Table 2.

The best results from the optimal models of taste score and each taste-related component both in the calibration set and the prediction set based on using Si-PLS algorithm

Quality parameters	n	Selected intervals	PCs	Calibration set		Prediction set
				Rc	RMSEC (%)	Rp	RMSEP (%)
Taste score	15	[1 14 15]	5	0.8517	0.568	0.8462	0.638
Water extracts	15	[3 11 15]	9	0.9376	1.419	0.9089	1.73
Total polyphenols	16	[5 9 16]	6	0.734	2.29	0.7126	2.35
Free amino acids	15	[5 8 9 15]	9	0.9373	0.246	0.8866	0.357
Caffeine	15	[10 12 15]	9	0.9517	0.19	0.9428	0.205
Total catechins	15	[7 12 15]	10	0.7794	0.821	0.7199	0.947
TF2A	14	[5 12 14]	10	0.728	0.149	0.7194	0.178
TF2B	15	[6 8 13 15]	10	0.8324	0.070	0.8074	0.0805
Theaflavins	15	[3 4 15]	8	0.7987	0.296	0.7726	0.34

n Number of intervals, PCs principal components number, R_c correlation coefficient of calibration, RMSEC root mean square error in the calibration set, R_p correlation coefficient of prediction, RMSEP root mean square error values of the prediction set, TF2A theaflavin-3-gallate, TF2B theaflavin-3′-gallate