For the Beetphen project, various sensors were tested by CRA-W and VITO, both on the ground and in the air, on the trials inoculated and set up by SES-VANDERHAVE, in order to assess the susceptibility to powdery mildew of sugar beet varieties.
The assessment of stress associated with a disease such as powdery mildew is conventionally carried out by experts specially trained for this task. They make visual observations using a rating scale to identify and quantify the presence of the disease. This type of assessment can be time-consuming and requires repeating observations throughout the growing season. This assessment is also highly dependent on human interpretation and can be influenced by weather conditions.
A first step towards more objective and efficient phenotyping is to perform measurements on the ground using portable fluorimetry and spectroscopy instruments. The fluorimeter provides measurements of chlorophyll fluorescence which can detect factors that affect photosynthetic activity. These measurements can reveal the presence of powdery mildew before symptoms appear to the naked eye. The spectrometer provides reflectance measurements in visible and near-infrared wavelength ranges that can detect variations in leaf colour and composition. The models developed on these spectral data made it possible to define two groups of infection. Although having many advantages compared to the traditional method, these measurements on the ground still take a long time and depend on the conditions of access to the land. These measurements can, however, be performed with better accuracy in greenhouses where conditions are controlled, using these portable instruments or hyperspectral imaging cameras mounted on ground platforms. Using these technologies, 3 to 4 groups of powdery mildew susceptibility can be identified.
In order to further improve the efficiency of phenotyping, drones have been equipped with spectral sensors for the quantitative evaluation of foliar diseases in experimental plots. This approach makes it possible to acquire information with a very high spatial resolution and a very flexible temporal resolution. In parallel with the multispectral approach, high-resolution hyperspectral remote sensing imagery was tested. This has been found to be more suitable for producing spectral indices related to crop health. It allows two groups of infection to be defined. Compared to the traditional method or to field measurements, image captures are faster and the measurements are more precise and homogeneous.
These new spectral phenotyping tools tested by researchers aim to bring new indicators into breeding programmes and help create the varieties of tomorrow that are more resistant to biotic stresses.