Wheat fell to 544.29 USd/Bu on June 9, 2025, down 1.89% from the previous day. Over the past month, Wheat's price has risen 5.64%, but it is still 10.40% lower than a year ago, 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 June of 2025.

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).

Learn about the various factors that influence grain commodity prices, including supply and demand, weather patterns, transportation costs, and government policies. Gain insight into how traders and analysts make predictions about price movements and why understanding these factors is crucial for farmers, traders, and consumers.

Data obtained from the National Bureau of Statistics in Abuja, Nigeria on monthly prices for select markets in Kebbi State, Nigeria for January 2000 to December 2016.

We present the largest homogenous dataset of grain prices for four major types of grain for pre-industrial Germany covering 70 cities with a total of 259 time series. This article describes the sources and the methodology followed to create calendar-year-based price series in grams of silver per litre. The dataset is organised and documented decentrally by means of one excel file for each city. To aggregate information for all cities in one file, future users can either use spreadsheet software or open-source software code that creates the national-level file. We use the dataset to show how price dispersion developed across more than 300 years. The dataset facilitates future research on market integration, storage, historical demography, and economic impacts of climate change.

A "spread" can have multiple meanings, but it generally implies a difference between two comparable measures. These can be differences across space, across time, or across anything with a similar attribute. For example, in the stock market, there is a spread between the highest price a buyer is willing to pay and the lowest price a seller is willing to accept.

In this dataset, spread refers to differences in prices between two locations, an origin (e.g., Illinois, Iowa, etc.) and a destination (e.g., Louisiana Gulf, Pacific Northwest, etc.). Mathematically, it is the destination price minus the origin price.

Price spreads are closely linked to transportation. They tend to reflect the costs of moving goods from one point to another, all else constant. Fluctuations in spreads can change the flow of goods (where it may be more profitable to ship to a different location), as well as indicate changes in transportation availability (e.g., disruptions). For more information on how price spreads are linked to transportation, see the story, "Grain Prices, Basis, and Transportation" (https://agtransport.usda.gov/stories/s/sjmk-tkh6).

This is one of three companion datasets. The other two are grain prices (https://agtransport.usda.gov/d/g92w-8cn7) and grain basis (https://agtransport.usda.gov/d/v85y-3hep). 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, and there needs to be both an origin and a destination to have a price spread).

The origin and destination prices come from the grain prices dataset.

Stay up-to-date with today's grain prices per bushel for corn, soybeans, wheat, oats, and rice, and learn about the various factors that influence these prices such as weather, supply and demand, government policies, and international trade. Discover how farmers, agribusinesses, and consumers are affected by these prices.

This data set contains Ontario wheat 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.

Data obtained from the National Bureau of Statistics in Abuja, Nigeria on monthly prices for select markets in Kebbi State, Nigeria for January 2000 to December 2016.

Corn fell to 442.02 USd/BU on June 9, 2025, down 0.11% from the previous day. Over the past month, Corn's price has fallen 1.34%, and is down 2.15% 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 June of 2025.

Learn about the importance of live grain market prices and how to access up-to-date information on the current prices of different grain commodities through commodity exchanges, news and analysis platforms, and free online price tracking tools.

Data obtained from the National Bureau of Statistics in Abuja, Nigeria on monthly prices for select markets in Kebbi State, Nigeria for January 2000 to December 2016.

This dataset 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, 2025 to May 31, 2025. Data for June 1, 2025 to December 31, 2025 will be added as it becomes available.

The period of the study was characterised by major improvements in financial institutions and transport. The objectives of the study were to see how pricing behaviour changed as a result of this. Since the prices are weekly and by county, it is possible to see how seasonality and regional patterns changed over time. Quantifying the effects of these changes should enable us to see their relative importance in promoting economic growth.

The general aim of our research has been to increase our understanding of market integration and its effect on economic performance - particularly in the context of financial markets and commodity markets. Our specific objectives were (i) to create a major dataset of eighteenth and nineteenth century grain prices which can be used within our research project and which could also potentially be useful for other researchers; (ii) to estimate an econometric model to quantify the changes in financial markets, especially the spread of country banks (iii) to estimate an econometric model to measure the effects of transport networks; (iv) to use our results from to estimate the social welfare gains from market integration and to relate the improvements in market integration to the major changes in agricultural practice.

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 September 30, 2024. Data for October 1, 2024 to December 31, 2024 will be added as it becomes available.

Graph and download economic data for Producer Price Index by Commodity: Processed Foods and Feeds: Wheat Mill Products, Corn Mill Products, and Other Grain Mill Products Except Flour (WPU02140908) from Jun 1998 to Apr 2025 about flour, grains, corn, wheat, mills, processed, food, commodities, PPI, inflation, price index, indexes, price, and USA.

The Wholesale Price Index of food grains across India during financial year 2024 was nearly 194. An overall increase in the price index was seen over the years from financial year 2013 in the country.

The monthly price of wheat (hard red winter) in the United States reached an all time high in May 2022, at over 520 U.S. dollars per metric ton. The unprecedented price increase began in mid-2020, due to the impact of the Covid-19 pandemic, and was later exacerbated by the Russo-Ukrainian War in March 2022. Before the war, Russia and Ukraine were among the world's five largest wheat exporters, and around one third of all international wheat imports came from these two countries.

The increase of 96 dollars per ton between February and March 2022 was the single largest price hike in U.S. history, and was only the second time that prices had exceeded 400 dollars - the first time this happened was due to the financial crisis of 2008. In the five years before the Covid-19 pandemic, the price of wheat generally fluctuated between 150 and 230 dollars per ton.

Globally, consumer food prices are expected to rise by 3.68 percent due to the increase in freight rates and grain prices. The comparative increase is showing the difference to a market where the prices and rates from February 2022, before the war in Ukraine, had remained stable. Lower middle income economies face the steepest increase in food prices since the shipping costs are highest for this group of countries.