High-Throughput Estimation of Crop Traits - A review of ground and aerial phenotyping platforms

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. 2020. High-Throughput Estimation of Crop Traits - A review of ground and aerial phenotyping platforms . IEEE Geoscience and Remote Sensing Magazine. https://doi.org/10.1109/MGRS.2020.2998816

AuthorsJin, 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
aid in finding solutions to currently limited and incremental improvements in crop yields.

Year of Publication2020
JournalIEEE Geoscience and Remote Sensing Magazine
Digital Object Identifier (DOI)https://doi.org/10.1109/MGRS.2020.2998816
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Department of Environment, Food and Rural Affairs
Funder project or codeDesigning 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 statusPublished
Publication dates
Print01 Jul 2020
PublisherInstitute of Electrical and Electronics Engineers Inc (IEEE)
ISSN2473-2397

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