U.S. Department of Agriculture

Note- "Amount of water used for irrigation per acre of cropland" is calculate as follows: Total - Acre-feet of water applied divided by  Total cropland - Acres

5 AREA DAILY WEIGHTED AVERAGE DIRECT SLAUGHTER CATTLE - NEGOTIATED Texas/Oklahoma/New Mexico; Kansas; Nebraska; Colorado; Iowa/Minnesota feedlots (Includes all transactions regardless of delivery day)  

Sugar Data of United States

The Producer Price Index (PPI) for food measures changes in prices paid to domestic producers for their output. The PPI is similar to the CPI in that it measures price changes over time and is a natural extension of ERS's work with the CPI for food. ERS regularly updates farm and wholesale food price forecasts for the short-term period.

Cost-of-production forecasts for U.S. major field crops, 2022F-2023F. The forecasts are developed as part of the USDA Baseline projections to help develop projected net returns for major field crops. These long-term baseline projections provide a starting point for discussion of alternative outcomes for the agricultural sector under expected or proposed future policies. Cost-of-production is the only forecast at the national level and would differ considerably among regions, individual farmers, and by size of operation. Projected costs are based on 2021 production costs and projected changes in 2022 and 2023 indexes of prices paid for farm inputs.

Note: Data is no longer being updated on source: https://www.ers.usda.gov/topics/international-markets-us-trade/international-consumer-and-food-industry-trends/#data The Dataset contain data on expenditures on food (including nonalcoholic beverages), alcoholic beverages, and tobacco as a share of consumer expenditures on all goods and services for 86 countries. The tables also contain data on per capita consumer expenditures on goods and services, as well as per capita food expenditures for these countries. Data is available for the 104 countries for which this type of information is currently available in the source database, Euromonitor International. All expenditure data are in current U.S. dollars.

This product summarizes fertilizer consumption in the United States by plant nutrient and major fertilizer products—as well as consumption of mixed fertilizers, secondary nutrients, and micro nutrients—for 1960 through the latest year for which statistics are available. The share of planted crop acreage receiving fertilizer, and fertilizer applications per receiving acre (by nutrient), are presented for the major producing States for corn, cotton, soybeans, and wheat (data on nutrient consumption by crop start in 1964). 

FNDDS is a database that provides the nutrient values for foods and beverages reported in What We Eat in America, the dietary intake component of the National Health and Nutrition Examination Survey.

A food dollar represents a $1 expenditure on domestically produced food by U.S. consumers. The food dollar is allocated to expenditures on each of the various food commodities sold in proportions that represent their share of annual sales in the U.S. market.

Food Security Measures for IFSA Countries, 2021 and 2031

Note that values are given for marketing years, e.g. 2016 corresponds to 2015/2016 marketing year, 2015 refers to 2014/2015 marketing year, etc.   Market year starts in December and ends in November of the following year.

Dietary Supplement Ingredient Database. Data cited at: US Department of Agriculture, Agricultural Research Service, Methods and Application of Food Composition Laboratory and US Department of Health and Human Services, National Institutes of Health, Office of Dietary Supplements. Dietary Supplement Ingredient Database (DSID) release 4.0, August 2017. Available from: https://dsid.usda.nih.gov  

