CROP.SENSe.Net: Interdisciplinary Competence Network for Phenotyping Science in Plant Breeding and Crop Management

CROP.SENSe.net is a German competence network for phenotyping and sensor development for plant breeding and precision farming, funded by the German Ministry of Science and Education (BMBF). It started in 2010 and is addressing a number of topics:

• Early identification of traits determining yield and yield potential, biotic and abiotic stress, crop quality
• High accuracy of early trait prediction from sensor data

• Ascertain phenotype from interactions between genotype and environment
• Predict performance of genotypes under different environmental conditions using quantitative models
• Using advanced methods of data mining

It is focusing on robustness, coping with complexity and trying to achieve greater precision in phenotyping. It includes groups working on rapid “on the run” soil assessment and plant data, working with “model species” sugar beet and barley, in selected cases as well with grape vine.

Significant improvements have been achieved e.g. with soil data evaluation where considering surface roughness significantly improved signal to noise ratios. Hyperspectral evaluation (imaging and spectral analysis) helps to assess and identify early fungal infections as well as initial phases of abiotic stresses before the onset of macroscopically visible symptoms. A new THz sensor is reliably able to follow changes in tissue water contents at a resolution comparable to gravimetric measurements.

The reconstitution of volume and shape information from laser point data may help to identify main components of shape variation and could be developed in the future for even automated recognition of characteristic shapes. Further examples of recent research will be presented.