Corn rose to 388.03 USd/BU on August 22, 2025, up 0.20% from the previous day. Over the past month, Corn's price has fallen 2.63%, and is down 0.76% compared to the same time last year, 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 August of 2025.

Soybeans rose to 1,035.54 USd/Bu on August 22, 2025, up 0.10% from the previous day. Over the past month, Soybeans's price has risen 2.96%, and is up 8.75% 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 August of 2025.

This data set contains Ontario feed grain prices collected by University of Guelph, Ridgetown Campus. The dataset includes daily prices of agricultural commodities at individual elevators in Ontario. Daily highs and lows are given for each commodity, as well as, daily Bank of Canada exchange rates.This dataset includes data from January 1, 2024 to December 31, 2024.

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.

Get statistical data on weekly spot market and forward contract corn prices in Ontario.

Data includes:

• old and new crop Chicago Board of Trade (CBOT) prices
• old and new crop weekly unadjusted basis
• old and new crop weekly adjusted basis
• old crop weekly cash price
• new crop cash price
• cash price spread
• CBOT price spread
• Canadian dollar value
• 5-year average for corn basis
• 10-year average for corn basis
• 10-year average cash price

Statistical data are compiled to serve as a source of agriculture and food statistics for the province of Ontario. Data are prepared primarily by Statistics and Economics staff of the Ministry of Agriculture, Food and Rural Affairs, in co-operation with the Agriculture Division of Statistics Canada and various government departments and farm marketing boards.

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.

This statistic shows the price increase in food commodities between mid-June and mid-July, 2012. The price of corn increased by 33 percent in this period.

Studies comparing profitability of tillage systems often examine narrow historic windows or exclude annual price fluctuations. This study uses a continuous corn (Zea mays L.) (CC; 1970–1990) and corn–soybean Glycine max (L.) Merr. Tillage × Fertilizer study in somewhat poorly drained soils in southern Illinois to reconstruct partial annual budgets with historical prices for crops, fertilizers, lime, herbicides, fuel, labor, and machinery. Combinations of tillage (moldboard plow [MP], chisel tillage [ChT], alternate tillage [AT], and no-till [NT]) and fertilizer (Control, N-only, N+NPK starter, NPK+NPK starter, and NPK broadcast) treatments were evaluated. The CC profits were highest in NPK-applied treatments followed by N-only and Control. The MP treatments were similar to ChT and more profitable than NT, while AT fell between. In CS, NPK-applied treatments were similar regardless of tillage. Combined costs for herbicide, machinery, labor, and diesel were higher in MP ...

Learn about current grain prices per bushel for corn, wheat, soybeans, and oats, and how they are impacted by weather conditions, export demand, and government policies affecting production and trade.

The dataset consists of 4 EXCEL files of 590 data entries. The soybean meal and corn prices in the wholesale markets include the average prices of soybean meal and corn markets nationwide from 2019 to 2022, measured on a weekly, monthly, and quarterly basis. Each entry is expressed in yuan per kilogram, with a total of 239 items for each time scale. The dataset involves processed monthly and quarterly data, with the weekly data retained in their raw form, sourced directly from the Animal Husbandry and Veterinary Bureau of the Ministry of Agriculture. The soybean meal and corn prices in the retail markets include the average prices of soybean meal and corn markets nationwide and 29 provinces from 2019 to 2022, measured on a monthly and quarterly basis. Each entry is expressed in yuan per kilogram, with a total of 56 items for each time scale. The dataset involves processed quarterly data, with the monthly data retained in their raw form, sourced directly from the CHINA Animal Veterinary Information Net of the National Animal Husbandry General Station.

The Corn, Wheat and Soybean Wholesaling industry has maneuvered through a challenging environment shaped by the COVID-19 pandemic and geopolitical tensions. The industry faced disruptions early on as supply chains and distribution networks were impacted. Yet, demand for essential grains like corn, wheat and soybeans stayed stable, cushioning revenue levels despite the upheaval. Demand surged as the sector began recovering from the pandemic, exerting pressure on supplies and driving price inflation for key grains like corn. The conflict in Ukraine added another layer of complexity, sharply constraining wheat supplies and complicating operational dynamics. Even so, governmental interventions, particularly through subsidies for biofuels using corn and soybean oils, provided a revenue boost, partially mitigating wider economic challenges. Overall, industry revenue is projected to climb at an annualized rate of 1.0% to $217.8 billion over the five years to 2024, although a 12.9% dip is expected in 2024. Evolving consumer preferences, most notably the shift towards low-carbohydrate diets, have led to a decreased demand for wheat, altering its market position and reducing profit for wholesalers. However, wholesalers have seen a boon from the rising demand for plant-based foods, which has spurred an increased need for soybeans. Navigating these shifts while concurrently managing rising costs and changing consumer behaviors has become crucial for wholesalers aiming to succeed in the competitive market. Despite the anticipated challenges that the industry faced, its adaptability and resilience were evident. These qualities will endure, allowing it to navigate through market complexities effectively. Moving forward, the Corn, Wheat and Soybean Wholesaling industry is projected to see a modest annualized revenue increase of 0.2% over the next five years, reaching $212.5 billion by 2029.

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).

Commodity Prices: Corn, soybeans, WTI crude oil and Henry Hub natural gas, Chicago Mercantile Exchange Group .

Today's grain market report shows a mix of trends in the prices of corn, soybeans, wheat, rice, and oats. Corn and soybean prices increased due to strong export demand and concerns about dry weather conditions, while wheat prices declined slightly. However, analysts warn that the upward trend may not be sustainable in the long run. Overall, the grain market seems to be driven by events in the global agricultural sector, such as reports of crop yields and demand.

This data set contains Ontario soybean grain prices collected by University of Guelph, Ridgetown Campus. The dataset includes daily prices of agricultural commodities at individual elevators in Ontario. Daily highs and lows are given for each commodity, as well as, daily Bank of Canada exchange rates.This dataset includes data from January 1, 2024 to December 31, 2024.

Soybean prices showed mixed movement influenced by weather trends and export updates, with Brazil and China reporting key trade data. Market awaits export sales figures.

Graph and download economic data for Global price of Soybeans (PSOYBUSDQ) from Q1 1990 to Q2 2025 about beans, World, and price.

The Price Discovery is a web based tool that allows users to view pricing information for the following crops covered by the Common Crop Insurance and the Area Risk Protection policies: barley, canola (including rapeseed), corn, cotton, grain sorghum, rice, soybeans, sunflowers, and wheat, and coverage prices, rates and actual ending values for the Livestock Risk Protection program, and expected and actual gross margin information for the Livestock Gross Margin program.

The data shows grain prices at select inland origin points and export destination ports and the price spread between them. More specifically, this dataset compares interior prices of corn in Illinois and Nebraska with the Gulf; Iowa and Gulf soybean prices; Kansas and Gulf hard red winter wheat; and North Dakota and Portland hard red spring wheat.

Learn about live grain markets, a platform for buyers and sellers to exchange information and transact on commodities like wheat, corn, and soybeans. Discover how prices are affected by supply and demand, and the different types of contracts available to manage risk. Understand the importance of live grain markets in the global economy for farmers, grain traders, and other market participants.