Scientists at the Royal Botanic Gardens, Kew, are using artificial intelligence and computer vision to identify plant and fungi species at risk of extinction [1].
This initiative accelerates the identification process for thousands of threatened species, allowing conservationists to make faster and more informed decisions to prevent permanent biodiversity loss [1].
The project relies on the integration of digital archives and AI tools to analyze millions of plant and fungi specimens [1]. By applying computer vision to digitised herbarium collections, the researchers can process data from collections located worldwide [1], [2]. This technological approach allows scientists to scan through vast amounts of botanical data more efficiently than traditional manual review.
The effort focuses on identifying species that are most vulnerable to extinction [1]. By leveraging these AI tools, the team at Kew can pinpoint specific specimens that require urgent protection and map their distribution across different global environments [1], [2].
Reports indicate the project has been ongoing through 2024 and 2025 [1]. The use of these tools represents a shift toward high-tech conservation, where digital footprints of plants help determine their survival strategies in the physical world [1]. The process involves training AI to recognize the unique morphological characteristics of rare plants and fungi, which helps in distinguishing them from common species within the archives [1].
This system allows for a more scalable approach to botany. While human experts are essential for final verification, the AI handles the initial screening of the millions of specimens [1]. This collaboration between human expertise and machine learning reduces the time required to catalog endangered flora [1], [2].
“Scientists at the Royal Botanic Gardens, Kew, are using artificial intelligence and computer vision to identify plant and fungi species at risk of extinction.”
The application of computer vision to botanical archives transforms static museum collections into active conservation tools. By automating the identification of endangered species across millions of records, researchers can identify critical biodiversity gaps and prioritize protection efforts for species that might otherwise be overlooked in manual surveys.
