Table 8.

Prediction results of PLSR based on fluorescence spectral data.

Feature extraction method	Number of feature variables	Number of potential variables	${\mathit{\text{R}}}_c^2$	RMSEC	${\mathit{\text{R}}}_p^2$	RMSEP	RPD
Boss	31	17	0.8687	0.6612	0.7577	0.6458	2.25
CARS	25	15	0.8588	0.6262	0.8159	0.7237	2.36
IVSO	23	14	0.8068	0.7344	0.7625	0.8171	2.05
IVISSA	41	30	0.9522	0.3851	0.7467	0.7089	2.20
MASS	29	16	0.8530	0.6164	0.8123	0.7743	2.30
CARS-Boss	21	16	0.8376	0.6715	0.7718	0.8058	2.01
MASS-Boss	21	14	0.8017	0.7880	0.7655	0.7024	1.85
IVISSA-Boss	20	16	0.8438	0.6697	0.7999	0.7293	2.23

The bold values represent the best performer in each table.