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  • Speculative Long Positioning Coincides with Rising Cotton Prices

    Speculative Long Positioning Coincides with Rising Cotton Prices

    The Commodity Futures Trading Commission (CFTC) publishes weekly “Commitment of Traders” (COT) data on the positions of index funds and hedge funds in agricultural futures markets (Figure 1).  The changes in these speculative futures positions have near term value in explaining fluctuations in ICE cotton futures.  

    For roughly two years, the hedge fund (or “non-commercial” or “managed money”) speculative position has been net short, meaning there is an excess of outright short sellers over longs.  This position has been associated with a low level and relatively flat pattern of ICE cotton nearby futures settlements.

    In April of 2026, the hedge fund short position in ICE cotton flipped to net long (see the thin upward green spike on the right-hand side of Figure 1).  This move was associated with initial buying to cover open short positions, followed by outright new buying.  This move is also associated with a twenty-cent rally in nearby ICE cotton futures.

    What other market implications are there from this speculative positioning?  Judging from the narrowness of many of the green spikes in Figure 1, we observe that the bullish or bearish influence of hedge fund positioning can sometimes be short lived. In the present case, hedge fund buying can act like a catalyst for higher prices, perhaps influencing prices to trend higher and move more quickly than fundamentals might justify.  The same can happen in reverse, i.e., liquidation of long speculative positions can contribute to volatility.  This has implications for the need for pre-harvest pricing strategies.

    The current price outlook for U.S. cotton in 2026 is fundamentally neutral in terms of the year-over-year comparison of ending stocks. The 2026/27 projection of ending stocks is within 500,000 bales of the 2025/26 estimate of ending stocks.  But in the near term, speculators and commercials are likely waiting for the unfolding of a so-called “weather market”, i.e., the effect of early dryness and forecasted El Niño moisture on the supply outcome.  The hedge funds will play their speculative role in this outcome, and likely contribute to seasonal price volatility.

    Figure 1. ICE Cotton Net Position of Index funds and Hedge Funds vs. Nearby ICE Cotton Futures Settlement

    January 3, 2006 Through May 12, 2026

    Robinson, John. “Speculative Long Positioning Coincides with Rising Cotton Prices.” Southern Ag Today 6(21.3). May 20, 2026. Permalink

  • U.S. Beef Exports to China Bottleneck 

    U.S. Beef Exports to China Bottleneck 

    U.S. beef exports to China have been an ever-evolving story in recent years. As shown on the chart above, exports were effectively zero until 2017 when China removed a ban on U.S. beef that dated back to 2003. Exports surged in 2021 and 2022, briefly making China a top three destination alongside Japan and South Korea. Since early 2025, beef exports to China have plummeted to very low levels amid broader trade challenges. For the first three months of 2026, beef exports to China totaled just 5.3 million pounds, a 95 percent decline from a year ago. 

    The lower exports over the past year have been driven by the lack of U.S. beef facilities registrations that are required for all food manufacturers who export into China. Over 400 U.S. beef plants lost the ability to export into China after registrations expired and were not renewed over the past year. President Trump’s summit with Chinese leader Xi Jinping in China last week led to hope from the beef industry that these expired registrations would be renewed and that larger exports to China could resume. 

    On Friday, the U.S. Meat Export Federation reported registration extensions have been granted to 425 overdue beef establishments, and an additional 77 establishments have been added, while 38 establishments remain suspended. This is good news for U.S. beef exports amid challenging export dynamics. Tight supplies of U.S. beef and high domestic prices have been a headwind to beef exports. Those headwinds remain with the renewed registrations, but China is a key market. 

    It is also worth mentioning U.S. beef exports to Hong Kong have increased over the past year, while exports to China declined. It is helpful to combine exports to both countries when looking at overall trends. While Hong Kong has offset some of the decline in exports to mainland China, combined exports to China and Hong Kong remain well below the levels seen during 2021–2024, when mainland China was a much larger buyer.

    Maples, Josh. “U.S. Beef Exports to China Bottleneck.” Southern Ag Today 6(21.2). May 19, 2026. Permalink

  • Check in on Current Non-Real Estate Farm Debt

    Check in on Current Non-Real Estate Farm Debt

    Authors: Charley Martinez, Mason Collins, and Eli Mundy

    As mentioned in previous Southern Ag Today (SAT) articles (Martinez and Ferguson 2022, Martinez 2023), monitoring Non-Real Estate Farm Debt provides insight into debt health. At the time of this article, planting season has begun or is in full swing for others, input prices have increased over the last few weeks, and livestock prices have remained at high levels. Last month, the Federal Financial Institutions Examination Council released its most recent Call Reports, which provided insights into the final quarter of 2025. As a refresher, every commercial bank in the U.S. submits its quarterly Reports of Condition and Income, which are known as call reports. Within these call reports are totals of agricultural loans and the status (on time or late) of the loans. Figure 1 displays the total loan volume (yellow line) and loan volume for three late categories (30-89 days late, 90+ days late, non-accrual) for the last 12 quarters (3 years). The totals are for all the Southern Ag Today States. 

