## 4 Discussion  
IR spectra peaks of Cu, Pb and Cd similar to Figure 1 and Table 1 have been reported in other studies [26]. Spectra interpretations are important when developing chemometric models [18]. The PLS and PCA analysis methods are useful when each measured component produces a measurable peak in the spectrum of the sample mixture [21; 22; 23]. This was also observed in this study in Figure 1. Metals can influence the IR spectra of solutions and obtained spectral variations can be valuable to determine metal detections with the use of chemometric approaches [8]. Complexes containing oxygen with metal ions cause frequency shifting and changes in the intensity and shape of bands. This is usually applied in the analysis of metal concentrations studies with an FT-IR. In this study, Figure 1 and Table 1 show that a similar effect could have influenced the spectra shifts due the presence of oxygen ions in water. The effect of metal bonding in organometallic compounds loosens the bonds causing lowering of the wavelength in a spectra value, more than is seen in free groups [8]. Findings on a study using waste waters suggested that metal ion shifts in a spectrum can be associated with O-H, C-H, C=C, C=O and C-O bonds movement in the functional groups [26]. Results of this study also compare well to Karthikeyan, [3], in a study where heavy metals were induced in water. Their findings suggest that shifts between 3301 to 3281 cm\({}^{-1}\) are assigned to O-H stretching, 2960 to 2874 cm\({}^{-1}\) to CH\({}_{3}\) and CH\({}_{2}\) symmetric stretching and 1664 to 1652 cm\({}^{-1}\), in plane C = O stretching. However, in the present study the solutions only had water and metal ions, which is unlikely to cause CH\({}_{3}\) and CH\({}_{2}\) symmetric stretching and C=O stretching. Studies have showed that the IR spectra of water contains three bands as predicted by the Group Theory [27; 28; 29]. The modes of vibration in water bands are related to dipole moment which are also infra-red active [29; 30]. Water has two stretching vibrations and one bending vibration. Two of the symmetric stretches occur at 3756 and 3657 cm\({}^{-1}\), whereas the bending motion occurs at 1595 cm\({}^{-1}\)[27; 30; 31]. This might also have been the cause in the stretching of the water bands in Figure 1 and Table 1 due to the effect of the studied metal ions. In the present study, closer water band ranges were obtained from all induced metal ions (3357 to 1635 cm\({}^{-1}\)) in the respective peaks in Figure 1.  
Use of PLS and PCA models have been implemented in heavy metal studies based on their regression fit and prediction abilities [8; 20]. In the present study, higher correlations (R\({}^{2}\)) from 0.95 to 1 were observed in the models in Figures 2 and 3. Studies have shown that the FT-IR spectroscopy is an acceptable method to assess heavy metal ions abundance and adsorption [20; 26]. Studies suggest that if the R\({}^{2}\) value is lower than 0.8, the linearity and prediction value have a low correlation with the actual value and the prediction is unfeasible [23]. Furthermore, the closer the RSMEC value is to 0, the higher the prediction of a model [23; 32]. In the present study, models in Figures 2 and 3 had similar low RSMEC values. [PERSON] and [PERSON] [33] in their study successfully reported R values which presented strong and linear relations using FT-IR calibration techniques. Findings in Figures 2d,e and 3d,e in this study compared well with the observations by [PERSON] et al., [8] as zinc and lead had a relatively good fit in their calibration models. However, their results were different on the copper models which presented a weak fit and prediction of the element. In this study, higher linear correlations values were obtained for both PLS and PCA. This result confirmed that rigid cross validation of the sample in standard calibration could have improved the sensitivity of the prediction of the models. This can also be seen on the higher detection of most metals in the study of the PLS calibration method.