Use of imaging spectroscopy to discriminate symptoms caused by Heterodera schachtii and Rhizoctonia solani on sugar beet

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.

Recent advances in sensing plant diseases for precision crop protection

“…Bravo et al (2003) used in-field spectral images for an early detection of yellow rust infecting wheat, Hillnhütter et al (2011b) successfully discriminated symptoms caused by H. schachtii and Rhizoctonia solani on sugar beet. At the present time, hyperspectral imaging is more widespread in the field of monitoring fruit security and quality.…”

Synergistic damage by interactions between Ditylenchus dipsaci and Rhizoctonia solani (AG 2–2IIIB) on sugar beet

“…The NDVI was sensitive to differences between treatments, which suggest that it is suitable as an indicator for disease development (Hillnhütter et al 2011a). NDVI was strongly correlated with the aboveground RCRR-rating.…”

“…The authors expect hyperspectral leaf reflectance to be a means of non-destructive detection of either symptoms caused by one organism alone or both together, as reported for H. schachtii-R. solani disease complex (Hillnhütter et al 2010(Hillnhütter et al , 2011a.…”

“…Hyperspectral reflectance assessment is a useful method to detect infections by pathogens in sugar beet (Hillnhütter et al 2011a). Recent developments in optical sensor technology have the potential to enable direct detection of diseases under greenhouse and field conditions.…”

Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium spec. Infections on Wheat

“…The involvement of several hundreds of wavelengths in image analysis may provide the prerequisite for high accuracy of detection, and, thus, makes a meaningful monitoring of maturation, quality or diseases possible at all [58,[89][90][91][92]. Nevertheless, with currently applied standard techniques such as conventional line scanners, recording of hyperspectral images is rather slow [45,58,74]. In addition, pre-processing, processing and analyses of the enormous amount of data are, still, laborious and time consuming and, thus, retarding infection evaluation.…”