Phenotyping of Arabidopsis for drought stress response using kinetic chlorophyll fluorescence imaging

Abstract.

Drought stress is one of the major concerns in global agricultural production. Developing an efficient phenotyping technology can bridge the knowledge gap between the plant phenotype and genotype, which can promote the progress of breeding for drought tolerant accessions and provide economic benefits for the producers and consumers. This research was aimed to investigate the plant phenotyping for drought stress responses of two different genotypes of Arabidopsis using chlorophyll fluorescence imaging. 59 treatment groups (three plants for each group) of each genotype were withholding being watered for 8 days as the drought stress treatment, and the other 59 groups considered as control were regularly watered with 6 ml 1% nutrient solution every day. The kinetic chlorophyll fluorescence images of the drought treatment groups and the control groups were acquired at day 1, 3, 5, 7 and 8 after the drought stress treatment started. The conventional chlorophyll fluorescence parameters and the leaf area index were then extracted from the images. In addition, associated morphological and physiological parameters were also assayed. To construct combinatorial images, the sequential forward selection (SFS) algorithm was used to select the maximum contrast images between two genotypes and the linear discriminant analysis (LDA) was used to build combinatorial images. Finally, combinatorial images were analyzed, indicating combinatorial images are valuable in drought stress studies. Above all, the study showed that AQ and osca1 presented different drought stress responses during the treatment period based on the conventional chlorophyll parameters and combinatorial images.