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Related Experiment Video

Updated: Jun 3, 2026

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

Published on: September 1, 2020

New concepts for dynamic plant uptake models.

A Rein¹, C N Legind, S Trapp

¹Department of Environmental Engineering, Technical University of Denmark, Lyngby, Denmark. arnr@env.dtu.dk

SAR and QSAR in Environmental Research

|March 11, 2011

Summary

This summary is machine-generated.

This study introduces a new dynamic model for predicting chemical uptake in plants, essential for accurate exposure assessments and environmental applications like phytoremediation when emissions are not constant.

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A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

Published on: August 5, 2020

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Last Updated: Jun 3, 2026

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

Published on: September 1, 2020

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

Published on: August 5, 2020

Area of Science:

Environmental Science
Plant Physiology
Computational Modeling

Background:

Chemical uptake models are crucial for exposure assessment and environmental applications.
Steady-state models are often used but are inadequate for non-steady emission patterns (e.g., pesticide spraying, sludge application).
Dynamic simulation is necessary for scenarios with variable chemical input into the soil-plant system.

Purpose of the Study:

To compare different dynamic modeling approaches for plant chemical uptake.
To identify key processes and timescales within the soil-plant-air system.
To develop an improved dynamic model for plant uptake.

Main Methods:

Compared various dynamic modeling strategies for plant chemical uptake.
Developed a new model concept incorporating logistic growth and transpiration coupled to plant mass.
Solved the differential equations analytically for constant input and used superposition for variable input periods.
Parameterized and tested the model for crop uptake and verified against numerical solutions.

Main Results:

A novel dynamic plant uptake model was developed, approximating logistic growth and coupling transpiration to plant mass.
The analytical solution for constant input, combined with superposition, effectively mimics complex, real-world emission patterns.
Model validation against numerical solutions confirmed its mathematical accuracy.

Conclusions:

The new dynamic model provides a more accurate representation of chemical uptake in plants under non-steady conditions.
This approach enhances the reliability of human and wildlife exposure assessments and environmental risk evaluations.
The model offers a versatile tool for pesticide design and phytoremediation strategies.