Graph and download economic data for Producer Price Index by Commodity: Farm Products (WPU01) from Jan 1913 to Sep 2025 about agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

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.

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.

Daily market prices of agricultural commodities across India from 2001-2025. Contains 75+ million records covering 374 unique commodities and 1,504 varieties from various mandis (wholesale markets). Commodity Like: Vegetables, Fruits, Grains, Spices, etc.

Cleaned, deduplicated, and sorted by date and commodity for analysis.

Column Schema

Data sourced from the Government of India's Open Data Platform.

License: Government Open Data License - India (GODL-India) https://www.data.gov.in/Godl

Tradefeeds Commodity Prices API enables you to get commodity prices data of the major commodity asset types like energy commodities, metals, industrial commodities, agricultural commodities and livestock commodities. Each commodity asset type has a different historical coverage. A commodity within its commodity asset type has not the same historical coverage as another commodity from the group. For example, within the group of energy commodities, crude oil has a historical coverage of 34 years while coal of only 13 years. Tradefeeds offers commodity prices data either via JSON REST API, or via downloadable databases in CSV or Excel format.

If you are interested to learn more, check out the company website: https://tradefeeds.com/commodities-prices-api/

Australia Feedgrains Price: Feed Wheat data was reported at 356.000 AUD/Ton in Sep 2021. This records an increase from the previous number of 351.600 AUD/Ton for Aug 2021. Australia Feedgrains Price: Feed Wheat data is updated monthly, averaging 296.000 AUD/Ton from Jan 2007 (Median) to Sep 2021, with 177 observations. The data reached an all-time high of 493.000 AUD/Ton in Mar 2008 and a record low of 202.000 AUD/Ton in Dec 2011. Australia Feedgrains Price: Feed Wheat data remains active status in CEIC and is reported by Australian Bureau of Agricultural and Resource Economics and Sciences. The data is categorized under Global Database’s Australia – Table AU.P002: Agricultural Commodity Prices.

Farm product prices, crops and livestock, by province (in dollars per metric tonne unless otherwise noted). Data are available on a monthly basis.

As an essential part of daily life, the drastic fluctuations in agricultural commodity prices significantly impact producers’ motivation and consumers’ quality of life, further exacerbating market uncertainty and unsustainability. The ability to scientifically and effectively predict agricultural commodity prices is of great significance for the rational deployment of market mechanisms, the timely adjustment of supply chains, and the promotion of food policy adjustments. This paper proposes a sustainable hybrid model SV-PSO-BiLSTM which integrates Seasonal-Trend decomposition procedure based on Loess (STL), Variational Mode Decomposition (VMD), Particle Swarm Optimization (PSO), and Bidirectional Long Short-Term Memory (BiLSTM) neural networks. This innovative approach first performs seasonal decomposition of the original data using the STL method, then applies the VMD method for double decomposition of the residual components, reconstructs the data based on sample entropy, and finally predicts agricultural commodity market prices using the BiLSTM network model optimized by the PSO algorithm. This paper investigates the market price dynamics of four agricultural commodities (chili, garlic, ginger, and pork) and one agricultural financial derivative (soybean futures). The experimental results indicate that the proposed SV-PSO-BiLSTM hybrid model achieves average values of 0.2241 for root mean square error (RMSE), 0.1665 for mean absolute error (MAE), 0.0207 for mean absolute percentage error (MAPE), and 0.9851 for the coefficient of determination (R2). These results surpass those of other comparative models, demonstrating stronger generalization, reliability, and stability. The research findings can provide effective guidance for the reasonable regulation of agricultural commodity market prices and further promote the healthy and sustainable development of the agricultural commodity industry.

View monthly updates and historical trends for Agriculture Price Index. Source: World Bank. Track economic data with YCharts analytics.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Tomatoes (WPU01130217) from Jan 1947 to Sep 2025 about agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

Description: This dataset provides daily price records for three key agricultural commodities: coffee, wheat, and corn, spanning five decades from 1973 to 2023. The dataset is a valuable resource for researchers, analysts, and enthusiasts interested in understanding the historical price trends of these essential commodities in the global market.

Columns: - Date: The date of the price record in yyyy-mm-dd format. - Coffee (USD): Daily prices of coffee in US dollars. - Wheat (USD): Daily prices of wheat in US dollars. - Corn (USD): Daily prices of corn in US dollars.

Data Source: The dataset is compiled from reliable sources and represents a comprehensive record of daily commodity prices, making it an ideal tool for studying the dynamics of these agricultural markets over the past fifty years.

Use Cases: - Analyze long-term price trends and patterns for coffee, wheat, and corn. - Create predictive models for commodity price forecasting. - Investigate the impact of various economic and environmental factors on commodity prices. - Explore correlations between commodity prices and global events.

Acknowledgments: We would like to express our gratitude to the data sources that have contributed to the compilation of this dataset, making it freely available for research and analysis.

Note: Please cite this dataset appropriately if you use it in your research or analysis.

Start exploring the world of agricultural commodity prices by downloading this dataset today!

