Abstract
Prediction models were developed to estimate the extent to which aluminium, chromium, copper, iron, manganese, nickel, lead, and zinc were absorbed in the grains, leaves, stems, and roots of Sorghum bicolor cultivated in soil with various amendment rate of sewage sludge (0, 10, 20, 30, 40, and 50 g/kg) under greenhouse conditions. It was found that, aside from lead, all the examined metals occurred in significantly higher content in the roots compared to aerial tissues. Furthermore, the r-values were significantly negative between the bioconcentration factors of all metals, apart from aluminium and lead, and soil pH, whereas they were significantly positive between the bioconcentration factors, apart from lead, and soil organic matter content (OM). The r-values were typically significantly positive between the levels of all eight metals in the investigated tissues and in the soil. Moreover, the content of all the eight metals in the tissues exhibited a significant negative r-value with soil pH but a significant positive r-value with soil OM. The eight metal contents in the tissues given by the prediction models were quite similar to the real values, suggesting that the created models performed well, as shown by t-tests. It was thus concluded that prediction models were a viable option for evaluating how safe it was to grow S. bicolor in soils with sewage sludge content and at the same time for keeping track of possible human health hazards.