Cotton rose to 66.76 USd/Lbs on July 23, 2025, up 0.32% from the previous day. Over the past month, Cotton's price has risen 3.76%, and is up 0.84% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cotton - values, historical data, forecasts and news - updated on July of 2025.

Dropping Ogallala aquifer levels and changing commodity prices and energy costs make irrigation management an important but uncertain issue to west Texas cotton producers. For example, is deficit or full irrigation more profitable under the current lint price and pumping cost conditions? Also, what is the best way to divide production into dryland and irrigated acreage with limited well capacity? To help producers answer these questions this web application estimates the effects of irrigation on the profitability of center pivot cotton production on the Southern High Plains. It's main purpose is to show the impact of irrigation on yield and the related effects on both profits per acre and profits over a center pivot area with combined dryland and irrigated production. Resources in this dataset:Resource Title: Cotton Irrigation Tool. File Name: Web Page, url: https://www.ars.usda.gov/research/software/download/?softwareid=486&modecode=30-96-05-00 download page

In agriculture

This dataset consists of growth and yield data for each season when upland cotton [Gossympium hirsutum (L.)] was grown for lint and seed at the USDA-ARS Conservation and Production Research Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). In the 2000 through 2004, 2008, 2010, 2012, and 2020 seasons, cotton was grown on from one to four large, precision weighing lysimeters, each in the center of a 4.44 ha square field also planted to cotton. The square fields were themselves arranged in a larger square with four fields in four adjacent quadrants of the larger square. Fields and lysimeters within each field were thus designated northeast (NE), southeast (SE), northwest (NW), and southwest (SW). Cotton was grown on different combinations of fields in different years. When irrigated, irrigation was by linear move sprinkler system years before 2014, and by both sprinkler and subsurface drip irrigation in 2020. Irrigation protocols described as full were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Irrigation protocols described as deficit typically involved irrigation at rates established as percentages of full irrigation ranging from 33% to 75% depending on the year. The growth and yield data typically include plant population density, height, plant row width, leaf area index, growth stage, total above-ground biomass, leaf and stem biomass, boll mass (when present), lint mass, seed mass, final yield, and lint quality. Data are from replicate samples in the field and non-destructive (except for final harvest) measurements on the weighing lysimeters. In most cases yield data are available from only manual sampling on replicate plots in each field and lysimeters. These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on cotton ET, crop coefficients, crop water productivity, and simulation modeling of crop water use, growth, and yield. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield and have been used for testing, and calibrating models of ET that use satellite and/or weather data. See the README for descriptions of each data file.

This dataset provides values for COTTON reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Graph and download economic data for Global price of Cotton (PCOTTINDUSDM) from Jan 1990 to Jun 2025 about cotton, World, and price.

Cotton prices in , May, 2025 For that commodity indicator, we provide data from January 1960 to May 2025. The average value during that period was 1.47 USD per kilogram with a minimum of 0.6 USD per kilogram in August 1969 and a maximum of 5.06 USD per kilogram in March 2011. | TheGlobalEconomy.com

Dataset

This dataset was created by Palash S

Released under CC0: Public Domain

Contents

This data product contains data on U.S. cotton and wool supply, demand, and prices, as well as U.S. cotton and textile trade data, maintained by the Economic Research Service to support related commodity market analysis and research.

Here are a few use cases for this project:

1. Agricultural Monitoring and Disease Management: Farmers and agricultural organizations can use the "disease cotton plant" computer vision model to monitor large-scale cotton fields for any signs of disease. Early detection and management can help in controlling the spread and minimizing the impact of diseases on the cotton crop.

2. Smart Crop Insurance: Insurance companies can provide policyholders with tailored protection by using the computer vision model to assess the health of cotton plants in a certain area. By identifying affected plants, they can offer insurance plans that accurately reflect the risk posed by diseases and other factors.

3. Agricultural Consultancy Services: Expert consultants can use the "disease cotton plant" computer vision model to advise farmers on the best methods to prevent, manage, and treat diseases affecting their cotton crops. The model can also be used for training and capacity building in disease management among extension officers and local community.

