Ukrainian IT Solutions and Artificial Intelligence Improve Cotton Yield Forecasting in Texas
Cotton remains a vital crop for the agricultural sector in Texas and the United States. However, in recent years, Texas farmers have faced serious challenges: climate change, extreme weather events, droughts, storms, and pest infestations increasingly lead to crop losses and economic damages. In particular, in 2022, the state experienced its worst cotton harvest in years, with economic losses exceeding $2 billion. In the High Plains region, which produces over two-thirds of the state’s cotton, the harvest abandonment rate reached 68%, and overall production fell by 53% compared to the five-year average.
This is reported by AgroReview
Challenges in Yield Forecasting: Data Scarcity and Climate Impact
Texas farmers are increasingly abandoning cotton cultivation due to rising temperatures and unpredictable climate conditions. According to Texas A&M AgriLife Extension, in June of last year, cotton acreage decreased by 450,000 acres, representing a 7% decline, with the abandonment rate at 39%. Cotton is sensitive to weather changes, especially droughts, floods, and sharp temperature fluctuations, which can completely destroy the harvest. Pest infestations, such as cotton weevils, aphids, and whiteflies, remain common and significantly reduce both the quality and quantity of the yield. At the same time, irregular irrigation and soil diversity in the fields add complexity to accurate forecasting. An additional problem is the lack of systematic data collection, which complicates the creation of reliable forecasts and the effective use of resources.
“The lack of systematic data collection also complicates accurate predictions. According to EOS Data Analytics (EOSDA), a company with Ukrainian roots specializing in satellite analytics solutions for agriculture, the absence of localized data and the fragmentation of historical records can significantly reduce forecast accuracy, leading to financial instability and inefficient resource use.”
Implementation of Satellite Analytics and Artificial Intelligence
In light of new challenges, Texas farmers are turning to modern technologies. The Ukrainian company EOS Data Analytics has initiated a pilot project for cotton yield forecasting in the state, utilizing satellite data, historical statistics, agricultural calendars, and artificial intelligence. By integrating satellite observations and machine learning algorithms, EOSDA has created a model that helps farmers make informed decisions regarding irrigation, soil treatment, and pest control, reducing resource costs and increasing resilience to weather risks. This approach allows for realistic forecasts for logistics, processing, and export, significantly enhancing the accuracy and timeliness of crop condition assessments.
Particularly valuable for farmers is that modern solutions help compensate for the lack of historical data. EOSDA combines real-time satellite imagery, historical weather data, and agrochemical information, ensuring a comprehensive approach to monitoring and analyzing field conditions.
EOS Data Analytics is a global provider of satellite analytics for the agriculture and forestry sectors, capable of creating solutions for 22 industries. The company, part of the Noosphere space group founded by Max Polyakov, has been operating since 2015 and collaborates with government, commercial, and scientific organizations. In January 2023, EOSDA launched its first Earth observation satellite, EOS SAT-1, using a Falcon 9 rocket from SpaceX at the Cape Canaveral Space Station in Florida. The satellite, developed by Dragonfly Aerospace and equipped with two DragonEye cameras, provides high-resolution imagery and can cover up to 1 million km² daily, allowing for detailed real-time mapping of field conditions.