We use cookies on our website. Some are necessary for the operation of the website. You can also allow cookies for statistical purposes. You can adjust the data protection settings or agree to all cookies directly.
Collaborative project: Prognosis and detection of fungal diseases in viticulture by fine-meshed microclimate assessment and application of imaging techniques - subproject 3 (FungiSens)
Project
Project code: 281B204916
Contract period: 01.09.2018
- 31.08.2021
Budget: 60,618 Euro
Purpose of research: Applied research
Keywords: viticulture (winery), agricultural engineering, digital world, sustainability, forecast, resource protection, resource efficiency, vine
Affected by climate change, the occurrence of pests and fungal diseases is also increasing in the wine growing areas of Germany. Above all, Peronospora can cause severe profit cuts, if not detected and treated in time. Crop protection treatment usually is scheduled with protective or curative strategies, following a positive indication of an infection. However, common planning methods are either imprecise, expensive, labor intensive or only applicable after an infestation has occurred. In the recent years, prognostic models, estimating fungal infestations based on weather data were generally accepted. However, the meaning of those models is limited by the restricted spatial availability of meteorological data and does only allow a general prognosis for a radius of multiple kilometers. Installation of multiple micro sensors directly in the rows of a vineyard does allow acquisition of the microclimate at multiple positions and thus can increase the precision of prognostic models in such a dimension, that crop protection can be scheduled for smaller scales, such as the vineyard or even the single vine level. By supplementary application of infra-red and hyperspectral imaging techniques, stress related physiological reactions of fungal infestations can be detected fast and for larger areas, which does allow a validation of the micro sensor based prognostic models. Also, unknown coherences can be detected and robust correlations for the prognostic models can be created by a combination of both methods.
Section overview
Subjects
- Crop Protection
- Viticulture
Framework programme
Funding programme
Excutive institution
State Research Institute for Viticulture & Pomiculture (LVWO)
Funding institution
Project management agencies
Associated projects: FungiSens
- Collaborative project: Prognosis and detection of fungal diseases in viticulture by fine-meshed microclimate assessment and application of imaging techniques - subproject 1
- Collaborative project: Prognosis and detection of fungal diseases in viticulture by fine-meshed microclimate assessment and application of imaging techniques - subproject 2
- Collaborative project: Prognosis and detection of fungal diseases in viticulture by fine-meshed microclimate assessment and application of imaging techniques - subproject 4