4. Research and Development: Researchers can use the model as a tool to study various aspects of cotton plant diseases, their patterns, and their impact on crop yield. This information can be valuable for creating new treatment strategies and understanding how diseases spread to improve future prevention measures.

5. Supply Chain Management: Companies dealing with cotton production can use the computer vision model to ensure the quality of sourced raw cotton material. By identifying diseased plants earlier in the supply chain, businesses can maintain a high-quality product and prevent the spread of diseases to other areas of production.

Annual cotton production in the United States grew from just a few thousand tons at the turn of the 19th century, to fluctuating between 1.6 million and 4.3 million tons throughout most of the 20th century. The amount of space used to produce cotton also grew from three to almost 18 million hectares of land between 1866 and the 1920s, before dropping to around four or five million hectares between the 1960s and 1980s. Despite this drop in land usage, advancements in agricultural technology meant that output remained relatively constant in the 20th century, meaning that output per hectare actually increased significantly.

The mechanical cotton gin's invention in 1793 revolutionized the U.S. cotton industry, which grew exponentially in the early 19th century. Cotton was the U.S.' primary export in these years, and its production was driven by slave labor in the southern states (particularly South Carolina). For the first time, output exceeded one million tons in 1859, and again in 1861, however, the disruption of the American Civil War caused cotton output to drop by over 93 percent in the next three years, to just 68 thousand tons by 1864. Production resumed upon its previous trajectory following the war's end, and many of the former-slaves forced to work on cotton plantations continued to work in the cotton industry, but as sharecroppers who worked the land in exchange for a share of the harvest, as well as housing and facilities (this was similar to tenant farming, although sharecroppers received a smaller share of the crop and had fewer legal protections).

Cotton Crop and Weather Relationship Dataset

This comprehensive dataset explores the intricate relationship between weather conditions and cotton crop growth over a decade (2013-2023). With over 80,000 records, it provides valuable insights into how various climatic factors influence cotton production throughout its growth cycle.

Dataset Overview:

The dataset includes the following key fields:

1. Farm identification and temporal data:

   • Farm_ID
   • Planting_Date, Harvest_Date
   • Growth_Cycle, Harvest_Year

2. Cotton yield information:

   • Yield (measured in standard units)

3. Weather conditions:

   • Sunlight_Hours
   • Precipitation
   • Average_Temperature
   • Drought_Days, Flood_Days
   • CO2_Concentration

4. Soil characteristics:

   • Soil_Moisture
   • Soil_pH

5. Calculated environmental levels:

   • Sunlight_Level
   • Flood_Level
   • Drought_Level

This rich dataset allows for in-depth analysis of how various environmental factors affect cotton growth and yield. It captures both daily weather variations and extreme events, making it valuable for studying climate change impacts on cotton farming.

Potential applications include predictive modeling of cotton yields, optimization of planting and harvesting schedules, analysis of soil condition impacts, and development of climate-resilient cotton farming strategies.

Whether you're an agronomist, data scientist, or climate researcher, this dataset provides a comprehensive resource for exploring the complex interplay between weather patterns and cotton crop performance.

Peru Export Price: Agriculture: Cotton data was reported at 2,425.886 USD/Metric Ton in Sep 2018. This records a decrease from the previous number of 2,557.399 USD/Metric Ton for Aug 2018. Peru Export Price: Agriculture: Cotton data is updated monthly, averaging 2,178.388 USD/Metric Ton from Jan 1985 (Median) to Sep 2018, with 405 observations. The data reached an all-time high of 31,275.660 USD/Metric Ton in Jan 2015 and a record low of 0.000 USD/Metric Ton in Jan 2018. Peru Export Price: Agriculture: Cotton data remains active status in CEIC and is reported by Central Reserve Bank of Peru. The data is categorized under Global Database’s Peru – Table PE.P004: Export Price.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Cotton Plant. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Cotton Plant. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Cotton Plant, the median household income stands at $36,016 for householders within the 45 to 64 years age group, followed by $12,336 for the 65 years and over age group. Notably, householders within the 25 to 44 years age group, had the lowest median household income at $9,063.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Cotton Plant median household income by age. You can refer the same here

