The INVITE project aims to promote the introduction of new varieties resistant to biotic and abiotic stresses, adapted to sustainable management practices and exhibiting good resource use efficiency, due to the improvement of variety assessment tools and a better information to farmers on the performance of varieties under various production conditions. This has been illustrated on the main cultivated species which cover different modes of propagation, various uses in food and animal feed and which show a significant breeding activity in the EU.
The CRA-W was involved on different operational objectives. One of the objectives was the development of new phenotyping tools in both the visible and non visible regions, to provide indicators of adaptation to stress and to improve the speed, precision and efficiency of observations when assessing varieties. To achieve this goal, the CRA-W teams have worked to determine on-site the properties of different varieties of wheat and apple using handheld and imaging instruments, visible and near infrared, for ground measurements. The evaluation trials on cereal varieties as well as the collections of apple genetic resources were used as support for this research. In particular, various optical sensors were evaluated to study the quality of apples in orchards, to measure the length of organs (stem, internodes, ear) of wheat plants, to count the number of orange blossom midge larvae extracted from wheat ears, to evaluate the susceptibility to fusarium head blight disease of winter wheat varieties in the laboratory and in the field, as shown in the following figures. Another goal was to work on historical data to predict the performance of a variety depending on environmental growing conditions and farming practices.
Figure 1 : Acquisition of spectral data on apples using a laboratory spectrometer or a portable spectrometer and calibration results for 4 quality parameters: dry matter, brix, acidity and total polyphenols.
Figure 2: Measuring the length of organs (stem, internodes, ear) of wheat plants from RGB images.
Figure 3: Counting of cecidomyia larvae, extracted from wheat ears, from RGB images
Figure 4: Acquisition and processing of hyperspectral images of wheat ears in the laboratory in order to assess the % of Fusarium contamination per ear.
Figure 5: Acquisition and processing of hyperspectral images of wheat ears in the field in order to assess the % of Fusarium contamination per plot.
