Scientists in the US are working to engineer cotton plants that naturally produce pigment or colour in their fibres, which will help reduce need for water and chemical-intensive dyeing, fueled by an $11 million grant from the Bezos Earth Fund.
Researchers at the University of Georgia and Clemson University are gearing up to develop cotton of the future. AI, genomics and gene editing are helping them accelerate the development of more resilient cotton varieties.
“The activities are designed as an integrated pipeline, not separate projects,” said Saski. “The main goal is to make cotton more competitive and sustainable by moving value upstream into the plant itself to ultimately reduce greenhouse-gas emissions, water pollution and waste.”
The team has identified heirloom cotton varieties that naturally produce subtle reds, greens and browns. By enhancing those biological traits and pigment pathways, the team hopes to eventually expand the range and vibrancy of colors available to consumers.
Clemson University’s Chris Saski estimates a reduction in water use associated with textile dyeing by at least 70%, cutting dye-related chemical inputs and wastewater by 80%, and reducing dyeing energy demands by half.
The research will combine gene editing, artificial intelligence (AI) and advanced breeding tools to identify and assemble favorable genetic combinations that enable cotton plants to maintain productivity under increasingly challenging growing conditions far more rapidly than traditional breeding processes.
“Peng Chee, professor of crop and soil sciences and a cotton breeder at UGA, will evaluate promising traits developed through the project under real-world growing conditions,” a University of Georgia field report informed.
Field testing allows researchers to determine whether new traits can maintain performance amid variations in weather, soil conditions, pests and farm management practices.
While Clemson researchers are leading efforts to identify and engineer those new, desirable traits, UGA’s role is to determine whether they hold up in the field.
Chee’s team will use advanced imaging systems, AI and DNA-based prediction models to evaluate thousands of cotton plants to develop elite germplasm — the most promising plant parent material — and provide the field evaluation and breeding infrastructure needed to bring desirable traits identified in Saski’s lab closer to practical use for growers.
Image courtesy: Unati Silks