Agricultural Prices: Average Weekly Prices: Producer: Cotton Seed: 15 Kg: Mato Grosso do Sul data was reported at 84.000 BRL in 19 Feb 2016. This records an increase from the previous number of 78.000 BRL for 12 Feb 2016. Agricultural Prices: Average Weekly Prices: Producer: Cotton Seed: 15 Kg: Mato Grosso do Sul data is updated daily, averaging 18.500 BRL from Jan 2014 (Median) to 19 Feb 2016, with 83 observations. The data reached an all-time high of 84.000 BRL in 19 Feb 2016 and a record low of 15.000 BRL in 01 May 2015. Agricultural Prices: Average Weekly Prices: Producer: Cotton Seed: 15 Kg: Mato Grosso do Sul data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Prices – Table BR.PA140: Agricultural Prices: CONAB: Average Weekly Prices: Producer: Cotton Seed.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Raw Cotton (WPU015) from Jan 1926 to Jun 2025 about cotton, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

Agricultural Prices: Average Weekly Prices: Producer: Feather Cotton: 15 Kg: Maranhão data was reported at 72.000 BRL in 01 Apr 2016. This records a decrease from the previous number of 72.800 BRL for 25 Mar 2016. Agricultural Prices: Average Weekly Prices: Producer: Feather Cotton: 15 Kg: Maranhão data is updated daily, averaging 56.400 BRL from Sep 2014 (Median) to 01 Apr 2016, with 77 observations. The data reached an all-time high of 76.000 BRL in 11 Mar 2016 and a record low of 52.000 BRL in 10 Oct 2014. Agricultural Prices: Average Weekly Prices: Producer: Feather Cotton: 15 Kg: Maranhão data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Prices – Table BR.PA140: Agricultural Prices: CONAB: Average Weekly Prices: Producer: Cotton Seed.

Cotton root rot is a century-old cotton disease that now can be effectively controlled with Topguard Terra fungicide. Because this disease tends to occur in the same general areas within fields in recurring years, site-specific application of the fungicide only to infested areas can be as effective as and considerably more economical than uniform application. The overall objective of this research was to demonstrate how site-specific fungicide application could be implemented based on historical remote sensing imagery and using variable-rate technology. Procedures were developed for creating binary prescription maps from historical airborne and high-resolution satellite imagery. Two different variable-rate liquid control systems were adapted to two existing cotton planters, respectively, for site-specific fungicide application at planting. One system was used for site-specific application on multiple fields in 2015 and 2016 near Edroy, Texas, and the other system was used on multiple fields in both years near San Angelo, Texas. Airborne multispectral imagery taken during the two growing seasons was used to monitor the performance of the site-specific treatments. Results based on prescription maps derived from historical airborne and satellite imagery of two fields in 2015 and one field in 2016 are reported in this article. Two years of field experiments showed that the prescription maps and the variable-rate systems performed well and that site-specific fungicide treatments effectively controlled cotton root rot. Reduction in fungicide use was 41%, 43%, and 63% for the three fields, respectively. The methodologies and results of this research will provide cotton growers, crop consultants, and agricultural dealers with practical guidelines for implementing site-specific fungicide application using historical imagery and variable-rate technology for effective management of cotton root rot. Resources in this dataset: Resource Title: A ground picture of cotton root rot File Name: IMG_0124.JPG Resource Description: A cotton root rot-infested area in a cotton field near Edroy, TX. Resource Title: An aerial image of a cotton field File Name: Color-infrared image of a field.jpg Resource Description: Aerial color-infrared (CIR) image of a cotton field infested with cotton root rot. Resource Title: As-applied fungicide application data File Name: Jim Ermis-Farm 1-Field 11 Fungicide Application.csv Resource Description: As-applied fungicide application rates for variable rate application of Topguard to a cotton field infested with cotton rot

UAV Cotton Flower Counting Dataset

https://doi.org/10.5061/dryad.5qfttdzhb

Description of the data and file structure

These data were collected with a UAV at a cotton breeding field in Watkinsville, Georgia in 2021. The field was scanned twice weekly, and the data was analyzed using an automated pipeline:

• The raw images were stitched together into an orthophoto
• Individual plot-level crops were extracted
• An object detector was used to detect flowers in the plot images
• The flower counts were analyzed in order to produce various phenotyping metrics

This dataset contains the raw, annotated images used to train the object detector. In addition to the data we collected in 2021, this dataset also includes some additional data, including UAV images from previous years (2016, 2018) as well as some plot-level images collected from a tractor. All images contain bounding box annotations for each flower.

