Sensitive Wavelengths Selection in Identification of Ophiopogon japonicus Based on Near-Infrared Hyperspectral Imaging Technology

Table 4

Results of SVM models using different wavelengths.

Methods	Variables	⁢Calibration		Prediction
		Correct number	Identification accuracy/%	Correct number	Identification accuracy/%
Raw	512	449	99.8	218	96.9
SPA	5	431	95.8	208	92.4	−4.46
RC	7	429	95.3	210	93.3	−3.55
LW	8	415	92.2	205	91.1	−5.71
UVE	291	448	99.6	219	97.3	0.17
UVE-SPA	12	448	99.6	217	96.4	−0.49
CARS	105	444	98.7	217	96.4	−0.40
iPLS	32	442	98.2	199	88.4	−7.97
BiPLS	208	444	98.7	221	98.2	0.77
FiPLS	480	444	98.7	218	96.9	0
GA-PLS	85	448	99.6	223	99.1	1.83