Abstract
A procedure has been used for the classification and quantification of metals on the basis of a chemometric analysis of visible and near-infrared (Vis-NIR) spectra of metals such as Cu, Mn and Fe in the brain, liver, kidney and testis of mice without digestion. Transmittance spectra in the 600- to 1000-nm region subjected to partial least-squares (PLS) regression analysis and leave-out cross-validation facilitated development of chemometrics models for predicting metal concentration. From the models, Cu, Mn and Fe yielded the coefficients of determination in cross-validation (R2VAL) as 0.8013, 0.9021 and 0.8295 with standard errors of cross-validation (SECV) of 3.399, 0.8237 and 76.512 μg per g tissue, respectively. The respective detection limits of Cu, Mn and Fe were 12.19, 2.616 and 266.32 μg per g tissue. Furthermore, the regression coefficients of the models showed specific patterns for the respective metals. These results suggest that Vis-NIR spectroscopy may have a great potential for analysis of native state of metals in tissues.
