Assessment of heavy metal concentration in amarathus hybridusl on soil supplemented with poultry litter and swine dung
This study identified and determined the concentration of heavy metals in poultry litter and swine dung. It also determined the uptake of the heavy metals by Amaranthushybridus. This was with the view to providing information on the growth and uptake of the heavy metals by Amaranthushybridusgrownon soil supplemented with composted poultry litter and swine dung. The experiment was carried out in the screen house of the Faculty of Agriculture, Obafemi Awolowo University (O.A.U.), Ile-Ife, Nigeria. Twenty (20) kilogrammes each of faeces from both poultry and swine were collected from two different locations namely; the O.A.U. Teaching and Research Farm, Ile-Ife and Dare Farms (a commercial farm), Ilesa, Nigeria. The animal wastes collected were aerobically composted for 60 days. The experiment consisted of six compost treatments which were 100% poultry litter, 100% swine dung and 50% poultry litter + 50% swine dung, each from O.A.U. Teaching and Research Farm, and Dare Farms. A treatment with zero compost addition served as control. Each of the treatment was replicated three times to give a total of 21 pots, arranged in a completely randomized design. Each pot contained three kilogrammes of sieved topsoil, and one kilogramme of the compost. Seeds of A.hybridus obtained from the International Institute of Tropical Agriculture Ibadan were sown. Growth performance of the test crop was monitored until maturity. Growth parameters such as number of leaves and plant height of the crop were measured 10 days after sowing at an interval of five days till 30 days after sowing. Pre- and post-cropping analyses of soil were done using standard methods. The heavy metals (Ni, Cd, Cr, Cu, As, Pb) in the harvested crop and animal feeds were analysed using Atomic Absorption Spectrophotometry. Transfer factors of the heavy metals from the soil to the crop were determined. Data collected were subjected to Analysis of Variance using SAS statistical package and significant means were separated using Duncan’s Multiple Range Test.