- Why it matters: Data-driven innovation is crucial for U.S. cotton growers to maintain profitability and long-term viability in the face of challenges like unpredictable weather and rising costs.
- Innovation in action: From precision irrigation to advanced breeding, data is transforming cotton production, leading to increased efficiency, improved resource management, and new market opportunities.
- The bottom line: Data-backed improvements unlock access to preferred supplier programs, premium prices, and help mitigate risks, ultimately boosting profitability and fostering a more thriving future for U.S. cotton.
Cotton represents approximately 25% of total world fiber use, making it one of the most important textile fibers in the world. The United States leads the world in cotton exports and ranks third in production, accounting for one-third of global trade in raw cotton.1 This puts U.S. growers in a critical position to meet global demand. At Cotton Incorporated, we work to support farmers as they meet this demand by funding research to address their challenges and ensure they have those results as soon as possible.
Having visited many cotton fields and gins across the country, I’ve seen firsthand the challenges growers face – from unpredictable weather to rising input costs. Given the current economic conditions, increasing input efficiency through data-driven insights is crucial for supporting grower profitability and ensuring the long-term viability of their operations. It’s not just about cutting costs; it’s also about increasing yields. Data-driven innovations are leading to increased efficiency, improved resource management, and new market opportunities.
Data-Driven Innovation in Action
U.S. cotton growers are increasingly adopting data-driven approaches to optimize their operations. Many of these technologies translate into tangible on-farm benefits. For example, considering precision agriculture, autosteer/GPS systems are now used by 86% of growers, and yield monitor adoption has jumped significantly in recent years.2 These technologies are the foundation of data-driven decision-making, providing a wealth of information about field variability. Plus, new harvesters with built-in cellular modems are providing real-time yield data, further simplifying data collection.3 The benefits of data extend across the entire cotton production process:
Improving Water Use Efficiency
Water is a precious resource, especially in arid regions. Precision irrigation, guided by data on soil moisture and weather patterns, allows growers to optimize water application with exceptional accuracy.4 This not only maximizes efficiency and conserves a vital resource but also contributes to cotton farmers’ profitability by reducing water costs and improving yields.5
Targeted Crop Management
Data enables more precise and effective crop management. Variable-rate fertilizer applications, informed by comprehensive grid soil sampling and advanced nutrient models, ensure that nutrients are applied only where and when they are needed.6 Similarly, Degree Day 60 (DD60) models – which use a 60°F threshold to predict cotton growth (with development slowing below that temperature) – coupled with real-time weather data, optimize the timing of critical inputs, maximizing their efficacy and minimizing environmental impact. The integration of Radio Frequency Identification (RFID) tags in round modules provides valuable data for tracking and managing cotton from sub-field areas, improving efficiency and traceability.7 This level of traceability allows for targeted interventions and optimized resource allocation at every stage of production.
Integrated Pest Management (IPM)
Data analysis plays a crucial role in informing IPM strategies, enabling growers to make more informed decisions about pest control. By analyzing factors such as control costs, crop value, potential damage, and pest population dynamics, growers can optimize insecticide and fungicide applications, minimizing environmental impact and promoting responsible pest management practices. Ongoing research refines thresholds for insecticide and fungicide applications based on new data, leading to more targeted and effective pest control.
Advanced Breeding Techniques
Genomic data is revolutionizing cotton breeding, accelerating the development of new varieties with improved yield potential, fiber quality, and resilience to pests and environmental stresses.8 Marker-assisted selection and gene editing technologies are enabling breeders to develop cotton varieties that are better adapted to specific growing conditions, reducing the need for inputs and enhancing overall sustainability. These innovations are crucial for ensuring the long-term resilience of U.S. cotton production in the face of evolving pest pressures.
Weed Control Revolution
Innovations in weed control are also on the horizon. Open-source image libraries are accelerating advancements in AI-powered weed control, enabling more precise and efficient weed management.7 These technologies enable both robotic and traditional application systems to identify and eliminate weeds with pinpoint accuracy, minimizing herbicide use and promoting healthier ecosystems. This machine vision approach reduces the environmental impact of cotton production and promotes biodiversity on and around the farm.
Ginning Optimization
The ginning process is also being optimized with data. Data linkages between the field, harvester, and gin facilitate the fine-tuning of ginning rates, reducing energy consumption and costs associated with fiber separation. Our recent project with SAS Institute showed that advanced data analytics can provide gins with a more accurate estimate of the best processing rate based on the characteristics of the incoming cotton. This holistic approach to data integration ensures the entire cotton production process is as efficient as possible.