Improving agricultural productivity has been the world's primary means of ensuring that the needs of a growing population don't outstrip the ability of humanity to supply food. Over the past 50 years, productivity growth in agriculture has allowed food to become more abundant and cheaper (see Growth in Global Agricultural Productivity: An Update, Amber Waves, November 2013, and New Evidence Points to Robust But Uneven Productivity Growth in Global Agriculture, Amber Waves, September 2012). A broad concept of agricultural productivity is total factor productivity (TFP). TFP takes into account all of the land, labor, capital, and material resources employed in farm production and compares them with the total amount of crop and livestock output. If total output is growing faster than total inputs, we call this an improvement in total factor productivity ("factor" = input). TFP differs from measures like crop yield per acre or agricultural value-added per worker because it takes into account a broader set of inputs used in production. TFP encompasses the average productivity of all of these inputs employed in the production of all crop and commodities livestock. "Growth accounting" provides a practicable way of measuring changes in agricultural TFP across a broad set of countries and regions, and for the world as a whole, given limited international data on production outputs, inputs, and their economic values. The approach (described in detail in Documentation and Methods) gives agricultural TFP growth rates, but not TFP levels, across the countries and regions of the world in a consistent, comparable way. Most of the data for the analysis comes from FAOSTAT. In some cases Food and Agriculture Organization (FAO) input and output data are supplemented with data from national statistical sources. Note: To facilitate international comparisons, certain simplifying assumptions must be made, and as such the estimates of TFP growth reported here may not be exactly the same as TFP growth estimates reported in other studies using different assumptions or methods. In particular, our TFP estimates for the United States differ slightly from those reported in ERS' Agricultural Productivity in the US data product. certain simplifying assumptions must be made, and as such the estimates of TFP growth reported here may not be exactly the same as TFP growth estimates reported in other studies using different assumptions or methods. In particular, our TFP estimates for the United States differ slightly from those reported in ERS' Agricultural Productivity in the US data product. certain simplifying assumptions must be made, and as such the estimates of TFP growth reported here may not be exactly the same as TFP growth estimates reported in other studies using different assumptions or methods. In particular, our TFP estimates for the United States differ slightly from those reported in ERS' Agricultural Productivity in the US data product.

Note: Source no longer update this dataset. This data set contains estimates of total and marginal budget shares and income and price elasticities for nine broad consumption groups and eight food subgroups across 144 countries. Total and marginal budget shares and income and price elasticities are estimated using 2005 International Comparison Program (ICP) data, which is maintained by the ICP Development Data Group of the World Bank

Agriculture is a major user of ground and surface water in the United States, accounting for 80 percent of the Nation's consumptive water use and over 90 percent in many Western States. This ERS research program investigates water allocation, water conservation, and water management issues facing irrigated agriculture. The focus is on irrigated agriculture, but other sectors are examined for their competitive influence on water supplies and impacts of water reallocations among agricultural, environmental, and urban users. It includes consideration of the role of water markets, producer decisions, institutional adjustments (including Federal water infrastructure), and water-related policies with respect to resource costs, water quality, profitability, and environmental effects, as well as analysis of the adoption of water conserving technologies.

Notes: Coefficients of variation (CVs) were checked for the category totals: gross value of production, and feed, operating, allocated overhead, and total costs. All CVs were less than 25 percent.

The data set covers Monthly and Annual milk COP estimates by State. Estimates since 2016 are based on the 2016 Agricultural Resource Management Survey (ARMS) data from milk producers. Estimates for 2010 through 2015 are based on the 2010 and estimates for 2005 through 2009 are based on the 2005 ARMS data from milk producers

Nutritional Values For Common Foods And Products. Interchangeable pairs of aminoacids: Methionine + Cysteine, Phenylalanine + Tyrosine. Other daily values are based on 2000 calorie diet. Nutritional value of a cooked product is provided for the given weight of cooked food. Data from USDA National Nutrient Database for Standard Reference, Release 28.

Nutritional Values For Common Foods And Products. Daily values for aminoacids are based on 155 lbs body weight. Interchangeable pairs of aminoacids: Methionine + Cysteine, Phenylalanine + Tyrosine. Other daily values are based on 2000 calorie diet. Nutritional value of a cooked product is provided for the given weight of cooked food. Data from USDA National Nutrient Database for Standard Reference, Release 28.

Source has been discontinued: https://www.ers.usda.gov/data-products/organic-prices.aspx#44269

Data on private-sector R&D spending in various agricultural input sectors and the food manufacturing industry in both nominal and constant (inflation-adjusted) dollars.

The Quarterly Food-at-Home Price Database (QFAHPD) provides food price data to support research on the economic determinants of food consumption, diet quality, and health outcomes. There are two versions of the database. Version 1 of the Quarterly Food-at-Home Price Database (QFAHPD-1) contains prices for 52 food groups based on both UPC-coded and random-weight food purchases. Quarterly prices are available for: 26 metropolitan markets for 1999-2006, and 9 nonmetropolitan areas for 2002-2006 and 4 nonmetropolitan areas for 1999-2001 Version 2 of the Quarterly Food-at-Home Price Database (QFAHPD-2) contains prices for 54 food groups based on only UPC-coded food purchases. Quarterly prices are available for: 26 metropolitan and 9 nonmetropolitan markets for 2004-2010. As Homescan data become available for future years, plans are to expand the database. A redefined carbonated nonalcoholic beverage group, which now excludes diet versions of beverages. Two new food groups: 1) diet carbonated beverages, and 2) unsweetened coffee and tea. Dry weights for coffee and tea have been converted to liquid equivalents, assuming that 2 grams of dry tea leaves and 10 grams of dry coffee yield 180 ml of liquid beverage.

