Institut für Pflanzenschutz in Ackerbau und Grünland
Detection of nematode infestations in field crops present a major challenge in agriculture. The patchy distribution, in particular of cyst nematodes, reduces the chances of detection, despite a high effort for soil sampling and extraction. The detection of nematode infestations on asymptomatic host plants by using hyperspectral signatures is therefore a new approach for detecting nematodes and consequently allow for new management options. The goal of this project is therefore to provide the baseline data for the use of hyperspectral signatures to detect the infection by the potato cyst nematode Globodera pallida. In particular, by the recently found new virulence type "Emsland" for which resistant varieties are longer available for control. In the project “Hypall”, new monitoring procedures based on hyperspectral sensor information on different scales will be developed and validated. As this specific host-parasite-system is highly complex and varies greatly over time, including other factors more dominant than the nematode itself, the dynamics on all spatial levels have to be considered. Therefore, all main components have to be part of the detection system including basic research on population, virulence, variety, the initial population problem, as well as technological factors which affect the sensors, as light intensity or reference signatures. All those factors are addressed in the planned lab and glasshouse experiments. Extrapolation to field level is performed with Heterodera schachtii, due to the quarantine status of G. pallida. The main objective of the network research to compose a sensor based management system will be achieved by the combination of all information taken from all network research levels by the use of statistical adaption of analysis protocols and existing population models, both currently available for H. schachtii only. In this way, latent infestations by the new virulent populations of G. pallida, which already show high reproduction rates without causing any visible symptoms, will be detected and the level of the existing virulence assessed. Furthermore, using the data generated in this project, new methods to detect virulent nematode populations and appropriate measures will be developed. This new knowledge will be in support of the responsible plant protection services to preserve production areas by avoiding high levels of population densities and therefore long-term blocking of fields for production of potatoes. Finally, this new knowledge is the basis for extending the use of hyperspectral signatures for the detection of damage by nematodes in further nematode-hostplant combinations.
Federal Ministry of Food and Agriculture
