loading page

High-throughput phenotyping of the core European Heritage Collection (ExHIBiT) under waterlogging
  • +12
  • Villő Bernád,
  • Emilie Jacob,
  • Jason Walsh,
  • Patrick Langan,
  • Nadia Al-Tamimi,
  • Kelly Houston,
  • Luke Ramsay,
  • Joanne Russel,
  • Robbie Waugh,
  • Stéphanie Guénin,
  • Hervé Demailly,
  • Gaëlle Mongelard,
  • Eleni Mangina,
  • Laurent Gutierrez,
  • Sónia Negrão
Villő Bernád
University College Dublin

Corresponding Author:[email protected]

Author Profile
Emilie Jacob
Université de Picardie Jules Verne
Jason Walsh
University College Dublin
Patrick Langan
University College Dublin
Nadia Al-Tamimi
University College Dublin
Kelly Houston
James Hutton Institute
Luke Ramsay
James Hutton Institute
Joanne Russel
James Hutton Institute
Robbie Waugh
James Hutton Institute
Stéphanie Guénin
Université de Picardie Jules Verne
Hervé Demailly
Université de Picardie Jules Verne
Gaëlle Mongelard
Université de Picardie Jules Verne
Eleni Mangina
University College Dublin
Laurent Gutierrez
Université de Picardie Jules Verne
Sónia Negrão
University College Dublin


Barley is the most produced crop in Ireland; it is essential as a fodder crop and a key ingredient for the malting industry, contributing to Irish national identity. In Ireland, climate change is bringing more extreme rain; leading to an increase in flooding and waterlogging events. Barley is particularly sensitive to waterlogging urging the need to harness genetic diversity and breed barley with increased waterlogging tolerance to maintain current agricultural production. One of the limiting factors in breeding is the drawbacks of traditional phenotyping. This project relies on modern high-throughput phenotyping, which allow non-destructive, continuous and quantitative data collection. Using imaging sensors in controlled conditions, we phenotyped a collection of barley accessions under controlled and waterlogged conditions using RGB, fluorescent and hyperspectral cameras (VNIR and SWIR). We used the core European Barley Heritage collection (ExHIBiT); made up of 230 diverse 2-row spring barley accessions. This collection was assembled, genotyped, agronomically characterized and its application for association mapping has been established by our team. We observed that 14 days of waterlogging lead to a significant reduction in pixel count (Project Shoot Area) and Quantum yield, showing a large impact on several hyperspectral indices. We also observed that 7 days of recovery after stress are fundamental for differentiate stress resilience. Work is ongoing to optimize hyperspectral image analysis, and establish parameters to distinguish plant performance, enabling to discriminate between resilient and sensitive accessions. These data will be used for association mapping to identify genetic regions contributing to waterlogging tolerance in spring barley.
17 Oct 2022Submitted to NAPPN 2023 Abstracts
29 Oct 2022Published in NAPPN 2023 Abstracts