Networking sensor technology R&D for crop breeding and management
Plant breeding and production face new challenges in the 21st century. These challenges include rapidly increasing demand for food by a growing world population, changing dietary needs, the use of biomass as an energy source, and global changes including climate change.
Crop research and crop breeding need to provide both qualitative and quantitative improvements in the quality of and production conditions for crops within a relatively short time in order to raise productivity on the limited available land. Primary crop production must be the key technology for a knowledge based bioeconomy to ensure resource resilience, yield security and yield stability.
Assessment and identification of phenotypes is currently a bottle neck in plant breeding. This bottle neck needs to be opened to keep pace with advances in genotyping and to enable increased precision in crop management, optimise the use of agricultural imputs and conserve adjoining ecosystems. Significant steps to improve efficiency are the development and use of non-invasive methods for qualitative and quantitative assessment of plant characteristics in breeding and the improvement of primary plant production.
The rapid development of non-destructive sensors and robotics, and the ability to analyse complex data sets, offers new opportunities for detection of external characteristics (morphology and growth dynamics) and internal characteristics (biochemical, physiological and genetic) of individual plants and populations. Furthermore, it is planned to combine data from different sensors.
Combination of phenotypic and genotypic information can be reliably and objectively recorded and documented represents a significant advance in plant breeding.
- Collect traits and properties in individual plants under high throughput conditions (high throughput screening) and for mechanistic analysis (Deep phenotyping)
- New development apply sensors at optimal spatial and temporal resolution
- Advance the evaluation of complex data sets from non-destructive measurements from individual plants and plant populations
- Combine data and results from high-throughput genetic, metabolic and proteomic methodologies to understand the emerging complex, multi-causal properties (e.g. yield, quality, resistance, tolerance) and as a basis for significant acceleration of breeding successfully adapted crops
- Apply sensory techniques for high-resolution temporal and spatial control of plant stocks, taking into account site conditions and soil variability with the aim of increasing yields, assurance, quality improvement and providing sustainable land management under reduced resource use.