Corn rose to 433.53 USd/BU on December 2, 2025, up 0.01% from the previous day. Over the past month, Corn's price has fallen 0.17%, but it is still 2.43% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on December of 2025.

This data product provides three Excel file spreadsheet models that use futures prices to forecast the U.S. season-average price received and the implied CCP for three major field crops (corn, soybeans, and wheat).

Using Futures Prices to Forecast the Season-Average Price and Counter-Cyclical Payment Rate for Corn, Soybeans, and Wheat

Farmers and policymakers are interested in the level of counter-cyclical payments (CCPs) provided by the 2008 Farm Act to producers of selected commodities. CCPs are based on the season-average price received by farmers. (For more information on CCPs, see the ERS 2008 Farm Bill Side-By-Side, Title I: Commodity Programs.)

This data product provides three Excel spreadsheet models that use futures prices to forecast the U.S. season-average price received and the implied CCP for three major field crops (corn, soybeans, and wheat). Users can view the model forecasts or create their own forecast by inserting different values for futures prices, basis values, or marketing weights. Example computations and data are provided on the Documentation page.

Spreadsheet Models

For each of the three major U.S. field crops, the Excel spreadsheet model computes a forecast for:

1. the national-level season-average price received by farmers and
2. the implied counter-cyclical payment rate.

Note: the model forecasts are not official USDA forecasts. See USDA's World Agricultural Supply and Demand Estimates for official USDA season-average price forecasts. See USDA's Farm Service Agency information for official USDA CCP rates.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: Webpage with links to Excel files For complete information, please visit https://data.gov.

Basis reflects both local and global supply and demand forces. It is calculated as the difference between the local cash price and the futures price. It affects when and where many grain producers and shippers buy and sell grain. Many factors affect basis—such as local supplies, storage and transportation availability, and global demand—and they interact in complex ways. How changes in basis manifest in transportation is likewise complex and not always direct. For instance, an increase in current demand will drive cash prices up relative to future prices, and increase basis. At the same time, grain will enter the transportation system to fulfill that demand. However, grain supplies also affect basis, but will have the opposite effect on transportation. During harvest, the increase in the supply of grain pushes down cash prices relative to futures prices, and basis weakens, but the demand for transportation increases to move the supplies.

For more information on how basis is linked to transportation, see the story, "Grain Prices, Basis, and Transportation" (https://agtransport.usda.gov/stories/s/sjmk-tkh6), and links below for research on the topic.

This data has corn, soybean, and wheat basis for a variety of locations. These include origins—such as Iowa, Minnesota, Nebraska, and many others—and destinations, such as the Pacific Northwest, Louisiana Gulf, Texas Gulf, and Atlantic Coast.

This is one of three companion datasets. The other two are grain prices (https://agtransport.usda.gov/d/g92w-8cn7) and grain price spreads (https://agtransport.usda.gov/d/an4w-mnp7). These datasets are separate, because the coverage lengths differ and missing values are removed (e.g., there needs to be a cash price and a futures price to have a basis price).

The cash price comes from the grain prices dataset and the futures price comes from the appropriate futures market, which is Chicago Board of Trade (CME Group) for corn, soybeans, and soft red winter wheat; Kansas City Board of Trade (CME Group) for hard red winter wheat; and the Minneapolis Grain Exchange for hard red spring wheat.

Headlines of Corn and Soybean

Headlines extracted from http://soybeansandcorn.com/

Monthly Average - Chicago Board of Trade (CBOT)

https://www.macrotrends.net/2531/soybean-prices-historical-chart-data https://www.macrotrends.net/2532/corn-prices-historical-chart-data

Content

The data source of time-series were obtained from the World Agricultural Supply and Demand Estimates (WAOB) from the United States Department of Agriculture (USDA) website.

The period ranges from January 2014 to December 2020. The attributes represent several time-series features, such as planted area, harvested area, yield, beginning stocks, imports, supply, demand (World), and other estimates from countries with the most significant corn and soybean production

The CBOT is a designated contract maker of the CME Group for the future exchange where agricultural commodity contracts are traded, and the prices charged at CBOT are a benchmark in worldwide prices.

We use the textual data extracted from the website Soybean & Corn Advisor. Since 2009, the website has provided daily news and information on soybean and corn production related to the South American growth cycles, climate, infrastructure, land use, ethanol, and alternative fuel production.

