Spectral data and the chemical data are written in the form of matrices, in which each row represents a sample spectrum. Rank (the number of PLS vectors) is crucial for the quality of the calibration model. Rank below 10 is desirable (Yang et al., 2008). All the spectral preprocessing method had rank below 10 (Table 1). RMSECV is a quantitative measure for the preciseness with which the samples are predicted during validation. RMSECV values obtained using different preprocessing methods were in the range of 0.277-0.709. Lowest value of RMMSECV (0.277) was obtained using straight line subtraction preprocessing method and it was maximum in case of first derivative. Residual Prediction Deviation (RPD) is qualitative measurement of the assessment of validation results. Larger the RPD, the better is the calibration. RPD values greater than 2.5 is desirable as lower value can result from the narrow range of reference value (Cozzolino et al., 2008).