Table 2. Calibration and cross-validation values in accordance with spectra preprocessing using the partial least squares regression (PLSR) model

Pretreatment¹⁾	Calibration (n=470)				Full cross-validation (n=470)				Total	Prediction (n=200)
Pretreatment¹⁾	Slope	Offset_c	RMSEC²⁾	R²_c	Slope	Offset_cv	RMSECV	R²_cv	R²	Prediction (n=200)
Raw	0.9147	0.2558	0.4129	0.9147	0.9134	0.2598	0.4192	0.9124	0.9136	80.5%
Normalisation	0.9140	0.2579	0.4146	0.9140	0.9130	0.2616	0.4207	0.9119	0.9130	75.5%
Smoothing	0.9142	0.2573	0.4142	0.9142	0.9129	0.2612	0.4202	0.9120	0.9131	81.0%
MSC	0.8839	0.3483	0.4819	0.8839	0.8826	0.3520	0.4862	0.8823	0.8831	69.5%
SNV	0.8845	0.3464	0.4805	0.8845	0.8833	0.3502	0.4848	0.8830	0.8838	70.0%
SG-1	0.9208	0.2375	0.3979	0.9208	0.9186	0.2438	0.3068	0.9176	0.9192	76.0%
SG-2	0.9082	0.2751	0.4283	0.9083	0.9043	0.2869	0.4386	0.9041	0.9062	72.0%

SNV, standard normal variate; MSC, multiple scatter correction; SG-1, Savitzky-Golay-1; SG-2, Savizky-Goloy-2.
RMSEC, root mean square error of calibration; RMSECV, root mean square error of cross-validation; R²_c, the coefficient of determination in calibration; R²_cv, the coefficient of determination in cross-validation;
The average value of R²_c and R²_cv.