Files: - All_Headlines: All headlines from 2014 to 2020 on the website (http://soybeansandcorn.com). - All_News_Corn_Soybean: All headlines and News from 2014 to 2020 on the website (http://soybeansandcorn.com). - Headlines_Corn/Soybean: headlines that have the word corn/soybean. Label2: 0 is neutral or downtrend; 1 is uptrend. Label3: -1 is downtrend ; 0 neutral; 1 uptrend. A variation of 1% of the monthly average was used for the attribution of labels. - USDA Corn/soybean: reports WASDE; - prices_historical_corn/soybean: historical value from CBOT. Source: Macrotrends.

Acknowledgements

The WASDE data is extracted from (public domain) monthly reports produced by the U. S. Department of Agriculture. The Corn and Soybean Advisor website for offering daily textual content. The macrotends by offering historical value

Inspiration

This data set was designed for forecasting tasks that consider textual data.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Corn (WPU012202) from Jan 1971 to Aug 2025 about corn, vegetables, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

Prices are a fundamental component of exchange and have long been important to the functioning of agricultural markets. Grain prices are closely related to grain transportation, where the supply and demand for grain simultaneously determines both the price of grain, as well as the demand for grain transportation.

This data has corn, soybean, and wheat prices for a variety of locations. These include origins—such as Iowa, Minnesota, Nebraska, and many others—and destinations, such as the Pacific Northwest, Louisiana Gulf, Texas Gulf, and Atlantic Coast.

The data come from three sources: USDA-AMS Market News price reports, GeoGrain, and U.S. Wheat Associates. Links are included below. GeoGrain offers granular data for purchase. The GeoGrain data here is an average of those granular prices for a given state (and the "Southeast" region, which combines Arkansas, Mississippi, and Alabama).

This is one of three companion datasets. The other two are grain basis (https://agtransport.usda.gov/d/v85y-3hep) and grain price spreads (https://agtransport.usda.gov/d/an4w-mnp7). These datasets are separate, because the coverage lengths differ and missing values are removed (e.g., there needs to be a cash price and a futures price to have a basis price).

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.

Wheat fell to 529.25 USd/Bu on December 1, 2025, down 0.33% from the previous day. Over the past month, Wheat's price has fallen 2.62%, and is down 1.53% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Wheat - values, historical data, forecasts and news - updated on December of 2025.

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.

Soybeans rose to 1,130.79 USd/Bu on December 2, 2025, up 0.25% from the previous day. Over the past month, Soybeans's price has risen 0.99%, and is up 14.02% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Soybeans - values, historical data, forecasts and news - updated on December of 2025.

North America Feed Enzymes Market Size was valued at USD 551 Million in 2024 and is projected to reach USD 893 Million by 2032, growing at a CAGR of 6% from 2026 to 2032.Key Market Drivers:Increasing Meat Consumption and Production: The steady increase in meat consumption across North America is driving demand for feed enzymes. According to the USDA Economic Research Service, the average American consumed about 225 pounds of meat per capita in 2023, up 2.7% from the previous year. In 2023, commercial red meat production in the United States will reach 55.3 billion pounds, while broiler production will be 46.2 billion pounds. This significant production volume requires optimized feed efficiency, which enzymes provide.Feed Cost Volatility and Price Pressures: Farmers are increasingly using feed enzymes to reduce the impact of fluctuating grain prices. According to the USDA National Agricultural Statistics Service, corn prices will average $4.85 per bushel in 2023, with seasonal fluctuations of up to 18%. The USDA Economic Research Service estimates that feed accounts for 60-70% of total livestock production costs. Feed enzymes, which typically cost $0.50-2.00 per ton but improve feed conversion ratios by 3-5%, provide significant economic benefits during periods of commodity price volatility.

