Multisurface modeling of Ni bioavailability to wheat (Triticum aestivum L.) in various soils. (July 2018) - Zhao, Xiaopeng; Jiang, Yang; Gu, Xueyuan; Gu, Cheng; Taylor, J. Anita; Evans, Les J.
Abstract: Continual efforts have been made to determine a simple and universal method of estimating heavy metal phytoavailability in terrestrial systems. In the present study, a mechanism-based multi-surface model (MSM) was developed to predict the partition of Ni(II) in soil–solution phases and its bioaccumulation in wheat ( Triticum aestivum L. ) in 19 Chinese soils with a wide range of soil properties. MSM successfully predicted the Ni(II) dissolution in 0.01 M CaCl2 extracting solution ( R 2 = 0.875). The two-site model for clay fraction improved the prediction, particularly for alkaline soils, because of the additional consideration of edge sites. More crucially, the calculated dissolved Ni(II) was highly correlated with the metal accumulation in wheat ( R 2 = 0.820 for roots and 0.817 for shoots). The correlation coefficients for the MSM and various chemical extraction methods have the following order: soil pore water > MSM ≈ diffuse gradient technique (DGT) > soil total Ni > 0.43 M HNO3 > 0.01 M CaCl2 . The results suggested that the dissolved Ni(II) calculated using MSM can serve as an effective indicator of the bioavailability of Ni(II) in various soils; hence, MSM can be used as an supplement for metal risk prediction and assessment besides chemical extraction techniques. Graphical abstract: Image 1 Highlights: Multi-surface model could predict Ni accumulation in wheat in 19 Chinese soils. The performance order was soil pore water > model ≈ DGT >0.43 M HNO3 > 0.01 M CaCl2 . The model is suitable for various soil types without any parameter adjustments. The calculated dissolved Ni serves as a strong indicator of Ni in soil pore water. Abstract : Prediction of Ni bioaccumulation in wheat using a geochemical multi-surface model.