20246801241750

The sustainability of US cotton production is pivotal to agricultural sustainability in the southern US. Protecting and improving soil health, reducing greenhouse gas (GHG) emissions, and enhancing input use efficiency are central to improving the sustainability of cotton in the face of changing climatic conditions.

According to the most recent USDA-ERS report on tillage and conservation cropping in the US (Claassen et al. 2018), 60% of cotton acreage is still under conventional tillage, compared for example, to only 30% or less in soybean. Tillage intensity has increased due to the need to control herbicide-resistant and other problematic weeds (Cast 2012), which is now widespread throughout the US cotton belt (Heap 2023).

Intensive tillage contributes greatly to greenhouse gas (GHG) emissions, stored carbon loss, and a loss of overall soil health, while conservation tillage is considered a vital component of a sustainable soil health management system (Elder and Lal 2008; USDA-NRCS 2017).

Cotton is inherently a low residue crop, which in turn adds limited amounts of carbon during the growing season. Because cotton is commonly grown with low residue crops in rotation (Claassen et al. 2018), this is a major area where rapid gains can be achieved in soil health improvement and climate change mitigation. In this regard, cover crops and living mulches can play a key role (Wick et al. 2017).

A recent analysis by the Cotton 2040 Initiative revealed that cotton is a vulnerable crop to climate change impacts (WTW 2022). There is a crucial need to make cotton cultivation a carbon-neutral, or better yet a net carbon-positive enterprise, while simultaneously mitigating/adapting to the adverse effects of climate change.

The majority of US cotton is already grown in marginal soils with low organic matter content. Potential increases in tillage to manage the anticipated surge in herbicide-resistant weeds associated with climate change (Ramesh et al. 2017) is expected to exacerbate this problem. Further, the use of artificial intelligence/machine learning (AI/ML)-assisted precision application technologies can greatly improve resource input use efficiency, which can in turn reduce GHG emissions (e.g. Cotton Inc. 2018).

These precision regenerative practices are also expected to create new market opportunities, through, for example, carbon crediting and sustainable cotton markets, and empower the rural agricultural workforce via employment generation.

The long-term goal of the proposed research is to apply improved precision management practices to enable enhanced carbon sequestration and reduced greenhouse gas emission, pest control, and nutrient and water management; and to address labor challenges, steward land, create new market opportunities, and ensure a sustainable supply of climate-smart cotton. Achieving this will require a coordinated effort among researchers, extension specialists, and broader industry stakeholders.

The specific objectives of this project are: 1. Develop regenerative cotton production practices and investigate their long-term effects on US belt-wide cotton production systems. 1.1. Establish soil organic carbon and carbon intensity baselines for ecoregions in the US cotton belt; 1.2. Investigate regenerative practices for reducing tillage and improving soil health; 1.3. Investigate the long-term impact of regenerative practices in addressing climate change using simulation models. 2. Develop and/or evaluate precision AI/ML and smart technologies for resource conservation and climate change mitigation/adaptation in cotton. 3. Evaluate the economic feasibility of precision regenerative production practices and determine new market opportunities. 4. Expand knowledge about farmers' multi-dimensional experiences of adoption of regenerative practices across the cotton belt. 5. Promote the adoption of regenerative, climate-smart cotton production practices through innovative and collaborative extension and outreach activities. 6. Provide educational opportunities to train the next generation of research and extension scientists and practitioners, including underserved communities, and empower the rural workforce.

This integrated project is expected to bring tremendous benefits to the US cotton industry through the development and implementation of sound regenerative practices for reducing tillage and addressing climate-change impacts. By utilizing precision agriculture technologies, there will be an improvement in the timely diagnosis of field issues and implementation of site-specific measures for increasing input use efficiency and reducing GHG emissions. New market opportunities will be generated, improving overall farm profitability. The economic analysis will highlight the economic benefits of the adoption of precision regenerative practices and smart-technologies for cotton production. The health and safety of farm workers will be improved. Automation will help alleviate labor shortage in rural areas, while equipping them for new employment opportunities.

Texas A&M Agrilife Research

NOT APPLICABLE

10.310 - Agriculture and Food Research Initiative (AFRI)

Institute of Bioenergy, Climate, and Environment (IBCE) [USDA - NIFA]

College Station, Texas 77843-0001 United States

Single Zip Code

Agriculture and Food Research Initiative Sustainable Agricultural Systems (USDA-NIFA-AFRI-009802)