Replication data for "Trade policy announcements can increase price volatility in global food commodity markets":

Original dataset on trade policy announcements from 2005 to 2017 for wheat and maize (corn) (details in codebook)

Daily price ranges based on the highest and lowest price recorded for wheat and corn futures (traded at the Chicago Board of Trade, CBOT)

Stocks-to-use data for the United States, which is compiled by the United States Department for Agriculture (USDA) and available at monthly frequency from their World Supply and Demand Estimates report

This dataset includes soil health, crop biomass, and crop yield data for a 13-year corn stover harvest trial in central Iowa. Following the release in 2005 of the Billion Ton Study assessment of biofuel sources, several soil health assessments associated with harvesting corn stover were initiated across ARS locations to help provide industry guidelines for sustainable stover harvest. This dataset is from a trial conducted by the National Laboratory for Agriculture and Environment from 2007-2021 at the Iowa State University Ag Engineering and Agronomy farm. Management factors evaluated in the trial included the following.

Stover harvest rate at three levels: No, moderate (3.5 ± 1.1 Mg ha-1 yr-1), or high (5.0 ± 1.7 Mg ha-1 yr-1) stover harvest rates. No-till versus chisel-plow tillage. Originally, the 3 stover harvest rates were evaluated in a complete factorial design with tillage system. However, the no-till, no-harvest system performed poorly in continuous corn and was discontinued in 2012 due to lack of producer interest. Cropping sequence. In addition to evaluating continuous corn for all stover harvest rates and tillage systems, a corn-alfalfa rotation, and a corn-soybean-wheat rotation with winter cover crops were evaluated in a subset of the tillage and stover harvest rate treatments. One-time additions of biochar in 2013 at rates of either 9 Mg/ha or 30 Mg/ha were evaluated in a continuous corn cropping system.

The dataset includes: 1) Crop biomass and yields for all crop phases in every year. 2) Soil organic carbon, total carbon, total nitrogen, and pH to 120 cm depth in 2012, 2016, and 2017. Soil cores from 2005 (pre-study) were also sampled to 90 cm depth. 3) Soil chemistry sampled to 15 cm depth every 1-2 years from 2007 to 2017. 4) Soil strength and compaction was assessed to 60 cm depth in April 2021. These data have been presented in several manuscripts, including Phillips et al. (in review), O'Brien et al. (2020), and Obrycki et al. (2018). Resources in this dataset:Resource Title: R Script for Phillips et al. 2022. File Name: Field 70-71 Analysis Script_AgDataCommons.RResource Description: This R script includes analysis and figures for Phillips et al. "Thirteen-year Stover Harvest and Tillage Effects on Soil Compaction in Iowa". It focuses primarily on the soil compaction and strength data found in "Field 70-71 ConeIndex_BulkDensityDepths_2021". It also includes analysis of corn yields from "Field 70-71 CornYield_2008-2021" and weather conditions from "PRISM_MayTemps" and "Rainfall_AEA".Resource Software Recommended: R version 4.1.3 or higher,url: https://cran.r-project.org/bin/windows/base/ Resource Title: Field 70-71 ConeIndex_BulkDensityDepths_2021. File Name: Field 70-71 ConeIndex_BulkDensityDepths_2021.csvResource Description: This dataset provides an assessment of soil strength (penetration resistance) and soil compaction (bulk density) to 60 cm depth, in continuous corn plots. Penetration resistance was measured in most-trafficked and least-trafficked areas of the plots to assess compaction from increased traffic associated with stover harvest. This spreadsheet also has associated data, including soil water, carbon, and organic matter content. Data were collected in April 2021 and are described in Phillips et al. (in review, 2022).Resource Title: Field 70-71 CornYield_2008-2021. File Name: Field 70-71 CornYield_2008-2021_ForR.csvResource Description: This dataset provides corn stover biomass and grain yields from 2008-2021. Note that this dataset is just for corn, which were presented in Phillips et al., 2022. Yields for all crop phases, including soybeans, wheat, alfalfa, and winter cover crops, are in the file "Field 70-71 Crop Yield File 2008-2020".Resource Title: PRISM_MayTemps. File Name: PRISM_MayTemps.csvResource Description: Average May temperatures during the study period, obtained from interpolation of regional weather stations using the PRISM climate model (https://prism.oregonstate.edu/). These data were used to evaluate how spring temperatures may have impacted corn establishment.Resource Title: Rainfall_AEA. File Name: Rainfall_AEA.csvResource Description: Daily rainfall for the study location, 2008-2021. Data were obtained from the Iowa Environmental Mesonet (https://mesonet.agron.iastate.edu/rainfall/). Title: Field 70-71 Plot Status 2007-2021. File Name: Field 70-71 Plot Status 2007-2021.xlsxResource Description: This file contains descriptions of experimental treatments and diagrams of plot layouts as they were modified through several phases of the trial. Also includes an image of plot locations relative to NRCS soil survey map units.Resource Title: Field 70-71 Deep Soil Cores 2012-2017. File Name: Field 70-71 Deep Soil Cores 2012-2017.xlsxResource Description: Soil carbon, nitrogen, organic matter, and pH to 120 cm depth in 2012, 2016, and 2017.Resource Title: Field 70-71 Baseline Deep Soil Cores 2005. File Name: Field 70-71 Baseline Deep Soil Cores 2005.csvResource Description: Baseline soil carbon, nitrogen, and pH data from an earlier trial in 2005, prior to stover trial establishment.Resource Title: Field 70-71 Crop Yield File 2008-2020. File Name: Field 70-71 Crop Yield File 2008-2020.xlsxResource Description: Yields for all crops in all cropping sequences, 2008-2020. Some of the crop sequences have not been summarized in publications.Resource Title: Field 70-71 Surface Soil Test Data 2007-2021. File Name: Field 70-71 Surface Soil Test Data 2007-2021.xlsxResource Description: Soil chemistry data, 0-15 cm, collect near-annually from 2007 to 2021. Most analyses were performed by Harris Laboratories (now AgSource) in Lincoln, Nebraska, USA. Resource Title: Iowa Stover Harvest Trial Data Dictionary. File Name: Field 70-71 Data Dictionary.xlsxResource Description: Data dictionary for all data files.

