Hyperspectral imaging (HSI) offers high potential as a non-invasive diagnostic tool for disease detection. In this paper leaf characteristics and spectral reflectance of sugar beet leaves diseased with Cercospora leaf spot, powdery mildew and leaf rust at different development stages were connected. Light microscopy was used to describe the morphological changes in the host tissue due to pathogen colonisation. Under controlled conditions a hyperspectral imaging line scanning spectrometer (ImSpector V10E) with a spectral resolution of 2.8 nm from 400 to 1000 nm and a spatial resolution of 0.19 mm was used for continuous screening and monitoring of disease symptoms during pathogenesis. A pixel-wise mapping of spectral reflectance in the visible and near-infrared range enabled the detection and detailed description of diseased tissue on the leaf level. Leaf structure was linked to leaf spectral reflectance patterns. Depending on the interaction with the host tissue, the pathogens caused disease-specific spectral signatures. The influence of the pathogens on leaf reflectance was a function of the developmental stage of the disease and of the subarea of the symptoms. Spectral reflectance in combination with Spectral Angle Mapper classification allowed for the differentiation of mature symptoms into zones displaying all ontogenetic stages from young to mature symptoms. Due to a pixel-wise extraction of pure spectral signatures a better understanding of changes in leaf reflectance caused by plant diseases was achieved using HSI. This technology considerably improves the sensitivity and specificity of hyperspectrometry in proximal sensing of plant diseases.

No abstract

Diseases caused by nematodes and non-sporulating soil-borne fungi have low mobility and are likely to be suitable targets for precision agriculture applications. Sensors which assess the reflectance of plant leaves may be useful tools to detect soil-borne pathogens. The development of symptoms caused by the plant parasitic nematode Heterodera schachtii and the fungal pathogen Rhizoctonia solani anastomosis group 2-2IIIB alone or in combination was studied by leaf reflectance recorded with a hyperspectral imaging system (range 400-1000 nm) for 9 weeks twice per week. Three image processing methods were tested for their suitability to generate the most sensitive spectral information for disease detection. Nine spectral vegetation indices were calculated from spectra to correlate them to leaf symptom recordings. Supervised classification by spectral angle mapper was tested for the discrimination of leaf symptoms caused by the diseases. The symptoms of Rhizoctonia crown and root rot caused by R. solani and symptoms caused by H. schachtii induced modifications that could be detected by hyperspectral image analysis. Rhizoctonia crown and root rot symptom development in mixed inoculations was faster and more severe than in single inoculations, indicating complex interactions among fungus, nematode and plant. The results from this study under controlled conditions are currently used to transfer the sensor technology to the field.

Belowground symptoms of sugar beet caused by the beet cyst nematode (BCN) Heterodera schachtii include the development of compensatory secondary roots and beet deformity, which, thus far, could only be assessed by destructively removing the entire root systems from the soil. Similarly, the symptoms of Rhizoctonia crown and root rot (RCRR) caused by infections of the soil-borne basidiomycete Rhizoctonia solani require the same invasive approach for identification. Here nuclear magnetic resonance imaging (MRI) was used for the non-invasive detection of belowground symptoms caused by BCN and/or RCRR on sugar beet. Excessive lateral root development and beet deformation of plants infected by BCN was obvious 28 days after inoculation (dai) on MRI images when compared with non-infected plants. Three-dimensional images recorded at 56 dai showed BCN cysts attached to the roots in the soil. RCRR was visualized by a lower intensity of the MRI signal at sites where rotting occurred. The disease complex of both organisms together resulted in RCRR development at the site of nematode penetration. Damage analysis of sugar beet plants inoculated with both pathogens indicated a synergistic relationship, which may result from direct and indirect interactions. Nuclear MRI of plants may provide valuable, new insight into the development of pathogens infecting plants below- and aboveground because of its non-destructive nature and the sufficiently high spatial resolution of the method.

The aim of this study was to investigate interactions between Ditylenchus dipsaci and Rhizoctonia solani. Both pathogens are known to cause problems in the primary sugar beet production areas in Germany. Furthermore, the organisms' ecological niches in the soil and on the beet overlap. Hence, it is probable that these parasites interact and have a deleterious synergistic impact on sugar beet production. The stem and bulb nematode, D. dipsaci, is a migratory endoparasite that penetrates the sugar beet seedling during the spring when temperatures are low. The main symptoms include distorted, bloated petioles and leaves. The fungus causing Rhizoctonia crown and root rot, R. solani, enters the plant at the beet-leaf transition zone. Synergistic damage was obtained when both organisms occurred on the same plant. Hyperspectral leaf reflectance data was used to calculate a vegetation index, the Normalised Difference Vegetation Index (NDVI), which could successfully be used to discriminate between growth reduction caused by R. solani and by dual inoculation (disease complex). High correlations were observed between ratings of disease symptoms and the vegetation index over a time series of seven weeks.