A - Papers appearing in refereed journals
Jin, X., Zarco-Tejada, P. J., Schmidhalter, U., Reynolds, M. P., Hawkesford, M. J., Varshney, R. V., Yang, T., Nie, C., Li, Z., Ming, B, Xiao, Y, Xie, Y. and Li, S. 2021. High-Throughput Estimation of Crop Traits - A review of ground and aerial phenotyping platforms . IEEE Geoscience and Remote Sensing Magazine. 9 (1), pp. 200-231. https://doi.org/10.1109/MGRS.2020.2998816
Authors | Jin, X., Zarco-Tejada, P. J., Schmidhalter, U., Reynolds, M. P., Hawkesford, M. J., Varshney, R. V., Yang, T., Nie, C., Li, Z., Ming, B, Xiao, Y, Xie, Y. and Li, S. |
---|---|
Abstract | Crop yields need to be improved in a sustainable manner to meet the expected worldwide increase in population over the coming decades as well as the effects of anticipated climate change. Recently, genomics-assisted breeding has become a popular approach to food security; in this regard, the crop breeding community must better link the relationships between the phenotype and the genotype. While high-throughput genotyping is feasible at a low cost, highthroughput crop phenotyping methods and data analytical capacities need to be improved. High-throughput phenotyping offers a powerful way to assess particular phenotypes in large-scale experiments, using high-tech sensors, advanced robotics, and imageprocessing systems to monitor and quantify plants in breeding nurseries and field experiments at multiple scales. In addition, new bioinformatics platforms are able to embrace large-scale, multidimensional phenotypic datasets. Through the combined analysis of phenotyping and genotyping data, environmental responses and gene functions can now be dissected at unprecedented resolution. This will |
Year of Publication | 2021 |
Journal | IEEE Geoscience and Remote Sensing Magazine |
Journal citation | 9 (1), pp. 200-231 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/MGRS.2020.2998816 |
Open access | Published as non-open access |
Funder | Biotechnology and Biological Sciences Research Council |
Department of Environment, Food and Rural Affairs | |
Funder project or code | Designing Future Wheat - WP1 - Increased efficiency and sustainability |
The Wheat Genetic Improvement Network (WGIN3) - Improving the resilience of UK wheat yield and quality through crop genetics and targeted traits analysis | |
Output status | Published |
Publication dates | |
01 Jul 2020 | |
Publisher | Institute of Electrical and Electronics Engineers Inc (IEEE) |
ISSN | 2473-2397 |
Permalink - https://repository.rothamsted.ac.uk/item/9814q/high-throughput-estimation-of-crop-traits-a-review-of-ground-and-aerial-phenotyping-platforms
Publisher's version