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Improved prediction of the bioconcentration factors of organic contaminants from soils into plant/crop roots by related physicochemical parameters

There has been an on-going pursuit for relations between the levels of chemicals in plants/crops and the source levels in soil or water in order to address impacts of toxic substances on human health and ecological quality. In this research, we applied the quasi-equilibrium partition model to analyz...

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Detalles Bibliográficos
Autores principales: Li, Yuanbo, Chiou, Cary T., Li, Hui, Schnoor, Jerald L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6931905/
https://www.ncbi.nlm.nih.gov/pubmed/30776749
http://dx.doi.org/10.1016/j.envint.2019.02.020
Descripción
Sumario:There has been an on-going pursuit for relations between the levels of chemicals in plants/crops and the source levels in soil or water in order to address impacts of toxic substances on human health and ecological quality. In this research, we applied the quasi-equilibrium partition model to analyze the relations for nonionic organic contaminants between plant/crop roots and external soil/water media. The model relates the in-situ root concentration factors of chemicals from external water into plant/crop roots (RCF((water))) with the system physicochemical parameters and the chemical quasi-equilibrium states with plant/crop roots (α(pt), ≤1). With known RCF((water)) values, root lipid contents (f(lip)), and octanol-water K(ow)’s, the chemical-plant α(pt) values and their ranges of variation at given f(lip)K(ow) could be calculated. Because of the inherent relation between α(pt) and f(lip)K(ow), a highly distinct correlation emerges between log RCF((water)) and log f(lip)K(ow) (R(2) = 0.825; n = 368), with the supporting data drawn from 19 disparate soil-plant studies covering some 6 orders of magnitude in f(lip)K(ow) and 4 orders of magnitude in RCF((water)). This correlation performs far better than any relationship previously developed for predicting the contamination levels of pesticides and toxic organic chemicals in plant/crop roots for assessing risks on food safety.