“…1, Birkle et al (1965)(Experiment a); 2, Andersen (1967); 3, Andersson and Lonsjo (1988); 4, Antonopoulos‐Domis et al (1990a); 5, Antonopoulos‐Domis et al (1990b); 6, Birkle et al (1965)(Experiment b); 7, Broadley and Willey (1997); 8, Buysse et al (1996); 9, Cline and Rickard (1972); 10, Clooth and Aumann (1990); 11, Colgan et al (1990); 12, Collander (1941); 13, Coughtrey et al (1989); 14, Demirel et al (1994); 15, Dushenkov et al (1999); 16, Evans and Dekker (1968); 17, Gouthu et al (1997); 18, Henrich et al (1990); 19, Horrill et al (1990); 20, Lasat et al (1997); 21, Lasat et al (1998); 22, Experimental Dataset 1; 23, Papanicolaou et al (1990); 24, Salt and Mayes (1991); 25, Salt et al (1992); 26, Salt and Mayes (1993); 27, Salt and Mayes (1990); 28, Skarlou et al (1999); 29, Tang and Wang (2002); 30, Tang and Willey (2003); 31, Experimental Dataset 2; 32, Experimental Dataset 3; 33, Tikhomirov et al (1981); 34, Experimental Dataset 4; 35, Experimental Dataset 5.…”
For (134/137)Cs, and many other soil contaminants, research into transfer to plants has focused on particular crops and phytoremediation candidates, producing uptake data for a small proportion of all plant taxa. Despite the significance of differences in uptake between plant taxa, the capacity of soil-to-plant transfer models to predict them is currently confined to those taxa for which data exist, there being no method to predict uptake by other taxa. We used residual maximum likelihood (REML) analysis on data from experiments (including 89 plant taxa from China plus 32 phytoremediation candidates) together with data from the literature, to construct a database of relative (134/137)Cs concentrations in 273 plant taxa. The REML (134/137)Cs concentrations in plants are not normally distributed but significantly clustered. Analysis of variance (ANOVA), coded with a recent ordinal phylogeny for flowering plants, showed that plant taxa do not behave independently for (134/137)Cs concentration because 42 and 15% of inter-taxa differences are associated with phylogeny above the species and ordinal level, respectively. In general, Eudicots, and especially the Caryophyllales, Asterales, and Brassicales, have high (134/137)Cs concentrations, while the Fabales and Magnoliids, in particular Poales, have low (134/137)Cs concentrations. Plants of the stress-tolerant ruderal (S-R) growth strategy sensu Grime have, in general, high concentrations of Cs, while those of the competitive (C) and generalist (C-S-R) strategies have low concentrations, although these effects are less pronounced than those of phylogeny. Plant phylogeny and growth strategy might thus be used to predict a significant portion of inter-taxa differences in plant uptake of (134/137)Cs.
“…1, Birkle et al (1965)(Experiment a); 2, Andersen (1967); 3, Andersson and Lonsjo (1988); 4, Antonopoulos‐Domis et al (1990a); 5, Antonopoulos‐Domis et al (1990b); 6, Birkle et al (1965)(Experiment b); 7, Broadley and Willey (1997); 8, Buysse et al (1996); 9, Cline and Rickard (1972); 10, Clooth and Aumann (1990); 11, Colgan et al (1990); 12, Collander (1941); 13, Coughtrey et al (1989); 14, Demirel et al (1994); 15, Dushenkov et al (1999); 16, Evans and Dekker (1968); 17, Gouthu et al (1997); 18, Henrich et al (1990); 19, Horrill et al (1990); 20, Lasat et al (1997); 21, Lasat et al (1998); 22, Experimental Dataset 1; 23, Papanicolaou et al (1990); 24, Salt and Mayes (1991); 25, Salt et al (1992); 26, Salt and Mayes (1993); 27, Salt and Mayes (1990); 28, Skarlou et al (1999); 29, Tang and Wang (2002); 30, Tang and Willey (2003); 31, Experimental Dataset 2; 32, Experimental Dataset 3; 33, Tikhomirov et al (1981); 34, Experimental Dataset 4; 35, Experimental Dataset 5.…”
For (134/137)Cs, and many other soil contaminants, research into transfer to plants has focused on particular crops and phytoremediation candidates, producing uptake data for a small proportion of all plant taxa. Despite the significance of differences in uptake between plant taxa, the capacity of soil-to-plant transfer models to predict them is currently confined to those taxa for which data exist, there being no method to predict uptake by other taxa. We used residual maximum likelihood (REML) analysis on data from experiments (including 89 plant taxa from China plus 32 phytoremediation candidates) together with data from the literature, to construct a database of relative (134/137)Cs concentrations in 273 plant taxa. The REML (134/137)Cs concentrations in plants are not normally distributed but significantly clustered. Analysis of variance (ANOVA), coded with a recent ordinal phylogeny for flowering plants, showed that plant taxa do not behave independently for (134/137)Cs concentration because 42 and 15% of inter-taxa differences are associated with phylogeny above the species and ordinal level, respectively. In general, Eudicots, and especially the Caryophyllales, Asterales, and Brassicales, have high (134/137)Cs concentrations, while the Fabales and Magnoliids, in particular Poales, have low (134/137)Cs concentrations. Plants of the stress-tolerant ruderal (S-R) growth strategy sensu Grime have, in general, high concentrations of Cs, while those of the competitive (C) and generalist (C-S-R) strategies have low concentrations, although these effects are less pronounced than those of phylogeny. Plant phylogeny and growth strategy might thus be used to predict a significant portion of inter-taxa differences in plant uptake of (134/137)Cs.
Under the International Atomic Energy Agency (IAEA) MODARIA (Modelling and Data for Radiological Impact Assessments) Programme, there has been an initiative to improve the derivation, provenance and transparency of transfer parameter values for radionuclides from feed to animal products that are for human consumption. A description of the revised MODARIA 2016 cow milk dataset is described in this paper. As previously reported for the MODARIA goat milk dataset, quality control has led to the discounting of some references used in IAEA's Technical Report Series (TRS) report 472 (IAEA, 2010). The number of Concentration Ratio (CR) values has been considerably increased by (i) the inclusion of more literature from agricultural studies which particularly enhanced the stable isotope data of both CR and F and (ii) by estimating dry matter intake from assumed liveweight. In TRS 472, the data for cow milk were 714 transfer coefficient (F) values and 254 CR values describing 31 elements and 26 elements respectively. In the MODARIA 2016 cow milk dataset, F and CR values are now reported for 43 elements based upon 825 data values for F and 824 for CR. The MODARIA 2016 cow milk dataset F values are within an order of magnitude of those reported in TRS 472. Slightly bigger changes are seen in the CR values, but the increase in size of the dataset creates greater confidence in them. Data gaps that still remain are identified for elements with isotopes relevant to radiation protection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.