Prediction models based on soil properties for evaluating the uptake of eight heavy metals by tomato plant (Lycopersicon esculentum Mill.) grown in agricultural soils amended with sewage sludge

The aim of this study is to design de novo prediction models in order to gauge the likely uptake of eight heavy metals (Al, Cr, Cu, Fe, Mn, Ni, Pb and Zn) by Lycopersicon esculentum, the tomato plant. Uptake was assessed within the plant’s root, stem, leaf and fruit tissues, respectively. The plant was cultivated in soil amended by different application rates of sewage sludge, i.e. 0, 10, 20, 30 and 40 g/kg. The roots exhibited markedly elevated heavy metal concentrations compared to the above-ground plant components, with the exception of the quantity of Ni in the leaves. Apart from Al, Fe and Mn, a bioconcentration factor >1 was identified for all heavy metals. Excluding Ni in the leaves, all tested heavy metals exhibited a translocation factor < 1. The regression models were deployed to predict the accretion of the heavy metals under investigation within the various parts of L. esculentum. These were founded on the parameters of the equivalent eight heavy metals within the soil, pH and organic matter content. Student’s unpaired t-tests revealed no differences between the actual and predicted heavy metal concentrations in the roots, stems, leaves or fruits of the tomato plant. These data suggest an excellent model goodness of fit in terms of its accuracy to forecast the degree of heavy metal uptake. The constructed models may therefore facilitate the safe propagation of L. esculentum in growing media amended with sewage sludge, and concurrently provide a risk assessment with respect to human well-being.The authors extend their appreciation to the Scientific Research Deanship at King Khalid University and the Ministry of Education in Saudi Arabia for funding this research work through the project number IFP-KKU-2020/3.Peer reviewe