Q&A with Melissa Cregger: From field to factory with precision crops

As co-chief science officer for the Center for Bioenergy Innovation (CBI) at the Department of Energy's Oak Ridge National Laboratory, Melissa Cregger helps guide research focused on developing and improving plant feedstocks to produce advanced chemicals and materials, strengthening U.S. supply chains.

Cregger stewards the work of hundreds of scientists at CBI's 18 research partners across the nation as they work on solutions for non-food plants that grow faster and larger, are resistant to drought and disease and are engineered to produce targeted end-products.

She discussed recent CBI discoveries, why the center is expanding into new plant feedstocks like pine and eucalyptus, and how automation and AI can accelerate the path from genetic insight to factory-ready plants. The use of AI and robotics is a cornerstone of the DOE Genesis Mission, a national initiative to build the world's most powerful scientific platform to accelerate discovery science, strengthen national security, and drive energy innovation.

Q: What is your focus at CBI as co-chief science officer?

A: My focus is stewarding research for the development of plants that can reliably produce the fuels, chemicals and materials we need, while performing in real-world conditions on marginal lands not typically used to grow food. CBI has historically focused on poplar and switchgrass, two leading perennial biomass crops, while growing a broader portfolio of feedstocks and tools to improve performance and economic viability.

CBI's goal isn't just higher yield crops - it's dependable yield in the places where these crops make the most sense to grow. We're identifying genes that control the traits that matter most in the field, such as the type and quantity of natural polymers they produce and their disease resistance and tolerance to stress such as drought, flooding and heat, so we can tailor feedstocks to different growing regions.

Genetic resources, nationwide footprint key to success

Q: What sets CBI apart in its research?

A: What sets CBI apart is the scale of our genetic resources - large, diverse plant populations paired with our distinctive expertise in plant genetics, plant and microbial engineering, and biomass deconstruction. CBI's broad network of university, national lab and industry partners is a powerhouse of science and technology supporting the agricultural and manufacturing sectors.

Q: How is CBI improving poplar as a bioenergy feedstock?

A: We're working to get the best of both worlds in poplar: high biomass yield from one species, and stress tolerance from another - then using genomics to select hybrids that can deliver both. CBI recently expanded work into heat stress tolerance and other traits in Populus deltoides and is especially interested in hybridizing it with Populus trichocarpa, combining stress tolerance with high yield to create trees better suited for varied environments.

Q: What discoveries are you most excited about right now?

A: One of our biggest wins has been discovering the Booster gene - because it directly improves photosynthetic efficiency and biomass yield. In the greenhouse, it increased poplar biomass by about 200 percent. CBI researchers are also identifying genes tied to plant composition, stress tolerance and pathogen resistance - traits that can determine whether a feedstock thrives outside ideal greenhouse conditions.

Q: CBI has added new feedstocks to its research portfolio recently. Why expand beyond poplar and switchgrass?

We've onboarded two additional biomass feedstocks - pine and eucalyptus - each with different advantages for U.S. supply chains and product possibilities. Pine is exciting because there's a large standing stock in the southeastern U.S. that we can begin leveraging for advanced chemicals and materials. The Southeast has this historic quantity of pine that is mostly unused as traditional pulp and paper markets have shifted their sourcing overseas.

Eucalyptus is a perennial crop that regrows every year in warmer regions and can offer both biomass and valuable extractable compounds. It opens a different door, because it's naturally high in terpenes, which can give us an expanded portfolio of chemicals, not just products from woody biomass alone. CBI is examining natural variation in terpene composition and abundance - traits that could expand the range of products made from plant feedstocks.

Q: How does CBI's research support land use goals and feedstock economics?

A: CBI aims to support biomass cropping systems that fit the landscape rather than compete with food production. The question isn't just 'Can we grow a biomass crop?' It's 'Can we match the right plant to the right environment?' - such as pairing drought-tolerant trees with marginal lands where water is limited, a focus area that's been very exciting to explore.

CBI is also conducting techno-economic analysis of factors such as how plant traits relate to real logistical and cost impacts. One example is our work on wood density. We conducted a study on how denser plant materials can reduce transportation costs by allowing more biomass to be shipped per load.

If you've got big, fluffy trees that are large but not really dense, you will end up spending more to transport them for processing versus a tree that produces a smaller log but contains just as much biomass. You can fit more of those smaller logs on the trucks, and that saves on fuel and other costs.

AI and automation speed development of advanced feedstocks

Q: What role will automation and AI play in the next phase of CBI feedstock development?

A: CBI is leaning into automation and AI because we've become so effective at plant transformation that we created a bottleneck: validating performance traits fast enough for the large numbers of engineered or selected plant lines created, especially in poplar and switchgrass. Advanced phenotyping can help us move from experiment to insight much faster.

We are leveraging capabilities like the Advanced Plant Phenotyping Laboratory at ORNL, a shared use facility that uses automation and AI to guide the imaging and analysis of plant structures. We're developing machine learning methods and an AI vision transformer model that can quickly connect imaging data to physiological measurements - an approach aimed at increasing throughput from gene discovery to trait validation.

Q: What's your personal goal for the program in the years ahead?

A: Fostering collaboration is my favorite part of the job. The integration of many different science disciplines has had a profound influence on our success at CBI. We bring together everything from genetics to microbiome science, phenotyping, automation and techno-economic analysis to speed learning cycles and make bio-based production more viable at scale. I really like being able to think about the integration of all of these different disciplines and how we can leverage each of them better to solve really large problems.

As we look to the future of CBI research, we are thinking about how we can expand our portfolio of end-products. By leveraging automation and AI with our range of disciplines, we can shorten the time from experiments to data processing and analysis that then guides our next set of iterative experiments. CBI's collaborative structure is key to that future.

UT-Battelle manages ORNL for DOE's Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE's Office of Science is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science. -Stephanie Seay