Pictured (from left to right): Agricultural innovations including a Field Infrared Thermometer, Harvest Monitoring system, and Weather Station.
Key Metrics for Continuous Progress
For brands, retailers, and growers alike, it’s essential to track progress toward a more efficient and resilient cotton industry. We’re not just talking about abstract goals; we’re talking about measurable improvements that benefit everyone. The U.S. cotton industry is actively measuring its environmental footprint, and the U.S. Cotton Trust Protocol offers a strong foundation for gathering and verifying this crucial data, ensuring transparency and accountability across the entire supply chain.
Here are some key metrics driving continuous improvement over 40 years (1980–2020):
- Water Use Efficiency: Optimizing water use is critical. Benchmarking against industry averages helps identify opportunities for optimization. Impressively, U.S. cotton growers have already boosted irrigation water use efficiency by 58%.9
- Land Use & Biodiversity: Strategies for minimizing land impact and promoting biodiversity on and around the farm are key goals. In fact, U.S. cotton growers have improved land use efficiency by 30% .9
- Input Optimization (fertilizers, pesticides): Optimizing inputs is a priority. Tracking application rates and exploring alternative pest and nutrient management methods are crucial to make sure we are increasing input efficiency.9
- Soil Health: Healthy soil is the foundation of sustainable agriculture. We’re focusing on practical methods to assess and improve soil health for long-term productivity. The results are already visible: U.S. cotton growers have decreased soil loss by 45%.9
- Greenhouse Gas Emissions: Understanding the sources of emissions on the farm and implementing strategies for reduction are essential. And the industry is making strides, with U.S. cotton growers reducing greenhouse gas emissions by 25%.9
The Innovation Imperative: Efficiency and Profitability
The drive for innovation and improved efficiency isn’t just about doing the right thing; it’s also about strengthening the bottom line. When we can measure the impact of our efforts, it translates into tangible benefits for everyone involved. Data-backed improvements can unlock access to preferred supplier programs, potentially leading to premium prices for sustainably sourced cotton. Brands and retailers are increasingly demanding transparency and traceability, and data is the key to proving commitment.
Furthermore, data-driven insights help anticipate and mitigate risks associated with weather variability, resource scarcity, and evolving regulations. By understanding these risks, growers can develop strategies to protect the crops and their livelihoods. Ultimately, resource efficiency translates directly into cost savings. By carefully tracking inputs like water and energy, growers can identify opportunities for operational optimization, reducing waste and improving profitability.
This commitment to data extends beyond our borders. The International Standards Organization (ISO) is undertaking an ambitious effort to globally standardize agricultural data. As part of the U.S. Technical Advisory Group (TAG), I’m proud to be involved in this initiative, which will foster greater interoperability and make it easier for growers to gain benefits from their data.
Embracing the Future of Cotton – Join the Data-Driven Movement
Data-driven innovation is essential for the future of cotton farming and promises a more resilient industry. I encourage growers to explore the available resources and tools to unlock the potential of data on their farms (several of these farmer-focused resources are listed at cottoncultivated.cottoninc.com). By embracing data-driven innovations, U.S. cotton growers can increase efficiency, improve profitability, and contribute to a more robust future for the industry. The path forward will continue to involve continuous improvements in every aspect of cotton production.
Dr. Ed Barnes – Senior Director of Agricultural & Environmental Research
1 United States Department of Agriculture, Economic Research Service. Cotton and Wool. Link
2 Bayramova et al. (2024). Sustainable cotton farming trends: Leveraging natural resources survey insights for U.S. cotton production. BioResources. Link
3 Hardin IV et al. (2022). Internet of things: Cotton harvesting and processing. Link
4 Barnes, E.M. et al. (2020). Forty years of increasing cotton’s water productivity and why the trend will continue. Applied Engineering in Agriculture. Link
5 Evett, S.R. et al. (2020). Theory and development of a VRI decision support system: The USDA-ARS ISSCADA approach. Transactions of the ASABE. Link
6 Roberts, R.K., English, B.C., Larson, J.A., Cochran, R.L. (2003). Use of precision farming technologies by cotton farmers. Beltwide Cotton Conferences. Link
7 Barnes et al. (2021). Opportunities for robotic systems and automation in cotton production. Applied Sciences. Link
8 Sreedasyam, A. et al. (2024). Genome resources for three modern cotton lines guide future breeding efforts. Nature Plants. Link
9 Field to Market: The Alliance for Sustainable Agriculture. (2021). Environmental outcomes from on-farm agricultural production in the United States – National Indicators Report (4th Edition). Link
