RESUMO
Image-based phenotyping is a non-invasive method that permits the dynamic evaluation of plant features during growth, which is especially important for understanding plant adaptation and temporal dynamics of responses to environmental cues such as water deficit or drought. The aim of the present study was to use high-throughput imaging in order to assess the variation and dynamics of growth and development during drought in a spring barley population and to investigate associations between traits measured in time and yield-related traits measured after harvesting. Plant material covered recombinant inbred line population derived from a cross between European and Syrian cultivars. After placing the plants on the platform (28th day after sowing), drought stress was applied for 2 weeks. Top and side cameras were used to capture images daily that covered the visible range of the light spectrum, fluorescence signals, and the near infrared spectrum. The image processing provided 376 traits that were subjected to analysis. After 32 days of image phenotyping, the plants were cultivated in the greenhouse under optimal watering conditions until ripening, when several architecture and yield-related traits were measured. The applied data analysis approach, based on the clustering of image-derived traits into groups according to time profiles of statistical and genetic parameters, permitted to select traits representative for inference from the experiment. In particular, drought effects for 27 traits related to convex hull geometry, texture, proportion of brown pixels and chlorophyll intensity were found to be highly correlated with drought effects for spike traits and thousand grain weight.