Prediction of Linalool Content in Osmanthus fragrans Using E-Nose Technology

Table 3

Prediction models of all sensors and feature sensors based on PCR and MLR.

Modeling method	Number of variables	Calibration	Root mean square error (RMSE)	_Prediction	Root mean square error (RMSE)
PCR	10	0.986	3.06	0.736	3.98
	6	0.986	3.04	0.685	3.83
MLR	10	0.992	2.48	0.895	2.10
	6	0.990	2.72	0.875	3.39