This dataset provides county-level data for Nitrogen fertilizer applied to county croplands [1000 kg N/yr]. This includes only those crops used in an assessment of greenhouse gas production from US agriculture using the DNDC agro-ecosystem model [see, for example, Li et al. (1992), J. Geophys. Res., 97:9759-9776; Li et al. (1996) Global Biogeochem. Cycles, 10:297-306]. Cropland area statistics are from the National Agricultural Statistical Service (NASS) for 1990 for most crops, though some are 1992 data from the Census of Agriculture. Data represent total of irrigated and non-irrigated areas. (see NASS Crops County Data).

This is based on 'typical' nitrogen fertilization rates for each of the crops. The fertilizer application rates (see Table below) were derived from USDA NASS state agricultural statistics bulletins.

Crop Typical' N Fert. Rate (kg N/ha) Alfalfa 0 Barley 75 Corn (grain & silage) 125 Cotton 100 Edible Bean 0 Idle Cropland 0 Non-Legume Hay 25 Oats 75 Pasture 0 Peanut 0 Potatoes 250 Rice 140 Sorghum 75 Soybean 0 Spring Wheat 50 Sugarbeets 150 Sugarcane 200 Sunflower 100 Tobacco 100 Vegetables 100 Winter Wheat 75

County crop areas were multiplied by the nitrogen fertilization rates given above to determine total N-fertilization of these croplands per year. The 1990 national total N fertilizer use calculated by this method (8.5 million tonnes N/yr) is 83% of the 1990 national N-fertilizer sales (10.3 million tonnes N/yr). The sales total is expected to be larger because it will include fertilizer sold for other uses (eg. lawns, golf courses, other non-crop uses) as well as farm-use fertilizer applied to crops not included in the crop database (eg. vineyards, orchards, sod). The source for N fertilizer sales is American Assoc. of Plant Food Control Officials, 103 Regulatory Services Building; University of Kentucky; Lexington, KY 40546-0275; Phone (606)257-2668 fax (606)257-7351.

EOS-WEBSTER provides seven datasets which provide county-level data on agricultural management, crop production, livestock, soil properties, geography and population. These datasets were assembled during the mid-1990's to provide driving variables for an assessment of greenhouse gas production from US agriculture using the DNDC agro-ecosystem model [see, for example, Li et al. (1992), J. Geophys. Res., 97:9759-9776; Li et al. (1996) Global Biogeochem. Cycles, 10:297-306]. The data (except nitrogen fertilizer use) were all derived from publicly available, national databases. Each dataset has a separate DIF.

The US County data has been divided into seven datasets.

