The soil-borne pathogen Rhizoctonia solani and the plant parasitic nematode Heterodera schachtii are the most important constraints in sugar beet production worldwide. Symptoms caused by fungal infection are yellowing of leaves and rotting of the beet tuber late in the cropping season. Nematode afflicted plants show stunted growth early in the cropping season and also leaf wilting late in the season when water stress often sets in. Due to the low mobility of soil-borne organisms, they are ideal targets for precision agriculture applications. Sensors which measure the reflectance of plant leaves are, therefore considered to be useful in detecting and discriminating soil-borne disease and pests impacting root health. These high capacity sensors combined with geographic information systems could be used to effectively map the distribution of soil-borne problems in fields. The maps would then define specific management zones for site-specific and variable rate application of plant protection agents. In greenhouse studies, symptom development of each organism alone or in combination was recorded with an imaging hyperspectral line sensor (ImSpector V10) in combination with a mirror scanner twice per week for 56 days. The camera recorded the visible and near infrared within a wavelength of 400 – 1000 nm. Full spectral information for each line image was obtained from the plants. The acquisition of many line images allowed development of a two dimensional spectral image. Symptoms caused by both organisms were detected by hyperspectral image data analysis before visible with the naked eye. Furthermore, disease progress could be discriminated between the organisms alone or when present concomitantly. Symptom development in mixed inoculations was faster and more severe than in single inoculations, indicating complex interactions between the fungus, nematode and plant. The results obtained in this controlled greenhouse study will be used in the future to deliver this sensor technology to the field.