World: Soybean Area, Yield and Production

ERS analysts track U.S. and international sugar and sweetener production, consumption, and trade. They also monitor and analyze U.S. sweetener policy and events that affect the domestic, Mexican, and other international sweetener markets.   The year 2005 shows data for agricultural season 2005/06.

ERS analysts track U.S. and international sugar and sweetener production, consumption, and trade. They also monitor and analyze U.S. sweetener policy and events that affect the domestic, Mexican, and other international sweetener markets.   The year 1990 shows data for agricultural season 1990/91.

Data on Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) participation and costs. Nation-wide and state level program participation counts and recipiency rates; value of benefits issued and other costs. The US Food Stamp/SNAP program administered by the U.S. Department of Agriculture’s (USDA) Food and Nutrition Service, is the largest food assistance program in the country, reaching more poor individuals over the course of a year than any other public assistance program. Unlike many other public assistance programs, SNAP has few categorical requirements for eligibility, such as the presence of children, elderly, or disabled individuals in a household. As a result, the program offers assistance to a large and diverse population of needy persons, many of whom are not eligible for other forms of assistance.   All data except population estimates originate from USDA Food & Nutrition Service. Sources & notes:For the national-wide totals USDA Food & Nutrition Service national level annual summaries are used. Totals for national level include all states, District of Columbia and island areas, excluding Puerto Rico. Totals for 1975-1982 including Puerto Rico. Puerto Rico initiated Food Stamp operations during FY 1975 and participated through June of FY 1982. A separate Nutrition Assistance Grant began in July 1982.State-level data for 2010-2014 from theUSDA Food & Nutrition Service national level annual summaries. For 2001-2009 - data from USDA SNAP State Activity reports. For the previous years - USDA data from the US Department of Health & Human Services "Welfare Indicators and Risk Factors" annual reports to Congress. Resident population counts are US Census Bureau’s latest estimates; for Guam and Virgin Islands -World Bank Population Estimates & Projections. Totals for United States resident population DOES NOT include Puerto Rico & island areas. Recipiency rates expressed as percentages of total population have been correctly computed using corresponding summary population values

Texas: Supplemental Nutrition Assistance Program 

US Bio Energy Statistics - Supply and Disappearance, FeedStock and Co-products

Commodity and market year for feed grains: Market year for corn and sorghum:- September-August, Market year for barley and oats:- June-May. Coarse grains:- Includes oats, rye, millet, and mixed grains Latest data maybe preliminary or projected.

These are the latest U.S. farm sector income and wealth statistics data. The data include historical U.S. and State-level farm income and wealth estimates, and U.S.-level forecasts for the current calendar year. Data are released three times a year: typically in February, August, and November. The U.S.-level calendar-year forecast is first provided in February, and is updated in August and November. The August release converts the prior year's farm income and balance sheet forecasts to estimates, adds State-level farm income estimates, and revises previous years' estimates. The November release updates the current year's forecast and revises previous years' estimates, as needed. 2022 are forecast values.

Fuel ethanol production facilities capacity and utilization rates are as of January of the year except 2018. For 2019 data is January 2019.

 Annual Price = Avg. Price for the Marketing Year (Sep-Aug); Quarterly data represent values according to Marketing Year (Sep-Aug): Q1 Sep-Nov, Q2 Dec-Feb, Q3 Mar-May, Q4 Jun-Aug.

US Census of Agriculture: Economics

Note: The grain bid summary illustrates the market relationships for commodities. Positive and negative adjustments in differential between terminal and futures markets, and the relationship to inland market points, are indicators of changes in fundamental market supply and demand. The map may be used to monitor market and time differentials.

