Exploring an automated indoor high-throughput phenotyping facility to investigate the response of faba bean to water stress

Abstract

Abstract Faba bean ( Vicia faba L.) has great potential to contribute to sustainable agriculture and protein security globally. However, it is known to be very sensitive to droughts, which can severely impact yield. Uncovering drought-resilient germplasm is critical for developing resilient cultivars and advancing our understanding of the mechanisms underlying stress adaptation. However, reliable phenotyping of water stress responses remains a significant bottleneck in crop genetics and breeding programs. Overcoming this bottleneck requires high-throughput phenotyping platforms. In this study, we used an indoor image-based phenotyping facility, the National Plant Phenotyping Infrastructure at the University of Helsinki. The facility incorporates cutting-edge imaging technologies such as top- and side-view digital imaging for assessment of growth and development, as well as chlorophyll fluorometry for the detection of physiological responses. In this study, 44 faba bean accessions were subjected to early-stage water stress via weight-based water-holding capacity. The accessions presented a range of responses to water stress across the studied traits, including plant height, total canopy area, digital biomass, and water use efficiency. Our results also revealed a strong correlation between digital biomass and biological biomass. Here, we demonstrate the potential of a fully automated indoor phenotyping facility for screening a relatively large faba bean germplasm collection under well watered and water stressed conditions. Accessions that maintained growth and physiological performance under water stress conditions in this study may serve as valuable pre-breeding materials for the development of drought-adapted faba beans.

Code and data availability

The preprint reports faba bean water-stress phenotyping (imaging, digital biomass, WUE, chlorophyll fluorescence) but no public dataset, images, or analysis code is currently available. The authors state all imaging and numerical data will be deposited in PHIS and that data are available upon request; supplementary xlx

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