A dynamic model to calculate cadmium concentrations in bovine tissues from basic soil characteristics

Development and comparison of regression models for the uptake of metals into various field crops

“…The explained variabilities of other models were lower, though they had high correlations. Grass models for Cd confirmed the positive effect of Cd concentration in soil and the negative effect of pH, as in the spring model by Waegeneers et al (2011). Grass models for other metals had similar specific parameters for each metal for both mowings (Tables SI12e SI13).…”

“…The simple estimation of bioconcentration factors (BCF) can serve as a rough insight into the range of heavy metal uptake, but it does not reflect more detailed site-specific conditions. A more complex approach is represented by regression models, in which concentrations of metals in plants are predicted by various soil parameters, mostly the total concentration of a metal in soil, soil pH, and organic carbon (Adams et al, 2004;Be ster et al, 2013;EC-DGI, 2000;Eriksson et al, 1996;Hough, 2002;Chaudri et al, 2007;Jackson and Alloway, 1992;Legind and Trapp, 2010;Otte et al, 2001;Waegeneers et al, 2011). Nevertheless, other models have revealed further important parameters e for example, clay content, the dry weight of the plant (Otte et al, 2001), the concentrations of other metals in the soil (Eriksson et al, 1996), and interaction terms between variables, which might reveal other than the measured soil properties (Tudoreanu and Phillips, 2004).…”

Uptake prediction of ten heavy metals by Corchorus olitorius L. cultivated in soil mixed with sewage sludge

“…Regression models are mathematical approaches that predict the concentrations of HMs in plants using some soil variables such as soil HMs, pH, and OM (Chaudri et al, 2007; Eid, Alrumman, Farahat, et al, 2018; Eid, Alrumman, Galal, et al, 2018, 2019; Eid, Shaltout, Abdallah, et al, 2019; Eid, Shaltout, Alamri, et al, 2019; Waegeneers et al, 2011). Data presented here suggested that the calculated prediction models are highly performed for all the estimated HMs in shoots and roots of C. olitorius , based on the parameters that evaluate the high performance of the models ( R 2 , ME, MNAE, and t ‐values).…”

“…They are useful mathematical tool for predicting the levels of the HMs in crop plants depending on certain soil properties including soil HMs, pH, and OM as independent variables (Waegeneers, Ruttens, & Temmerman, 2011). Regression models are available for many crop plants (e.g., Bešter, Lobnik, Eržen, Kastelec, & Zupan, 2013; Chaudri et al, 2007; Eid, Alrumman, Farahat, & El‐Bebany, 2018; Eid, Alrumman, Galal, & El‐Bebany, 2018; Eid, Alrumman, Galal, & El‐Bebany, 2019; Eid, Shaltout, Abdallah, et al, 2019; Eid, Shaltout, Alamri, et al, 2019; Novotná, Mikeš, & Komprdová, 2015; Ramadan & Al‐Ashkar, 2007; Waegeneers et al, 2011; Zeng et al, 2011). For the safe crop production, it is useful to create multiple models of regression to investigate the correlation between HMs in plants and in soils supporting them to evaluate the dangerous levels of these HMs in soil.…”

Regression Models to Estimate Accumulation Capability of Six Metals by Two Macrophytes, Typha domingensis and Typha elephantina, Grown in an Arid Climate in the Mountainous Region of Taif, Saudi Arabia

“…A straightforward appraisal of bioaccumulation factors (BAFs) provides an approximate guide into the metal uptake spectrum but fails to offer in-depth information on location-specific sediment properties [18]. Regression models have utility for the estimation of the metallic levels in plants according to a range of sediment measurements, such as metal concentrations, pH, and proportion of organic matter [19]. Plant uptake is primarily governed by metal solubility and bioavailability [20].…”