We have also included a model trai...

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Cotton Market Size 2025-2029

The cotton market size is forecast to increase by USD 8.69 billion, at a CAGR of 3.2% between 2024 and 2029.

The market is a significant contributor to economic growth and a crucial source of livelihood for numerous communities worldwide. Key drivers propelling the market include the adoption of new technologies by companies to enhance productivity and efficiency. However, challenges persist, including the overconsumption of water due to poor management and water pollution. These issues not only pose environmental risks but also threaten the sustainability of cotton production. companies are increasingly investing in advanced technologies such as genetically modified cotton seeds, Precision Farming, and automation to improve yields and reduce costs. These innovations enable farmers to optimize resource utilization and minimize waste.
However, the market faces a substantial challenge in addressing the environmental impact of cotton production, particularly water usage and pollution. Inefficient drip irrigation systems and the use of excessive water for cotton cultivation have led to water scarcity in several regions, threatening both agricultural productivity and food security. Additionally, the discharge of untreated cotton processing wastewater into water bodies contributes to water pollution, posing health risks to local populations and negatively impacting the environment. To capitalize on market opportunities and navigate these challenges effectively, companies must focus on implementing sustainable farming practices and investing in water management technologies.

What will be the Size of the Cotton 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, with dynamic interplay between various sectors shaping its landscape. Cotton trade is a vital component, influenced by global supply and demand trends. Weaving transforms raw cotton into fabric, with organic cotton gaining prominence due to increasing consumer demand for sustainable textiles. The cotton supply chain encompasses spinning, flannel, plaid, voile, and various other types, each with unique applications. Research and innovation are at the forefront of the industry, driving advancements in cotton twill, blends, recycling, and regulations. Policies and certifications shape the cotton production process, focusing on sustainability and agricultural practices. Apparel, home textiles, and industrial textiles, including denim, quilting, broadcloth, and medical textiles, showcase the versatility of cotton.

Cotton's continuous evolution is further highlighted in the emergence of technologies, such as cotton derivatives, printing, and dyeing. Market volatility influences pricing, while waste reduction and innovation in finishing processes contribute to the industry's ongoing growth. The market's intricate web of interconnected components ensures a dynamic and ever-evolving industry landscape

How is this Cotton Industry segmented?

The cotton 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.

Application

  Cotton fiber
  Cotton seed oil
  Cotton seed


Distribution Channel

  Offline
  Online


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  Middle East and Africa

    Turkey


  APAC

    Bangladesh
    China
    India
    Pakistan


  Rest of World (ROW). 

By Application Insights

The cotton fiber segment is estimated to witness significant growth during the forecast period.

Cotton, a natural fiber grown in tropical and subtropical regions, is a significant player in the global textile industry. India, as the world's leading cotton producer, contributes substantially to the market. The textile and apparel sectors' expansion fueled the cotton industry's growth. Consumer preferences and trends shape the demand for cotton fibers, which accounts for approximately one-third of all fibers produced globally. Despite being an export crop, most processing occurs in major producing countries, such as China and India. Cotton's versatility is evident in its various applications, including industrial textiles, denim, home textiles, quilting, broadcloth, medical textiles, and more. Organic cotton, recycled cotton, and cotton blends are gaining popularity due to sustainability concerns.

The cotton supply chain involves various processes, from harvesting and certifications to spinning, weaving, dyeing, and finishing. Cotton agriculture faces challenges such as regulations, production volatility, and sustainability concerns. To address these issues, re