The Alliance at the 9th International Plant Phenotyping Symposium (IPPS9) 2026

The session explores the work of the Alliance’s Banana Characterization & Evaluation team and how banana phenotyping can move from controlled environments to field-ready, lower-cost approaches. It covers the assessment of Musa genetic diversity under controlled conditions in the BananaTainer, semi-controlled greenhouse studies, and the development of transpiration and growth models for banana genotypes exposed to varying climatic conditions.

It examines how the team validated transpiration and growth models under fluctuating field conditions using state-of-the-art equipment, and how these results are being further validated through a faster, lower-cost smartphone-based approach. Using artificial intelligence, the smartphone pipeline extracts stomatal density, size and pore aperture from leaf images, linking stomatal patterning with transpiration behaviour and field water use.

The session highlights what these findings mean for banana breeding programmes in the Global South, particularly the potential of AI-supported smartphone phenotyping to accelerate screening for drought tolerance and climate resilience across multiple locations and environments.

Join a dynamic discussion on how collaboration, data, capacity, and fit-for-purpose technologies can expand access to phenotyping across Africa. Discover lessons from Ona and Bruno, highlighting the value of affordable, repairable tools, local data, and solutions designed around real-world breeding conditions, and explore how these approaches can be adapted across crops and environments.

Discover how Ona, a smartphone-based computer vision workflow, is making quantitative field phenotyping more accessible to breeding programmes. See how field images are transformed into trait data, validated under African field conditions, and supported by the affordable Bruno pushcart for fast, consistent image collection. The session highlights how AI can support breeders with reliable data for better decision-making across crops, sites, and environments.