Fruit Tree model for uptake of organic compounds from soil and air†

Trapp, Stefan

doi:10.1080/10629360701303693

Cited by 145 publications

(141 citation statements)

References 28 publications

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“…More recently, Dettenmaier et al [9] presented an empirical relationship between TSCF and log K OW that indicates that non-ionizable, polar, highly watersoluble organic compounds are most likely to be taken up by plant roots and translocated to shoot tissue. Highly watersoluble compounds were also predicted to be the most likely type of organic chemicals transferred from soil to aboveground plant compartments [45,66].…”

Section: Relationships Between Plant Bioaccumulation Metrics and Orgamentioning

confidence: 99%

A review of measured bioaccumulation data on terrestrial plants for organic chemicals: Metrics, variability, and the need for standardized measurement protocols

Doucette

Shunthirasingham

Dettenmaier³

et al. 2017

Enviro Toxic and Chemistry

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Quantifying the transfer of organic chemicals from the environment into terrestrial plants is essential for assessing human and ecological risks, using plants as environmental contamination biomonitors, and predicting phytoremediation effectiveness. Experimental data describing chemical uptake by plants are often expressed as ratios of chemical concentrations in the plant compartments of interest (e.g., leaves, shoots, roots, xylem sap) to those in the exposure medium (e.g., soil, soil porewater, hydroponic solution, air). These ratios are generally referred to as "bioconcentration factors" but have also been named for the specific plant compartment sampled, such as "root concentration factors," "leaf concentration factors," or "transpiration stream (xylem sap) concentrations factors." We reviewed over 350 articles to develop a database with 7049 entries of measured bioaccumulation data for 310 organic chemicals and 112 terrestrial plant species. Various experimental approaches have been used; therefore, interstudy comparisons and data-quality evaluations are difficult. Key exposure and plant growth conditions were often missing, and units were often unclear or not reported. The lack of comparable high-confidence data also limits model evaluation and development. Standard test protocols or, at a minimum, standard reporting guidelines for the measurement of plant uptake data are recommended to generate comparable, high-quality data that will improve mechanistic understanding of organic chemical uptake by plants. Environ Toxicol Chem 2018;37:21-33. C 2017 SETAC

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Section: Relationships Between Plant Bioaccumulation Metrics and Orgamentioning

confidence: 99%

A review of measured bioaccumulation data on terrestrial plants for organic chemicals: Metrics, variability, and the need for standardized measurement protocols

Doucette

Shunthirasingham

Dettenmaier³

et al. 2017

Enviro Toxic and Chemistry

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“…[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]). In most cases, the underlying different equations have been solved for steady-state and/or numerically for dynamic studies.…”

Section: A Rein Et Al Sar and Qsar In Environmental Researchmentioning

confidence: 99%

“…Considering e.g. trees or annual seed crops, water flux into leaves and fruits, Q L and Q F , can be calculated from total (xylem) flow Q by averaging with the respective (green) surface areas, where phloem flux adds for fruits [9] and subtracts for leaves:…”

Section: Sar and Qsar In Environmental Researchmentioning

confidence: 99%

New concepts for dynamic plant uptake models

Rein

Legind

Trapp

2011

SAR and QSAR in Environmental Research

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Models for the prediction of chemical uptake into plants are widely applied tools for human and wildlife exposure assessment, pesticide design and for environmental biotechnology such as phytoremediation. Steady-state considerations are often applied, because they are simple and have a small data need. However, often the emission pattern is non-steady. Examples are pesticide spraying, or the application of manure and sewage sludge on agricultural fields. In these scenarios, steady-state solutions are not valid, and dynamic simulation is required.We compared different approaches for dynamic modelling of plant uptake in order to identify relevant processes and time-scales of processes in the soil-plant-air system. Based on the outcome, a new model concept for plant uptake models was developed, approximating logistic growth and coupling transpiration to growing plant mass. The underlying system of differential equations was solved analytically for the inhomogenous case, i.e., for constant input. By superposition of the results of n periods, changes in emission and input data between periods are considered. This combination allows to mimick most input functions that are relevant in practice.The model was set up, parameterised and tested for uptake into growing crops. The outcome was compared to a numerical solution, to verify the mathematical structure.

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“…We calculated the total balance of the herbicide's mass through the following equations: (TRAPP et al, 2003;PARAIBA, 2007;PARAIBA et al, 2010), where M P (kg ha -1 ) is the total plant fresh biomass, Q (L day -1 ha -1 ) is the plant transpiration rate, TSCF soil is the herbicide concentration factor in the transpiration stream in relation to the soil solution, C W (mg L -1 ) is the soil solution herbicide concentration, k E (day -1 ) is the herbicide transformation rate in the plant, k G (day -1 ) is the plant growth rate, C P (mg kg -1 ) is the plant herbicide concentration, and K PW (L kg -1 ) is the herbicide plant-water sorption coefficient or herbicide bagasse-water sorption coefficient measured as described in the sorption experiments.…”

Section: Methodsmentioning

confidence: 99%

“…Several models simulate any substance uptake by plants (TRAPP & MATTHIES, 1995;FUJISAWA et al, 2002;TRAPP et al, 2003;TRAPP, 2007;PARAIBA & KATAGUIRI, 2008). Some researchers developed models to simulate specific substance uptake by leaves (TRAPP, 1995), roots and tubers, (TRAPP et al, 2003;PARAIBA & KATAGUIRI, 2008) or by roots and leaves (FUJISAWA et al, 2002;TRAPP, 2007). However, none of these models estimate the herbicide bioconcentration factor and uptake in sugarcane.…”

Section: Introductionmentioning

confidence: 99%