Can models based on phylogeny be used to predict radionuclide activity concentrations in crops?
Beresford, N.A.; Barnett, C.L. 
ORCID: https://orcid.org/0000-0001-9723-7247; Guillén, J..
2020
Can models based on phylogeny be used to predict radionuclide activity concentrations in crops?
Journal of Environmental Radioactivity, 218, 106263.
9, pp.
10.1016/j.jenvrad.2020.106263
Abstract/Summary
The modelling of transfer of radionuclides from soils to plants generally relies upon empirical soil-plant concentration ratios. Concentration ratios are often highly uncertain and are not available for many plant-radionuclide combinations. A number of papers published over the last 20 years have suggested that phylogenetic models could be used to make predictions of the radionuclide transfer to plants. Such a modelling approach would have the advantage that site factors (typically related to soils) are taken into account. For the first time we have compared predictions of Cs and Sr transfer to a range of crops grown on different soils. Predictions for both elements were generally acceptable (within an order of magnitude of observed data) but Sr concentrations were over predicted in fruits and tubers. This over prediction of Sr concentrations is likely to be because the phylogenetic models were fitted to data for green shoots. We conclude that phylogenetic models offer a number of advantages, but that they must be validated and, in future, parametrisation datasets need to include data on concentrations in edible plant parts and not just green shoots.
| Item Type: | Publication - Article |
|---|---|
| Digital Object Identifier (DOI): | 10.1016/j.jenvrad.2020.106263 |
| UKCEH and CEH Sections/Science Areas: | Pollution (Science Area 2017-) |
| ISSN: | 0265-931X |
| Additional Keywords: | radioecology |
| NORA Subject Terms: | Agriculture and Soil Science Botany |
| Date made live: | 16 Apr 2020 13:56 +0 (UTC) |
| URI: | https://nora.nerc.ac.uk/id/eprint/527404 |
Actions (login required)
 |
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year
Tools
Tools
