Natural Variation among Arabidopsis Accessions in the Regulation of Flavonoid Metabolism and Stress Gene Expression by Combined UV Radiation and Cold.

Plants are constantly exposed to stressful environmental conditions. Plant stress reactions were mainly investigated for single stress factors. However, under natural conditions plants may be simultaneously exposed to different stresses. Responses to combined stresses cannot be predicted from the reactions to the single stresses. Flavonoids accumulate in Arabidopsis thaliana during exposure to UV-A, UV-B or cold, but the interactions of these factors on flavonoid biosynthesis were unknown. We therefore investigated the interaction of UV radiation and cold in regulating the expression of well-characterized stress-regulated genes, and on transcripts and metabolites of the flavonoid biosynthetic pathway in 52 natural Arabidopsis accessions that differ widely in their freezing tolerance. The data revealed interactions of cold and UV on the regulation of stress-related and flavonoid biosynthesis genes, and on flavonoid composition. In many cases, plant reactions to a combination of cold and UV were unique under combined stress and not predictable from the responses to the single stresses. Strikingly, all correlations between expression levels of flavonoid biosynthesis genes and flavonol levels were abolished by UV-B exposure. Similarly, correlations between transcript levels of flavonoid biosynthesis genes or flavonoid contents, and freezing tolerance were lost in the presence of UV radiation, while correlations with the expression levels of cold-regulated genes largely persisted. This may indicate different molecular cold acclimation responses in the presence or absence of UV radiation.

A segmentation procedure using colour features applied to images of Arabidopsis thaliana.

In studies of environmental effects on plant growth, the images of plants are often used for non-destructive measurements in phenotyping. In this work, a computational procedure has been developed to segment images of plants allowing an improved separation of plants and other types of objects in the frame such as moss or soil. The proposed procedure is based on colour analysis and image morphology. The red-green-blue (RGB) values are transformed into a colour space as ratios of R, G and B vs the sum of R, G, and B channels. We introduce an approach to render the training set of pixels on a Microsoft Excel two-dimensional graph and a technique to determine the discriminant regions of pixel classes. Two approaches for the classification based on colour analysis are shown: an automatic method using support vector machines and a procedure based on visual inspection. The segmentation procedure is designed to classify more than two object types utilising flexibly curved boundaries of discriminant regions that can also be non-convex. We propose a machine-vision algorithm to detect plant features - leaf anthocyanin accumulation and trichomes. The procedures of segmentation and feature detection are applied to images of Arabidopsis thaliana (L.) Heynh. that grow under either normal or drought stress conditions.