In recent years, market pressures have reinforced the demand to solve the problem of an increased occurrence of Fusarium head blight (FHB) in cereal production, especially in wheat. The symptoms of this disease are clearly detectable by means of image analysis. This technique can therefore be used to map occurrence and extent of Fusarium infections. From this perspective, a separate harvest in the field can be taken into consideration. Based on the application of chlorophyll fluorescence and hyperspectral imaging, characteristics, requirements and limitations of Fusarium detection on wheat, both in the field and in the laboratory, are discussed. While the modification of spectral signatures due to fungal infection allows its detection by hyperspectral imaging, the decreased physiological activity of tissues resulting from Fusarium impacts provides the base for CFI analyses. In addition, the two methods are compared in view of their usability for the detection of Fusarium, and different approaches for data analysis are presented.

Head blight on wheat, caused by Fusarium spp., is a serious problem for both farmers and food production due to the concomitant production of highly toxic mycotoxins in infected cereals. For selective mycotoxin analyses, information about the on-field status of infestation would be helpful. Early symptom detection directly on ears, together with the corresponding geographic position, would be important for selective harvesting. Hence, the capabilities of various digital imaging methods to detect head blight disease on winter wheat were tested. Time series of images of healthy and artificially Fusarium-infected ears were recorded with a laboratory hyperspectral imaging system (wavelength range: 400 nm to 1,000 nm). Disease-specific spectral signatures were evaluated with an imaging software. Applying the ‘Spectral Angle Mapper’ method, healthy and infected ear tissue could be clearly classified. Simultaneously, chlorophyll fluorescence imaging of healthy and infected ears, and visual rating of the severity of disease was performed. Between six and eleven days after artificial inoculation, photosynthetic efficiency of infected compared to healthy ears decreased. The severity of disease highly correlated with photosynthetic efficiency. Above an infection limit of 5% severity of disease, chlorophyll fluorescence imaging reliably recognised infected ears. With this technique, differentiation of the severity of disease was successful in steps of 10%. Depending on the quality of chosen regions of interests, hyperspectral imaging readily detects head blight 7 d after inoculation up to a severity of disease of 50%. After beginning of ripening, healthy and diseased ears were hardly distinguishable with the evaluated methods.

New regulations for critical values of the Fusarium toxins in cereals and cereal products have been implemented in the European Union since 2005. For selective mycotoxin analyses of cereals information about the status of infestation in the field would be helpful. Therefore, early detection of disease symptoms directly on the ears together with the corresponding geographic position will become highly important for selective harvest. In this project various digital imaging methods were tested for their ability to detect head blight disease on winter wheat. For hyperspectral imaging a laboratory system was developed. Time series of images of healthy and artificially Fusariuminfected ears were recorded within the wavelength range of 400 nm to 1000 nm. The image analysis software ENVI was applied to define disease specific spectral signatures. Applying ‘Spectral Angle Mapper’ as an appropriate method for classification healthy and diseased ear tissue could be clearly distinguished. Simultaneous to hyperspectral imaging chlorophyll fluorescence imaging of healthy and Fusarium-infected ears, and visual rating of the degree of infection was performed. Using the FluorCam 690 MF the photosynthetic efficiency was measured to determine the effect of disease on photosynthesis. A decrease of photosynthetic efficiency of diseased compared to healthy ears was observed between six and eleven days after artificial inoculation. The severity of disease symptoms was correlated with the photosynthetic efficiency. Chlorophyll image analysis reliably detects diseased ears at a limit of 5%. A differentiation of 10% steps up to 10% severity of disease degree succeeded. Hyperspectral image analyses very exactly detect head blight after 7 days after inoculation up to a degree of disease of 50%. The result strongly depends on the quality of chosen region of interests (ROI). From the beginning of ripening (growth stage 81) the possibility to distinguish between healthy and diseased ears is very limited with the evaluated methods.