United States Agricultural Price Index: Received by Farmers: Food Commodities data was reported at 88.800 2011=100 in Oct 2018. This records a decrease from the previous number of 90.600 2011=100 for Sep 2018. United States Agricultural Price Index: Received by Farmers: Food Commodities data is updated monthly, averaging 101.000 2011=100 from Jan 2010 (Median) to Oct 2018, with 106 observations. The data reached an all-time high of 126.000 2011=100 in Apr 2014 and a record low of 81.000 2011=100 in Feb 2010. United States Agricultural Price Index: Received by Farmers: Food Commodities data remains active status in CEIC and is reported by National Agricultural Statistics Service. The data is categorized under Global Database’s United States – Table US.I043: Agricultural Price Index.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Hay and Hayseeds (WPU0181) from Jan 1947 to Sep 2025 about agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Eggs for Fresh Use (WPU017107) from Dec 1991 to Sep 2025 about eggs, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

Agmarknet India Commodity Prices (October 2024 – August 2025)

🧩 Overview

This dataset contains daily agricultural commodity price data scraped from the Agmarknet (Government of India) portal for the period October 2024 to August 2025.
It provides granular market-level data across multiple states, including information on commodity, variety, grade, and minimum, maximum, and modal prices (in Rs./Quintal).

With over 1.1 million records, this dataset offers valuable insights into agricultural price fluctuations and regional market dynamics in India.

📅 Time Period

October 2024 – August 2025

📊 Dataset Columns Description

🌾 Data Source

Data has been scraped from the official Agmarknet portal maintained by the Directorate of Marketing & Inspection (DMI) under the Ministry of Agriculture and Farmers Welfare, Government of India.
👉 https://agmarknet.gov.in/

📈 Possible Use Cases

• Agricultural price forecasting using machine learning
• Commodity-wise seasonal and regional trend analysis
• Correlation between price volatility and climatic or policy factors
• Decision support for farmers and agri-businesses
• Market intelligence and demand-supply analysis

🧮 Dataset Statistics

• Records: 1,118,899
• Features: 11
• Coverage: 8 Indian states and 1160 markets
• Frequency: Daily

⚖️ License

This dataset is released under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.
You are free to use, share, and adapt this dataset for any purpose, provided that you give appropriate credit and share derivatives under the same license.

📢 Citation

If you use this dataset in your research, please cite it as:

Anish (2025). Agmarknet India Commodity Prices (October 2024 – August 2025).
Retrieved from https://agmarknet.gov.in/

🧠 Acknowledgments

Special thanks to the Ministry of Agriculture & Farmers Welfare, Government of India, for maintaining open access to Agmarknet data, which enables valuable research and innovation in agricultural analytics.

View monthly updates and historical trends for US Producer Price Index: Farm Products: Tomatoes. from United States. Source: Bureau of Labor Statistics. T…

The question whether there is a correlation between fluctuations of crop yields and economic cycles has been answered very differently from the very start. Answers range from the thesis of a passive dependency of the industrial cycle on the state of the agriculture to the thesis of a passive dependency of the agricultural cycle on industrial cycles. As the author explains in a short overview, Pigou and Robertson assume that the increase in purchasing power, which, they say, the agriculture experienced in the case of a rich harvest, triggers a commercial upswing. According to Timoshenko, however, the low prices of agricultural products in the years of rich harvests have caused a stimulation of the whole economy. Following Arthur Spiethoff, the author suggests an analysis of the influence of fluctuating crops on the economic cycles in certain periods. For this purpose, he examines closely the harvest yields of the most important crops (and for some colonial countries the external sales volumes respectively), the prices of agricultural products, and of industrial raw materials for six European and six non-European countries. Datatables in the search and downloadsystem HISTAT (Historical Statistics, www.histat.gesis.org): 1. Crop yields, prices of agricultural products, indeces of agricultural production, prices, purchasing power and monetary value of agricultural products in Germany (1878-1914) 2. Crop yields, prices of agricultural products, indeces in England (1844-1914) 3. Crop yields, prices of agricultural products, indeces of agricultural production, prices, purchasing power and monetary value in France (1871-1914) 4. Crop yields, prices of agricultural products, indeces of agricultural production, prices, purchasing power and monetary value in Austria and Hungary (1881-1914) 5. Crop yields and index of agricultural production in Romania (1886-1914) 6. Crop yields, average price of corn, index of agricultural production, index of prices of agricultural products, index of price, purchasing power and monetary value of agricultural products in Russia (1871-1914) 7. Crop yields, average corn prices, index of agricultural production, index of prices of agricultural products, index of price, purchasing power and monetary value of agricultural production in the United States (1866-1914) 8. Total exports and prices of agricultural products, index of agricultural production, index of prices of agricultural products, index of price, purchasing power and monetary value of agricultural products in Canada (1868-1914) 9. Total exports, prices in gold pesos, agricultural indeces in Argentina (1874-1913) 10. Total exports and export prices for coffee in Brazil (1871-1912) 11. Total exports and export prices for coffee, cotton, rice, corn, jute, seeds, tea in India, indeces of production, prices, purchasing power, monetary value (1873-1914) 12. Crop yields, prices of agricultural products, agricultural indeces in Australia (1860-1914) 13. Index of world crops and world prices (1873-1910). Timeseries are downloadable via the online system HISTAT (www.histat.gesis.org).