Multi-facility, high-temporal-resolution phenomics of growth-defence allocation responses in potato
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Updated: Nov 9, 2026

High Throughput Image-Based Phenotyping for Determining Morphological and Physiological Responses to Single and Combined Stresses in Potato
Published on: June 7, 2024
Sylvain Poque1,2, Murilo A Sandroni3, Pedro Garcia-Caparros4
1Department of Agricultural Sciences, University of Helsinki, Finland.
Abstract:
Understanding how plants allocate resources between growth and defence is a fundamental question in plant biology. Such allocation responses are often subtle, requiring precise measurement tools and comparative experimental designs to detect. In this study, a high-throughput phenomics framework with daily monitoring was deployed at two independent facilities to assess growth, morphology, and physiology of Solanum tuberosum cv. Désirée and six transgenic lines under pathogen-free conditions. Plants treated with resistance-inducing compounds β-aminobutyric acid (BABA) or potassium phosphite (KPhi), alongside lines carrying single Rpi genes (R2A, blb1), a three-gene stack (3R1, 3R2), or RNAi knockdown of the jasmonate co-receptor StCOI1 (coi1H1, coi1X5), were phenotyped to compare the allocation responses of resistance inducers and genetically encoded resistance. Over four weeks, image-derived traits revealed consistent effects across both facilities: BABA increased plant height and elevated the greenness index, whereas KPhi imposed no consistent change in growth; StCOI1-silenced lines gained in height. Endpoint enzyme profiling revealed that BABA and KPhi engaged distinct enzyme classes within each facility, with KPhi consistently imposing a lower apparent growth cost; StCOI1-silenced lines showed facility-dependent enzyme configurations despite a consistent height phenotype; however, the specific enzyme signatures were not conserved across facilities, indicating that cross-facility enzyme phenotyping requires explicit characterisation of the local metabolic baseline. Overall, high-throughput phenomics resolved subtle, resistance-associated allocation responses across platforms, showing that BABA and KPhi were associated with distinct endpoint enzyme signatures in a given environment, with KPhi's lower cost conserved across environments but signature identity shaped jointly by treatment and environment.

