Abstract:
The epithermal neutron shape factor, α of the inner and outer irradiation sites of the Ghana Research Reactor-1 (GHARR-1) was determined obtaining results of 0.105 for the inner (Channel 1) Irradiation site and 0.020 for the outer (channel 6) irradiation site. The neutron temperatures for the inner and outer irradiation sites were 27°C and 20°C, respectively. The α values used in Westcott Formalism k 0 INAA was applied to determine multi elements in 13 Ghanaian herbal medicines used by the Centre for Scientific Research into Plant Medicine (CSRPM) for the management of various diseases complemented by Atomic Absorption Spectrometry. They are namely Mist. Antiaris, Mist. Enterica, Mist. Morazia, Mist. Nibima, Mist. Modium, Mist. Ninger, Mist Sodenia, Mist. Tonica, Chardicca Powder, Fefe Powder, Olax Powder, Sirrapac powder and Lippia Tea. Concentrations of Al, As, Br, K, Cl, Cu, Mg, Mn, Na and V were determined by short and medium irradiations at a thermal neutron flux of 5×10 11ncm -2s -1. Fe, Cr, Pb, Co, Ni, Sn, Ca, Ba, Li and Sb were determined using Atomic Absorption Spectrometry (AAS). Ba, Cu, Li and V were present at trace levels whereas Al, Cl, Na, Ca were present at major levels. K, Br, Mg, Mn, Co, Ni, Fe and Sb were also present at minor levels. Arsenic was not detected in all samples. Standard Reference material, IAEA-V-10 Hay Powder was simultaneously analysed with samples. The precision and accuracy of the method using real samples and standard reference materials were evaluated and within ±10% of the reported value. Multivariate analytical techniques, such as cluster analysis (Q-mode and R-mode CA) and principal component analysis (PCA)/factor analysis (FA), have been applied to evaluate the chemical variations in the herbal medicine dataset. All the 13 samples may be grouped into 2 statistically significant clusters (liquid based and powdered herbal medicines), reflecting the different chemical compositions. R-mode CA and PCA suggest common sources for Co, Mg, Fe, Ca, Cr, Ni, Sn, Li and Sb and Na, V, Cl, Mn, Al, Br and K. The PCA/FA identified 3 dominant factors as responsible for the data structure, explaining 84.5% of the total variance in the dataset. © 2011 Elsevier Ltd.