Cost and return estimates are reported for the United States and major production regions for corn, soybeans, wheat, cotton, grain sorghum, rice, peanuts, oats, barley, milk, hogs, and cow-calf. The series of commodity cost and return estimates for the U.S. and regions is divided into two categories: Recent and Historical estimates. Recent estimates date back to the point of the most recent major revision in accounting methods, account format, and regional definitions for each commodity. Historical estimates date back to when the series began.  Cost-of-Production Forecasts are also available for major U.S. field crops. Organic Costs and Returns for corn, milk, wheat, and soybeans are also available.

This dataset covers the following public data available at US Dept. of Agriculture website. 1. Wheat: Supply and disappearance 2. Hard red winter wheat: Supply and disappearance 3. Hard red spring wheat: Supply and disappearance 4. Soft red winter wheat: Supply and disappearance 5. White wheat: Supply and disappearance 6. U.S. wheat exports by selected destinations (1,000 metric tons) Reference Market year (start from Jun-May) Q 1 in Market year: Jun-August Q 2 in Market year: Sep-Nov Q 3 in Market year: Dec-Feb Q 4 in Market year: March-May

  * Reference Date for the year data are as below 2015 - (17/2/2015) 2016 - (25/3/2016) 2017 - (15/12/2017) * Values for some Indicators are not provided in source due to confidentiality.

Suggested Citation : US Department of Agriculture, Agricultural Research Service. 2016.  Nutrient Data Laboratory.  USDA National Nutrient Database for Standard Reference, Release 28 (Slightly revised). Current Version: May 2016. http://www.ars.usda.gov/nea/bhnrc/mafcl

Avian influenza is caused by influenza Type A virus (influenza A). Avian-origin influenza viruses are broadly categorized based on a combination of two groups of proteins on the surface of the influenza A virus: hemagglutinin or “H” proteins, of which there are 16 (H1-H16), and neuraminidase or “N” proteins, of which there are 9 (N1-N9). Many different combinations of “H” and “N” proteins are possible. Each combination is considered a different subtype, and related viruses within a subtype may be referred to as a lineage. Avian influenza viruses are classified as either “low pathogenic” or “highly pathogenic” based on their genetic features and the severity of the disease they cause in poultry. Most viruses are of low pathogenicity, meaning that they causes no signs or only minor clinical signs of infection in poultry.

Confirmations of Highly Pathogenic Avian Influenza in Commercial and Backyard Flocks Avian influenza is caused by influenza Type A virus (influenza A). Avian-origin influenza viruses are broadly categorized based on a combination of two groups of proteins on the surface of the influenza A virus: hemagglutinin or “H” proteins, of which there are 16 (H1-H16), and neuraminidase or “N” proteins, of which there are 9 (N1-N9). Many different combinations of “H” and “N” proteins are possible. Each combination is considered a different subtype, and related viruses within a subtype may be referred to as a lineage. Avian influenza viruses are classified as either “low pathogenic” or “highly pathogenic” based on their genetic features and the severity of the disease they cause in poultry. Most viruses are of low pathogenicity, meaning that they causes no signs or only minor clinical signs of infection in poultry.

Note: Source has discontinued the update of this data product.  

Note: Source has discontinued the update of this data product.   ERS organic price tables are based on Agricultural Marketing Service (AMS) Market News and other data sources, and show monthly and annual prices over a period of years for major commodities. These tables are useful for examining price trends over time, as well as for comparing organic and conventional prices. The latest organic wholesale prices are always available on the AMS Market News website.   

Note: Source has discontinued the update of this data product. ERS organic price tables are based on Agricultural Marketing Service (AMS) Market News and other data sources, and show monthly and annual prices over a period of years for major commodities. These tables are useful for examining price trends over time, as well as for comparing organic and conventional prices. The latest organic wholesale prices are always available on the AMS Market News website.

World Agricultural Supply and Demand Estimates Report (WASDE): World Supply and Use   Note 1: The dataset considered the market year as follows   2018/19 actual year referred as 2019, 2019/20 Estimated year  referred as 2020 and 2020 for Current Month 2020/2021 Projection year referred as 2020 for Monthly and 2021 for Annual   Note 2: For Regions: -Central Asia, Afr. Fr. Zone, Australia, Thailand, Vietnam For Crop: -Cotton For Indicator: -Production and Imports Values ​​are Less than 5,000 bales.

Note: FY20-21 data is preliminary and FY21-22 is Projection. Yield is on a rough basis, before the milling process. Production is on a milled basis, after the milling process