDs, adjustments were made to take into account the actual updated size of the CDs, which led to a final size of 7,378 households, or 1,382 CDs.

Sampling deviation

Compared to the survey plan, adjustments were made based on the response rate at each phase.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The first questionnaire collected information on census and characteristics of agricultural household plots. The second questionnaire collected information on agricultural production, machinery, equipment and agricultural productivity.

Response rate

First phase: sample of 7378 households, including 6360 surveyed, i.e. a coverage rate of 86%.

Second phase: sample of 7218 households, including 6,834 surveyed, i.e. a coverage rate of 95%.

Brochure Theme: S5 – Statistical data – Agriculture Under Theme:S510.A1 – Agricultural statistics S5 – Statistical data – Agriculture

Under Theme: S510.A1 – Agricultural statistics

United States Crop Production: Taro data was reported at 3,686.000 lb th in 2017. This records an increase from the previous number of 3,502.000 lb th for 2015. United States Crop Production: Taro data is updated yearly, averaging 4,300.000 lb th from Dec 1997 (Median) to 2017, with 20 observations. The data reached an all-time high of 7,000.000 lb th in 2000 and a record low of 3,100.000 lb th in 2013. United States Crop Production: Taro data remains active status in CEIC and is reported by National Agricultural Statistics Service. The data is categorized under Global Database’s USA – Table US.B068: Agriculture Crop Production.

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 for 2024 are provisional, all other figures are final.

Changes as of November 28, 2024: the provisional 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.

The statistic shows the gross production value of agriculture in China between 2013 and 2023. In 2023, the agricultural production value in China amounted to around 8.71 trillion yuan.

The value of artificial intelligence in the global agriculture market was estimated to be around 1.7 billion U.S. dollars in 2023 and is forecast to grow to about 4.7 billion U.S. dollars by 2028.

Success.ai’s Agricultural Data provides unparalleled access to verified profiles of agriculture and farming leaders worldwide. Sourced from over 700 million LinkedIn profiles, this dataset includes actionable insights and contact details for professionals shaping the global agricultural landscape. Whether your objective is to market agricultural products, establish partnerships, or analyze industry trends, Success.ai ensures your outreach is powered by accurate, enriched, and continuously updated data.

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The Cropland Data Layer (CDL) is a crop-specific land cover data layer created annually for the continental United States using moderate resolution satellite imagery and extensive agricultural ground truth. The CDL is created by the USDA, National Agricultural Statistics Service (NASS), Research and Development Division, Geospatial Information Branch, Spatial Analysis Research Section. For detailed FAQ please visit CropScape and Cropland Data Layers - FAQs. To explore details about the classification accuracies and utility of the data, see state-level omission and commission errors by crop type and year. The asset date is aligned with the calendar year of harvest. For most crops the planted and harvest year are the same. Some exceptions: winter wheat is unique, as it is planted in the prior year. A hay crop like alfalfa could have been planted years prior. For winter wheat the data also have a class called "Double Crop Winter Wheat/Soybeans". Some mid-latitude areas of the US have conditions such that a second crop (usually soybeans) can be planted immediately after the harvest of winter wheat and itself still be harvested within the same year. So for mapping winter wheat areas use both classes (use both values 24 and 26). While the CDL date is aligned with year of harvest, the map itself is more representative of what was planted. In other words, a small percentage of fields on a given year will not be harvested. Some non-agricultural categories are duplicate due to two very different epochs in methodology. The non-ag codes 63-65 and 81-88 are holdovers from the older methodology and will only appear in CDLs from 2007 and earlier. The non-ag codes from 111-195 are from the current methodology which uses the USGS NLCD as non-ag training and will only appear in CDLs 2007 and newer. 2007 was a transition year so there may be both sets of categories in the 2007 national product but will not appear within the same state. Note: The 2024 CDL only has the data band. The cultivated and confidence bands are yet to be released by the provider.

The USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer produced using satellite imagery and extensive agricultural ground reference data. The program began in 1997 with limited coverage and in 2008 forward expanded coverage to the entire Continental United States. Please note that no farmer reported data are derivable from the Cropland Data Layer.

Brochure Theme: S5 – Statistical data – Agriculture

Under Theme: S510.A1 – Agricultural statistics