    In the fourth quarter of 2025, total non‑real estate loans (yellow line) continued to trend upward overall and was 4% higher compared to 2024 Q4. Non-accrual (blue line) loans remained elevated at the 2025 Q3 levels, and increased 172% from 2024 Q4. Loans that are 90+ days late (grey line) remained about the same as 2024 Q4, and decreased 3%. Last year, the most concerning statistics were the loans that were 30-89 days late (orange line), which increased to $108.9 million in Q1 in the SAT states. By the end of the year, total loan amounts in this category decreased to $49.6 million, but it seems the decline was the result of debt moving to the non-accrual category by Q4 of 2025. While this loan type decreased from Q1, the amount increased by 35% compared to 2024 Q4. Due to the varying size of states, measuring the percentage of 30-89 days late loans compared to total loan volume is a good way to compare the SAT states and the impacts of these bad loan types. In 2025 Q4, the quarterly average of 30-89 days late loans to total loan volume was 0.3% (which is stable), with the highest being  Kentucky (0.8%), North Carolina (0.5%), and Louisiana (0.4%). When comparing the percentage of total late debt (non-accrual, 30-89 days late, and 90+ days late) relative to total loan volume, the quarterly average was 0.9%. Alabama (3.1%), Georgia (2.4%), Louisiana (1.8%), Mississippi (1.2%), and Arkansas (1.1%) were the only states above the SAT average. North Carolina and South Carolina were the only two states below 1%. 

    Taking a broad view, the 2025 fourth‑quarter bank reports give a useful snapshot of farm debt conditions following a difficult profitability year for many row‑crop operations and a strong revenue year for livestock producers across the SAT states. The reports show that financial condition remains stable in several states, but there are also early warning signs in others that warrant close attention. Recent improvements in row‑crop prices offer some potential relief for operating debt in 2026, though margins remain tight. Government payments will also be an important factor this year; ARC and PLC payments are expected again for the current crop year, though they will not be received until October 2026, and should help reduce some problem loan balances. In the meantime, producers should closely monitor working capital, manage short‑term debt carefully, and continue the sound production, marketing, and risk‑management practices they already have in place. Overall, while reliance on non‑real estate credit has increased, rising input costs, higher interest rates, and income variability are placing added pressure on farm finances, making proactive financial management especially important in the months ahead.

    Figure 1. Non-Real Estate Farm Debt from 2023 Q1- 2025 Q4

    Source: Federal Financial Institutions Examination Council

    References

    Martinez, Charley, and Haylee Ferguson. “Current Non-Real Estate Farm Debt“. Southern Ag Today 2(30.3). July 20, 2022. Permalink

    Martinez, Charley, Mason Collins, and Eli Mundy. “Check in on Current Non-Real Estate Farm Debt.” Southern Ag Today 6(21.1). May 18, 2026. Permalink

  • Incorporating AI and Digital Technologies: Opportunities and Challenges for Rural Counties

    Incorporating AI and Digital Technologies: Opportunities and Challenges for Rural Counties

    Authors: An-Ting Liao (Graduate Research Assistant, TAMU) & Chrystol Thomas (Assistant Professor and Extension Specialist, AgriLife Extension)

    Agriculture is a critical pillar of economic activity in rural communities, driving employment, income stability, and local economic development (Unjia et al., 2024). Recent advancements in artificial intelligence (AI), machine learning, and digital twins present new opportunities for businesses, enabling improvements in performance and competitiveness. As agricultural systems continue to evolve, rural communities cannot be left behind. Adopting digital technologies is essential for sustaining agribusiness, including farming, food processing, and distribution, and for supporting future community development.

    AI and digital technologies offer substantial opportunities to improve agribusiness operations (Cavazza et al., 2023). AI systems can enhance business processes by optimizing transactions, refining pricing strategies, and improving supply chain coordination through real time data analysis. For example, digital twins enable the creation of virtual farm models that allow producers to simulate different scenarios and evaluate potential outcomes before making operational decisions(Verdouw et al., 2021). Machine learning applications can also be used to predict crop yields, analyze weather patterns, and forecast market demand fluctuations, enabling more informed and timely decision making. Generative AI tools such as Claude, ChatGPT, and Gemini, and similar tools can support agribusiness operations by enhancing decision-making, facilitating market analysis, and improving access to information. Empirical evidence suggests that agribusinesses adopting these technologies can achieve higher operational efficiency, reduce input costs, and improve long term financial performance (Yuan et al., 2025). In addition, by integrating AI tools into production and management systems, rural agribusinesses also enhance their adaptability and resilience in a competitive and dynamic market environment.

    However, rural agribusinesses are likely to face challenges in adopting advanced technologies. Limited financial capital remains a primary barrier, as small and medium sized enterprises typically lack the resources required for initial investments in digital infrastructure, software, and system maintenance (Gálvez Nogales and Casari, 2023). In addition, technical capacity constraints and limited digital infrastructure restrict rural agribusiness’s ability to implement and manage AI tools effectively, as many rural counties still experience unreliable connectivity. Demographic factors also contribute to these challenges, as rural areas often face shortages of younger, technologically skilled workers due to outmigration. Furthermore, there is limited awareness and training related to AI applications among agribusiness operators, reducing their ability to integrate these tools into operations (Udoh et al., 2025). 

