Abstract
The autofluorescence of a sample is a highly sensitive and selective optical property and gives the possibility to establish non-destructive techniques of the investigation of plants, like detecting the chlorophyll fluorescence related to stress phenomena. In this study, an advanced multi-color fluorescence imaging system and data analysis were presented. The advantage of an imaging system is the additional receiving of spatial information over a sample area, this is a strong improvement compared to spot measurements commonly used. The purpose was to demonstrate the possibility of the detection and characterization of stress symptoms using this system. Specific fluorescence ratios were identified to characterize the stress status over the whole leaf, here shown on barley grown under different nitrogen supply (abiotic stress). Due to the changes, it is possible to make conclusions about leaf pigments (chlorophylls and phenolics) related to stress response. The second aim was to use the shape of local symptoms (biotic stress) as a criterion. For this purpose, three structural different kinds of fungal symptoms were analyzed using shape descriptors. It shows that an additional image shape analysis can be very useful for extracting further information, in this case the successful discrimination of fungal infections.
Highlights
The measurement of fluorescence gives the possibility for highly accurate and sensitive non-destructive detection method of specific fluorescence dyes.Fluorescence represents a part of the energy taken up by light absorption of the fluorescence dye
One example is the re-absorption of chlorophyll fluorescence caused by the overlapping of the fluorescence emission spectrum with the absorption spectrum of the leaf pigments located on the way of fluorescence signal to the leaf surface [9]
In order to make use of the full spatial information of an image related to a biological issue, here for stress detection, the processing should be complemented by a detailed image analysis using the appropriate software application
Summary
The measurement of fluorescence gives the possibility for highly accurate and sensitive non-destructive detection method of specific fluorescence dyes (for a general description see e.g., [1]). The fluorescence emitted from plant material is a complex signal and can be influenced by the penetration of the excitation light, the re-absorption of the fluorescence on its way to the sample surface, and—in case of chlorophyll fluorescence—energy transfer processes and photosynthetic activity. This gives room for specific detection of sample characteristics and changes of plant material caused by diseases or abiotic stresses. A detailed image analysis with the selection of relevant regions of interest (fungal infection) was demonstrated, and the use of shape descriptors made it possible to discriminate different types of symptoms depending on the shape
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