Some statistical parameters were calculated to compare PLS 1 and PLS 2 models (Table 1),

root mean square error of calibration (RMSEC), root mean square error of the cross validation (RMSECV), root mean square error of prediction (RMSEP), and correlation coefficient (r) between the real concentration and the concentration predicted during the calibration.

Correlation coefficient for calibration and prediction ([R.sup.2]C and [R.sup.2]P) and

root mean square error of calibration and prediction (RMSEC and RMSEP) were tabulated in Table 2; good correlations of calibration were found between GC-IMS data and content of adulterant oil added to canola oil with high coefficient of determination ([R.sup.2]C>0.96) and low errors (RMSEC [less than or equal to] 2.92).

The better analytical performance was obtained by PLS technique coefficient of determination (R2),

root mean square error of calibration (RMSEC) with the value of 0.999 and 0.00864, respectively.

The quality of the calibration model was evaluated using the following statistical parameters: coefficient of determination between predicted and measured luwak content in luwak-arabica blend ([R.sup.2]),

root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), bias between actual and predicted luwak content, and ratio prediction to deviation (RPD) value ([RPD.sub.cal] = [SD.sub.validation set]/RMSECV) [16].

Spectral region 1727-1690 [cm.sup.-1] Factors 4 Validation standards 3 RMSEC 0.449 RMSECV 2.265 RMSEP 0.324 [R.sup.2] 0.9993 [R.sup.2] is correlation coefficient of actual and calculated values of free fatty acids concentration in the calibration set; RMSEC:

root mean square error of calibration; RMSECV: root mean square error of cross-validation; RMSEP: root mean square error of prediction.

The best calibration equation for each analysis was selected in terms of the lowest root mean square error of cross-validation (RMSECV),

root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), and the highest correlation coefficient ([R.sup.2]).

The values of coefficient of determination ([R.sup.2]) and

root mean square error of calibration (RMSEC) were used as performance criteria for calibration model.

(c)

Root mean square error of calibration. (d) Standard error of calibration.

The performances of the optimal model were evaluated according to

root mean square error of calibration (RMSEC).