US County Data Datasets:

1) Agricultural Management 2) Crop Data (NASS Crop data) 3) Crop Summary (NASS Crop data) 4) Geography and Population 5) Land Use 6) Livestock Populations 7) Soil Properties

This dataset shows active grain (corn, soybeans, wheat, and sorghum) rail tariff rates to the Mexico border for a number of U.S. locations, border crossings, car types, and shipment sizes for BNSF, Union Pacific, and Kansas City Southern (KCS). These rates are Rule 11 rates, where a through rate from a U.S. origin to a Mexico destination is divided into a rate from a U.S. origin to the border and a rate from the border to a Mexico destination. The U.S. railroads began reporting only Rule 11 rates to the border in January 2022 following the implementation of a VAT tax on the Mexican portion of the rail shipment. This dataset only contains rates on the U.S. to-the-border portion of the shipment.

The rates are collected from the BNSF, UP, and KCS websites. The railroads do not update the tariffs on defined interval, but do typically have at least one update a year before that commodity's harvest season. The tariff rates are joined to fuel surcharges that are updated monthly. A row in the dataset represents the active tariff rate for that shipment type (route, size, etc.) and the fuel surcharge for that railroad in a particular month. In the case where a tariff rate is changed mid-month, the row is an average of any rates that were active during that month.

Fuel surcharges are published by the railroads on a monthly, per-mile basis and are collected separately from the tariff documents (See USDA's fuel surcharge data at https://agtransport.usda.gov/d/f883-g4tq). To compute a per car fuel surcharge, the U.S. origin to the border rail route distance is approximated using the Department of Transportation's National Rail Network Lines (NARL) dataset and a shortest-path computation.

KCS is now CPKC, but KCS rates are still reported separately at https://web.kcsouthern.com/AgricultureTariff/Default.aspx.

The dataset is intended to capture most of the published tariffs for corn, soybean, and wheat shipments to Mexico. However, some routes and tariff updates may not be included.

SNAP (Soil Nutrient Assessment Program), a component of the USDA/ARS Soil and Water Hub, is a web-based tool that provides an estimate of plant-available nutrients that the soil naturally provides. Soil test fertilizer recommendations have long been predicated upon response curves generated from fertility trials across the country. These response curves have been compared to relative yield which provide probability ranges for a response to varying fertilizer inputs. Category responses include very low, low, adequate, high or very high inversely related to probability of a response to various inputs of nitrogen, phosphate, and potassium (N, P, and K). New soil test methods, increases in computing power and access to the internet have enabled development of an interactive tool that is based on plant available NPK from both the inorganic fraction and organic pool of the soil. The new methods provide an estimate of plant available nutrients that the soil naturally provides, which has largely been ignored for decades. Since we have access to large datasets we can calculate the amounts of NPK required growing crops in lbs NPK per bu of the desired crop. For example, it requires 100 lbs of N, 50 lbs P2O5, 50 lbs K2O to grow 100 bu corn. These are the base numbers from which we subtract the soil test data after converting from the analytical ppm to Lbs P2O5 or lbs K2O. This is a straight subtraction. It also eliminates the need for "calibration data" since the soil tests reflect the soils inherent fertility. Using the example above, of 100, 50, 50 of N, P, and K required and soil test results of 25, 35, 45 then the fertilizer needed would be 75 N, 15 P2O5 and 5 K2O. This is a simple approach that doesn't get lost in relative yield-crop response curves that have been used for decades from differing geographical areas. This tool will include current fertilizer prices, soil test inputs, and crop based county averages for the last 15 years that will predict the chances of making the yield goal the user inputs compared to historical yield data for their county and calculate the fertilizer cost with and without soil testing compared to user input yield goal and county average. This tool will allow the user via the internet to produce a more straightforward approach to realistically planning next year's fertilizer inputs and associated cost. It will also show the benefits of soil testing for increased fertilizer efficiency and reduced environmental impact. Resources in this dataset:Resource Title: Website Pointer to SNAP - Soil Nutrient Assessment Program. File Name: Web Page, url: https://snap.brc.tamus.edu/Home/Index The web dashboard interface for estimating local yield based on field location (state/county), crop (, area, and yield goal; and soil NPK test results (lb/acre), Results returned illustrate local yield, fertilizer cost/acre, fertilizer needed (lb/acre), and overall chance of success (%).