    Addressing barriers to technology adoption requires accessible resources, targeted strategies, and institutional collaboration. The growing availability of free or low-cost digital tools and AI platforms provides rural agribusinesses with entry for integrating technology into their operations. Strengthening digital literacy and workforce training is essential for effective use, while embedding digital technologies into daily practices supports gradual and sustainable adoption. Collaboration with academic institutions, including cooperative extension services and land-grant universities, also play a key role in building local capacity through technical assistance, training, and research-based support (Jaiswal et al., 2025). These efforts further strengthen efficiency, profitability, and resilience in agribusiness systems, reinforcing the long-term competitiveness and sustainability of rural communities.

    References

    Cavazza, A., Dal Mas, F., Paoloni, P., & Manzo, M. 2023. Artificial intelligence and new business models in agriculture: A structured literature review and future research agenda. British Food Journal, 125(13), 436–461. https://doi.org/10.1108/BFJ-02-2023-0132.

    Gálvez Nogales, E., & Casari, G. 2023. Promoting the digitalization of small and medium-sized agrifood enterprises in Asia and the Pacific. Food and Agriculture Organization of the United Nations. https://doi.org/10.4060/cc8826en.

    Jaiswal, N., Phukan, P., Ramsem, P. A., Vyas, D., Tamgale, G. S., Verma, A. K., Singh, G., Kumari, R., Ribadiya, N. K., & Singh, J. (2025). Bridging the gap: The role of agricultural extension in knowledge transfer and rural development. Plant Archives.

    Unjia, Y., Padaliya, S., Agrawat, Y., & Padaliya, M. 2024. Rural development and agribusiness integration. In Agribusiness management. Routledge.

    Udoh, F. E., Udom, U. G., & Udo, U. A. 2025. Awareness, perception and adoption of artificial intelligence (AI) technologies among agricultural entrepreneurs in Nigeria. International Journal of Contemporary Africa Research Network, 3(2). https://doi.org/10.5281/zenodo.

    Verdouw, C., Tekinerdogan, B., Beulens, A., & Wolfert, S. 2021. Digital twins in smart farming. Agricultural Systems, 189, 103046. https://doi.org/10.1016/j.agsy.2020.103046.

    Yuan, Y., Wu, H., & Shen, Y. 2025. Achieve sustainable operation of agricultural enterprises: Improving agribusiness performance through digital transformation. Frontiers in Sustainable Food Systems, 9, 1547358. https://doi.org/10.3389/fsufs.2025.1547358.

    Liao, An-Ting, and Chrystol Thomas. “Incorporating AI and Digital Technologies: Opportunities and Challenges for Rural Counties.” Southern Ag Today 6(20.5). May 15, 2026. Permalink

  • The Ag Technology Treadmill is About as Fun as the One at the Gym

    The Ag Technology Treadmill is About as Fun as the One at the Gym

    Authors: Joe Outlaw and Bart L. Fischer

    Anyone who ever worked out on a treadmill at a gym—or purchased their own for home use—knows just how unpleasant walking or running on a treadmill can be.  For most of us, it is the rare combination of boring and monotonous, staring at yourself in a mirror while walking or running in place. 

    While the agricultural technology treadmill is neither boring nor monotonous for farmers, it’s currently just as unpleasant.  In his 1958 book Farm Prices: Myth and Reality, renowned agricultural economist Willard Cochrane first introduced the concept of the “technology treadmill” (or agricultural treadmill).  According to Cochrane, early adopters of agricultural technology do so to lower production costs and increase profits, only to see widespread adoption of the technology causing an increase in supply that drives down market prices.  All remaining farmers are forced to adopt the new technology just to survive, trapping them on a “treadmill” where they must continuously adopt the latest technology in hopes of becoming profitable again. The alternative is getting off the treadmill…and going out of business.

    One doesn’t have to look very hard to see this playing out in real life. U.S. farmers have continuously adopted new seed, labor-saving, fuel-saving, time-saving, and many other types of technologies in the name of lower costs and higher profits.  In the case of seed technology alone, tremendous innovation has increased yields which, in some years, have offset lower prices and provided an opportunity to break-even or better.  At the same time, farmers continue to get off the treadmill and the number of farms in this country continues to decline. The main question is this: can this go on forever?

    Given the current cost-price squeeze in agriculture—and when weighing the cost of technology against the value of agricultural commodities—the benefits of adopting technology seemingly are not there anymore.  However, technology providers are shielded from this reality as the Federal government provides ad hoc assistance to keep producers from falling off the treadmill.  As Congress works to reauthorize the farm bill, we keep coming back to one solution (albeit not a silver bullet):  continue the shift back to standing farm policy that provides risk management without guaranteeing outcomes.  As farmers face this risk, input suppliers must face it as well and must come to terms with the cost of their products and producer’s ability to pay for them. 

    Outlaw, Joe, and Bart L. Fischer. “The Ag Technology Treadmill is About as Fun as the One at the Gym.” Southern Ag Today 6(20.4). May 14, 2026. Permalink