Table 6.

Partial least squares (PLS1) regression analysis of the wine sensory attributes opacity and astringency (Y) showing the total principal component (PC) number in the model, R-squared values for calibration (cal) and validation (val), root mean squared error of prediction (RMSE) and the explained variance (%) for all compositional X variables, and sub-sets of significant X variables.

Variables Included in PLS1 Model	Opacity PLS1 Model							Astringency PLS1 Model
	PC No	R 2 cal	R 2 val	RSMEcal	RSMEval	X (%)	Y (%)	PC No	R 2 cal	R 2 val	RSMEcal	RSMEval	X (%)	Y (%)
All variables	2	0.93	0.70	0.17	0.39	31	93	2	0.88	0.60	0.08	0.15	32	87
Significant variables *	1	0.91	0.89	0.20	0.23	66	91	1	0.82	0.76	0.10	0.12	37	82
Significant variables * excluding pH and TA	1	0.90	0.88	0.21	0.24	72	90	1	0.81	0.75	0.10	0.12	38	81

* identified using uncertainty test.