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.

Wheat fell to 516.75 USd/Bu on August 1, 2025, down 1.24% from the previous day. Over the past month, Wheat's price has fallen 8.38%, and is down 4.13% 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 August of 2025.

United States SCE: Commodity Price Change Expectation: 1 Year Ahead: Food data was reported at 5.081 % in Apr 2025. This records a decrease from the previous number of 5.233 % for Mar 2025. United States SCE: Commodity Price Change Expectation: 1 Year Ahead: Food data is updated monthly, averaging 5.027 % from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 9.843 % in Mar 2022 and a record low of 3.766 % in Nov 2024. United States SCE: Commodity Price Change Expectation: 1 Year Ahead: Food data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.H080: Survey of Consumer Expectations: Commodity Price.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Tillaberi, Tahoua, Agadez, Zinder, Dosso, Niamey, Maradi, Diffa, Market Average

This dataset contains historical data on chili prices and weather conditions in Kota Singkawang. It includes monthly records of various chili prices, shallot and garlic prices, rainfall levels, number of rainy days, and inflation rates. This dataset is a cleaned and merged version of several publicly available datasets from Statistics Indonesia (BPS). See the attached README file for detailed sources and descriptions.

This Data is associated to the paper "PREDICTION OF FOOD COMMODITY PRICES IN KOTA SINGKAWANG USING MACHINE LEARNING: A COMPARATIVE STUDY OF RANDOM FOREST, LINEAR REGRESSION, AND XGBOOST" by Lestari, D. , Bangun, E., Gaol, F. and Matsuo, T.

CRB Index fell to 369.61 Index Points on July 31, 2025, down 1.78% from the previous day. Over the past month, CRB Index's price has risen 1.62%, and is up 14.57% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on August of 2025.

United States CPI U: Commodities Less Food & Energy Commodities data was reported at 144.237 1982-1984=100 in Jun 2018. This records a decrease from the previous number of 144.745 1982-1984=100 for May 2018. United States CPI U: Commodities Less Food & Energy Commodities data is updated monthly, averaging 113.050 1982-1984=100 from Jan 1957 (Median) to Jun 2018, with 738 observations. The data reached an all-time high of 148.070 1982-1984=100 in Apr 2012 and a record low of 37.000 1982-1984=100 in Feb 1957. United States CPI U: Commodities Less Food & Energy Commodities data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I002: Consumer Price Index: Urban.

What is it?The “Regional self-reliance model of the New England food system” explores future scenarios of regional food self-reliance. In this model, self-reliance is defined as the ratio of production to consumption and can be expressed for individual commodities, food groups, or the overall diet. The model allows a user to define assumptions about diet composition and target self-reliance for different groups of foods. The model estimates the regional self-reliance across seven food groups (grains, vegetables, fruits, dairy, protein-rich foods, fats and oils, and sweeteners) and for the overall diet. In addition, the model calculates land requirements for producing the target amounts of food from New England agriculture. These estimates are presented beside data on current land use to place the results in context.Why was it generated?The model was generated as part of the New England Feeding New England (NEFNE) project. The central question of NEFNE was, "What would it take for 30% of the food consumed in New England to be regionally produced by 2030?" The model addresses the agricultural production capacity of the region, while accounting for the contribution of capture fisheries and aquaculture to food production. The purpose of the model is to estimate the production capacity of the region’s land resources to evaluate the land requirements of increasing regional self-reliance in food.How was it generated?A team of researchers collaborated to construct the model. The model builds on prior work on regional self-reliance, the human carrying capacity of agricultural resources, and analysis of livestock feed requirements. As described below, the model estimates the land requirements of supplying a given level of self-reliance, accounting for food needs, food losses and waste, livestock feed requirements, crop yields, and land availability.Starting from the food consumption end of the food system, the model takes input data on food intake (in servings person-1 day-1) by food group (e.g., grains) and distributes consumption across primary food commodities from that food group (e.g., corn meal, wheat flour) in the Loss-Adjusted Food Supply. Intake for each primary food commodity is then converted into the equivalent quantity of agricultural commodity (in pounds year-1) needed to supply the region with a sufficient amount of that commodity to meet the target level of self-reliance, at a given projected population size. This conversion accounts for the serving size of the commodity (in grams), losses at different stages of the food system, and processing conversions. For animal products, a further step is taken to convert the quantity of food consumed into equivalent quantities of crop biomass required to feed the requisite livestock. Land requirements for each food are determined by dividing the agricultural commodity (for plant foods) or crop biomass requirements (for animal products) by regional average yields for the appropriate crop(s).Input data were collected from an array of secondary data sources, including, the Loss-Adjusted Food Supply, the Census of Agriculture, the New England Agricultural Bulletin, Major Land Uses, the Atlantic Coastal Cooperative Statistics Program Data Warehouse, and the NOAA Fisheries Landings data portal. Additional sources used to develop the model are cited in the workbook and reference information is provided in each worksheet. The unique contribution of the model is to organize the data in a form that permits exploration of alternative scenarios of diet, target self-reliance, and land availability for the New England region.

