Dr Alexandra Gibbs

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Dr Alexandra Gibbs is an Assistant Professor in Agriculture and the Environment at our School of Biosciences. Her research on photosynthesis in crop plants spans the whole canopy level, addressing critical crop resilience and yield challenges to food production. She is incorporating advanced technologies like 3D reconstruction and AI deep learning tools into her approach. In this Take 10, Alexandra discusses the benefits of her research in unlocking new solutions for sustainable food and how she plans to build partnerships to translate her work into real-world impact.

Explain your research using everyday terms

I study photosynthesis at the whole canopy level in crop plants. I am particularly interested in how structural properties of plants determine light interception and use. I use methods such as 3-dimensional reconstruction and mathematical modelling to determine how different structural traits influence productivity. This is important because the quantity and colour (spectral composition) of light will determine how much yield a crop can produce, thus strengthening food security. I am also interested in the use of alternative cropping practices to improve yield production, including agroforestry systems and intercropping, the cultivation of two or more crops simultaneously.

What inspired or motivated you to pursue this research area?

Global food security and climate change are defining challenges of our time. I was inspired to pursue crop physiology because understanding how plants capture light and use water fundamentally determines our ability to feed a growing population under increasingly volatile environmental conditions.

My work addresses the pressing need to improve crop resilience and yield without relying on unsustainable inputs. By exploring diverse systems like agroforestry and multi-species intercropping, we can create climate-resilient agricultural landscapes that benefit farmers, communities, and the environment.

What I enjoy most is the interdisciplinary nature of this work. Combining plant biology with cutting-edge technologies like 3D reconstruction and AI deep learning tools, and more recently, techniques from Civil Engineering.

Bridging these fields to unlock new solutions for sustainable food production is incredibly rewarding and gives me hope for a food-secure future.

What is innovative or different about your research?

My research is highly cross-disciplinary, merging traditional plant physiology with advanced computational technologies. A key innovation is using multi-modal deep learning and AI alongside 3D canopy reconstruction. For example, my team , a tool utilising Generative Adversarial Networks to generate highly realistic, artificial images of stomata. This significantly improves image-based analysis, enabling deep learning models to detect stomata with near-perfect accuracy without relying on exhaustive manual data collection. Integrating this AI-driven approach with empirical mathematical modelling allows us to link microscopic metabolic processes to whole-canopy structural traits faster and more accurately than existing methods.

Who benefits from your research?

My research benefits a broad spectrum of stakeholders, from plant breeders and agronomists to environmental policymakers and farmers.

Understanding how canopy structure and stomatal behaviour influence light and water use can help agricultural industries breed more resilient, high-yielding crop varieties. Furthermore, our insights into cropping practices directly support farmers by providing evidence-based practices that boost yield while promoting environmental sustainability.

In the future, this impact can be scaled by integrating our AI tools, like StomaGAN, into commercial phenotyping platforms, making large-scale crop analysis accessible globally. Expanding open-source access to these AI-driven models will empower international researchers and the agritech sector to rapidly evaluate crop traits.

Additionally, translating our findings into policy guidelines will encourage wider adoption of diversified, climate-resilient agricultural systems, ultimately securing food supply chains and supporting rural communities on a global scale.

What achievements or milestones have you recorded recently?

I have secured multiple competitive funding and prizes awarded for improving infrastructure and methodologies to advance crop phenotyping. Most significant among these include a BBSRC International Partnership in AI for Biosciences to analyse cross scale water use by plants, and a recent BBSRC AIBIO Pilot award to map cross-kingdom (plant and animal) image analysis techniques. I was previously awarded a Royal Society Research Grant, the Rank Prize New Lecturer Award, the Gatsby Grant for Exceptional Researchers and a Leverhulme Early Career Fellowship, and in 2022, I was part of a group awarded the UKRI Molecules to Landscapes award.

Are you working with or plan to work with any collaborators or external partners?

While my career to date has been strongly rooted in academic research, a key priority for my future is to significantly expand my engagement with external, non-academic partners. I currently do not collaborate outside academia as much as I would like, but I am eager to connect with agritech industries, policymakers, and farming communities. Expanding this network is crucial to maximising the real-world impact of my work.

By partnering with agritech companies, the AI-driven tools and dynamic canopy models we develop could be translated into commercial phenotyping platforms for plant breeders.

Similarly, working directly with agricultural stakeholders would ensure our insights into wind dynamics, alternative cropping practices and climate resilience are shaped into practical, socio-economically viable guidelines. Ultimately, I want to actively bridge the gap between my fundamental physiological discoveries and the on-the-ground needs of global food production industries.

What big questions or opportunities have emerged from your work recently?

A major opportunity emerging from my recent work is understanding the highly dynamic interaction between crop canopies and wind. Working alongside my PhD students and collaborating with the civil engineering department, we are exploring the biomechanics of how plants physically respond to wind. We are using controlled wind tunnel experiments with drone video analysis in the field to investigate "honami"; the wave-like movement of crop canopies.

This raises a big question: how does dynamic wind movement influence light interception, gas exchange, and crop susceptibility to lodging (i.e. stem breakage)? Understanding these complex biomechanical interactions is crucial. It presents an opportunity to move beyond static 3D plant models and integrate dynamic aerodynamic traits into our digital analyses. Ultimately, this will support future agricultural innovations by guiding the breeding of structurally optimised, climate-resilient crops that can withstand extreme weather events while maintaining high yields.

What support or steps could accelerate this work?

Accelerating this work requires strategic investment in both digital infrastructure and on the ground translation. Increased funding from government and private sectors is essential to scale our AI-driven phenotyping tools from the lab to cloud-based open-access platforms for global breeders. Equally critical is bridging the gap between computational models and field practice.

We need stronger partnerships with agricultural extension services to co-design mixed-cropping and agroforestry systems directly with farmers. Accelerating impact also requires behavioral change and policy support.

Transitioning away from intensive monocultures involves socio-economic risks for farmers, therefore implementing financial subsidies or risk-sharing policies for adopting resilient, multi-species systems would speed up the transition. Ultimately, closer alignment between researchers, agritech developers and policy makers will ensure that fundamental discoveries in plant physiology rapidly translate into climate-resilient agricultural practices and commercial technologies.

What barriers have you overcome throughout your career?

A primary barrier I’ve navigated is the inherent complexity of working across highly distinct disciplines. Merging plant physiology and wet-lab techniques with advanced computer science (like AI and 3D reconstruction) requires mastering different scientific "languages." I overcame this by actively fostering collaborative networks, ensuring clear communication and building diverse teams where computational and biological expertise are equally valued.

Another significant challenge is the traditional bottleneck in manual data collection for plant phenotyping. Analysing microscopic traits across whole canopies took an impractical amount of time. I navigated this with innovati developing AI tools like StomaGAN to generate synthetic training data, drastically reducing manual labour.

Finally, scaling insights from the lab to the field always presents environmental variables. I address this by conducting empirical modelling to validate how structural traits perform under real-world, dynamic fluctuations.

What advice do you have for yourself and future scientists?

I would tell my younger self to embrace unfamiliar technologies early on. Don't be intimidated by fields outside your initial expertise, the most impactful innovations like integrating AI into biology happen at the intersection of different disciplines. Build relationships with industry and policymakers early and always be prepared to explain your complex data in everyday language.

I would also advise focusing on the "so what?" of your research. Impact isn't just about publishing papers, it’s about ensuring your tools and insights reach the people who need them, whether that’s a plant breeder or a farmer.
Dr Alexandra Gibbs, Assistant Professor, School of Biosciences