Project Details
Description
This project aims to develop remote sensing tools for non‐destructive high‐throughput phenotyping of potato crops and to use the tools to identify key canopy characteristics associated with increased nitrogen (N) use efficiency and potato yield.
A low‐altitude drone equipped with high resolution RGB and multispectral imaging capability will be used to provide images of potato canopy at several key growth stages in a purposely designed potato trial hosted at The Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences.
Researchers from NIAB and Aberystwyth University will develop image analysis software to phenotype canopy traits and to establish association of these traits with N use efficiency and yield.
The proposed remote sensing technique will provide an efficient phenotyping method to predict crop production potential, bridging the genotype‐phenotype gap.
The tool will benefit breeders by allowing accurate and efficient selection of promising genotypes to breed varieties with increased N use efficiency and crop productivity. Moreover, it will enable potato growers to monitor crop growth dynamically, enabling application of crop husbandry at correct times.
A low‐altitude drone equipped with high resolution RGB and multispectral imaging capability will be used to provide images of potato canopy at several key growth stages in a purposely designed potato trial hosted at The Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences.
Researchers from NIAB and Aberystwyth University will develop image analysis software to phenotype canopy traits and to establish association of these traits with N use efficiency and yield.
The proposed remote sensing technique will provide an efficient phenotyping method to predict crop production potential, bridging the genotype‐phenotype gap.
The tool will benefit breeders by allowing accurate and efficient selection of promising genotypes to breed varieties with increased N use efficiency and crop productivity. Moreover, it will enable potato growers to monitor crop growth dynamically, enabling application of crop husbandry at correct times.
| Status | Finished |
|---|---|
| Effective start/end date | 01 May 2018 → 31 Mar 2019 |
Funding
- Science and Technology Facilities Council (Funder reference unknown): £6,604.00
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