The global Commodity Fumigation Services market is projected to reach USD 351 million by 2033, exhibiting a CAGR of 7.9% during the forecast period (2025-2033). The growing demand for the protection of commodities from pests and diseases, stringent regulations related to commodity fumigation, and the increasing adoption of fumigation services in various sectors such as agriculture, food processing, and pharmaceuticals are key factors driving market growth. Key trends in the market include the growing adoption of sustainable and environmentally friendly fumigation techniques, the integration of data analytics and IoT devices for real-time monitoring and control of fumigation processes, and the increasing demand for fumigation services in emerging economies. North America and Europe are expected to remain dominant markets, while the Asia Pacific region is anticipated to witness significant growth over the forecast period due to the expanding agricultural and food processing industries in the region.

Food Price Index in World increased to 128 Index Points in June from 127.30 Index Points in May of 2025. This dataset includes a chart with historical data for World Food Price Index.

Treehouse Foods stock is expected to experience moderate growth in the coming months, driven by the company's strategic initiatives to streamline operations, optimize its portfolio, and expand into higher-growth segments. However, investors should be aware of the inherent risks associated with the food industry, such as commodity price volatility, competition, and potential disruptions in the supply chain. Furthermore, Treehouse Foods' significant debt burden could weigh on profitability and limit its ability to make strategic acquisitions or investments.

United States CPI UW: Commodities Less Food & Energy Commodities data was reported at 19.635 % in Jun 2018. This records a decrease from the previous number of 19.736 % for May 2018. United States CPI UW: Commodities Less Food & Energy Commodities data is updated monthly, averaging 21.640 % from Jan 1993 (Median) to Jun 2018, with 306 observations. The data reached an all-time high of 24.161 % in Apr 1998 and a record low of 18.574 % in Dec 2017. United States CPI UW: Commodities Less Food & Energy Commodities data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I010: Consumer Price Index: Urban: Weights.

Cost of food in India decreased 1.06 percent in June of 2025 over the same month in the previous year. This dataset provides - India Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

United States PPI: Commodity: ID: PG: Materials: Mfg: Food data was reported at 197.500 1982=100 in Jun 2018. This records a decrease from the previous number of 197.900 1982=100 for May 2018. United States PPI: Commodity: ID: PG: Materials: Mfg: Food data is updated monthly, averaging 99.750 1982=100 from Jan 1947 (Median) to Jun 2018, with 858 observations. The data reached an all-time high of 216.300 1982=100 in Oct 2014 and a record low of 31.900 1982=100 in Jan 1950. United States PPI: Commodity: ID: PG: Materials: Mfg: Food data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I023: Producer Price Index: FD-ID System: Intermediate Demand: Commodity Type.

Snapshot img

Agribusiness Market Size 2025-2029

The agribusiness market size is forecast to increase by USD 843.4 million, at a CAGR of 4.6% between 2024 and 2029.

The market is experiencing significant shifts driven by population growth, which is leading to an increased demand for food production. This trend is placing immense pressure on the industry to find innovative solutions to meet the rising demand, particularly in the context of a shrinking amount of arable land. One response to this challenge is the adoption of automation in agriculture, with technologies such as precision farming, drones, and robotics gaining traction. These solutions aim to optimize resource usage and increase efficiency, enabling farmers to produce more with less land. However, the implementation of automation also presents challenges, including high upfront costs and the need for significant investment in technology and infrastructure.
Additionally, regulatory compliance and data security concerns add complexity to the adoption process. To capitalize on the market opportunities presented by population growth and the need for more efficient agriculture, companies must navigate these challenges and invest in technologies that can help them stay competitive while addressing the sustainability and productivity demands of the industry.

What will be the Size of the Agribusiness Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, shaped by various dynamics that impact different sectors. Land use patterns are shifting, with an increasing focus on carbon sequestration and sustainable farming practices. Precision agriculture is revolutionizing yield optimization, while food processing and packaging technologies advance to ensure food safety and traceability. Seed production and agricultural biotechnology are driving innovation in crop production, and harvesting equipment is becoming more efficient and eco-friendly. Food security remains a critical concern, leading to the adoption of irrigation systems, biodiversity conservation, and sustainable farming practices. Livestock feed and breeding are undergoing transformations, with a focus on disease prevention and environmental sustainability.

