Recent advances in artificial intelligence (AI) and computer technologies are changing the way we understand plants and their interactions with their environment. These developments could help breeders develop more resilient crops and prepare farmers for a future of increasing challenges. With a growing world population and the pressures of soil degradation, pests, diseases and climate change, this is crucial.
The state of affairs :
AI algorithms are nothing new in plant science. Robots roam fields, photograph plants and use deep learning methods to detect diseases and analyse plant characteristics. This enables precise and consistent data collection in agriculture.
But the latest AI-based tools go even further and allow researchers to decode the complex inner workings of plant biology.
AI and computer technologies pave the way for more resilient plants
One notable example is Google DeepMind's AlphaFold project, which has increased the coverage of plant proteins to over 60 %, leading to a deeper understanding of plant structural biology. Researchers such as Jake Harris from the University of Cambridge are using this technology to understand the chemical modifications to plant DNA that play a role in stress responses.
Another exciting project is the development of a digital twin of an apple tree by Daniel Uyeh from Michigan State University. Using LiDAR, cameras and other sensors, detailed digital models of trees under different conditions are being created. This enables farmers to simulate future climate and field conditions and plan accordingly.
Beyond genes: soil, climate and cultivation
Recent advances in AI are enabling plant scientists to look beyond genes and proteins. Researchers at the University of Kentucky have shown that machine learning algorithms can predict the genetic composition of a grapevine from the soil microbiome. This suggests that plants could be bred to be better hosts for beneficial microbes, which could reduce the amount of water or chemicals needed for cultivation.
New technologies and their implications
The integration of single-cell RNA sequencing (scRNA-seq) technologies into plant research is another major advance. The recently developed RevGel-seq method allows for more efficient and flexible sample preparation, enabling deeper insights into plant cell biology. This technique could be instrumental in better understanding the molecular mechanisms behind plant responses to environmental stressors.
Challenges and future prospects
Despite impressive progress, the integration of AI into plant biology faces challenges. There is a lack of digitised images of various physical aspects of plants, and it is difficult to find scientists who understand both biology and computer science. In addition, plant sciences often do not offer the salaries and funding available in medical research.
Nevertheless, large language models (LLMs) that power chatbots and other AI tools offer a promising future. These models could make it possible to decode the language of DNA and proteins and understand the interactions of different genome regions.
The latest advances in AI and computational technologies offer a more detailed view of plants and their interactions with the environment. These technologies have the potential to revolutionise plant biology, develop more resilient crops and help farmers prepare for a future under the challenges of climate change and a growing global population. While there are still some challenges to overcome, the future of agriculture with these new tools is promising and exciting.
For more information on current developments in plant biology and artificial intelligence, visit the Plant Biology 2024 Conference(Plant Biology 2024).