Pest control methods are evolving, with a shift towards more natural and less harmful alternatives. Supply chain management is becoming more complex, with the integration of farm management software and crop rotation techniques. Water conservation is a priority, with new technologies and practices emerging to address this challenge. Agribusiness investment is on the rise, driven by market volatility and price fluctuations due to climate change adaptation and commodity trading. Direct marketing and consumer dietary trends are influencing food distribution, with a growing demand for locally sourced and organic produce. Vertical farming and agricultural finance are gaining traction, offering solutions to land tenure issues and providing access to capital for small-scale farmers.

The ongoing unfolding of these market activities and evolving patterns underscores the continuous nature of the agribusiness landscape.

How is this Agribusiness Industry segmented?

The agribusiness industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Grains and cereals
  Dairy
  Oilseeds
  Livestock
  Others


Application

  Agrichemicals
  Seed business
  Breeding
  Machinery and equipment


Technology

  Traditional agriculture
  Mechanized farming
  Precision agriculture and smart farming
  Organic and sustainable Farming


Distribution Channel

  Retail chains and supermarkets
  Wholesale distribution
  Direct-to-consumer
  Food processing and manufacturing companies


Farm Size

  Small-Scale Farms
  Medium-Scale Farms
  Large-Scale Farms


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan
    South Korea


  South America

    Argentina
    Brazil


  Rest of World (ROW)

.

By Product Insights

The grains and cereals segment is estimated to witness significant growth during the forecast period.

The market encompasses various sectors, including grains and cereals, dairy production, land use, carbon sequestration, agricultural machinery, organic farming, yield optimization, food security, irrigation systems, biodiversity conservation, supply chain management, livestock feed, livestock breeding, pest control, poultry farming, government subsidies, farm management software, crop rotation, water conservati

United States CPI U: AW: Commodities Less Food & Beverages data was reported at 21.371 % in 2017. This records a decrease from the previous number of 21.596 % for 2016. United States CPI U: AW: Commodities Less Food & Beverages data is updated yearly, averaging 25.364 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 27.582 % in 1990 and a record low of 21.371 % in 2017. United States CPI U: AW: Commodities Less Food & Beverages data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I011: Consumer Price Index: Urban: Weights (Annual).

United States PPI: Commodity: ID: Processed Foods & Feeds data was reported at 195.000 1982=100 in Jun 2018. This records a decrease from the previous number of 196.100 1982=100 for May 2018. United States PPI: Commodity: ID: Processed Foods & Feeds data is updated monthly, averaging 111.850 1982=100 from Jan 1967 (Median) to Jun 2018, with 618 observations. The data reached an all-time high of 215.300 1982=100 in Sep 2014 and a record low of 41.000 1982=100 in Nov 1967. United States PPI: Commodity: ID: Processed Foods & Feeds data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I023: Producer Price Index: FD-ID System: Intermediate Demand: Commodity Type.

United States PPI: ME: Special: Food Products: Commercial Food data was reported at 250.800 1982=100 in Jun 2018. This records an increase from the previous number of 248.100 1982=100 for May 2018. United States PPI: ME: Special: Food Products: Commercial Food data is updated monthly, averaging 129.450 1982=100 from Jan 1961 (Median) to Jun 2018, with 690 observations. The data reached an all-time high of 254.500 1982=100 in Apr 2018 and a record low of 30.700 1982=100 in Nov 1961. United States PPI: ME: Special: Food Products: Commercial Food data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I017: Producer Price Index: By Commodities.

United States CPI U: Commodities Less Food & Beverages data was reported at 152.228 1982-1984=100 in Jun 2018. This records a decrease from the previous number of 152.599 1982-1984=100 for May 2018. United States CPI U: Commodities Less Food & Beverages data is updated monthly, averaging 105.850 1982-1984=100 from Jan 1957 (Median) to Jun 2018, with 738 observations. The data reached an all-time high of 166.479 1982-1984=100 in Apr 2012 and a record low of 37.000 1982-1984=100 in Feb 1957. United States CPI U: Commodities Less Food & Beverages data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I002: Consumer Price Index: Urban.

Canada Commodity Price Index: Food data was reported at 148.310 1982-1990=100 in Apr 2010. This records an increase from the previous number of 143.310 1982-1990=100 for Mar 2010. Canada Commodity Price Index: Food data is updated monthly, averaging 133.930 1982-1990=100 from Jan 2006 (Median) to Apr 2010, with 52 observations. The data reached an all-time high of 217.320 1982-1990=100 in Feb 2008 and a record low of 114.510 1982-1990=100 in Mar 2006. Canada Commodity Price Index: Food data remains active status in CEIC and is reported by Bank of Canada. The data is categorized under Global Database’s Canada – Table CA.I026: Commodity Price Index: 1982-1990=100.