Estimation of Total Nitrogen Content in Fresh Tea Leaves Based on Wavelet Analysis

Fig. 6. Fitting diagrams of the optimal models of tea nitrogen based on (a) CWT (1 scale)-SPA-PLS, (b) CWT (1 scale)-CARS-PLS and (c) CWT (1 scale)-VCPA-PLS

Download full size

View in Article

Table 1. Models based on different preprocessing methods and variables selection methods

View table

View in Article

Table 1. Models based on different preprocessing methods and variables selection methods

模型	光谱处理	主成分	建模集		预测集
模型	光谱处理	主成分	$R_{C}^{2}$	RMSE_C	$R_{P}^{2}$	RMSE_P
	SG	8	0.50	0.42	0.37	0.48
	Detrending	9	0.59	0.35	0.58	0.38
SPA-PLSR	1st	7	0.63	0.37	0.61	0.35
	SNV	10	0.71	0.31	0.60	0.39
	MSC	8	0.62	0.38	0.68	0.29
	SG	5	0.62	0.35	0.55	0.41
	Detrending	10	0.75	0.30	0.71	0.29
CARS-PLSR	1st	11	0.79	0.26	0.73	0.32
	SNV	11	0.71	0.33	0.68	0.29
	MSC	11	0.73	0.29	0.62	0.39
	SG	6	0.81	0.24	0.65	0.37
	Detrending	10	0.83	0.25	0.73	0.31
VCPA-PLSR	1st	9	0.86	0.18	0.84	0.25
	SNV	7	0.81	0.25	0.67	0.35
	MSC	6	0.82	0.24	0.72	0.32

Table 2. Models based on different decomposition scales and variables selection methods

View table

View in Article

Table 2. Models based on different decomposition scales and variables selection methods

模型	分解尺度	主成分	建模集		预测集
模型	分解尺度	主成分	$R_{C}^{2}$	RMSE_C	$R_{P}^{2}$	RMSE_P
SPA-PLSR	1	5	0.83	0.25	0.72	0.37
	2	7	0.72	0.30	0.68	0.36
	3	10	0.74	0.31	0.69	0.33
	4	11	0.78	0.28	0.67	0.35
	5	11	0.79	0.26	0.60	0.41
	6	11	0.65	0.33	0.60	0.42
CARS-PLSR	1	7	0.91	0.19	0.88	0.24
	2	8	0.81	0.24	0.76	0.32
	3	12	0.81	0.25	0.73	0.31
	4	8	0.82	0.26	0.69	0.29
	5	10	0.78	0.28	0.64	0.35
	6	11	0.73	0.32	0.68	0.32
VCPA-PLSR	1	7	0.95	0.16	0.90	0.23
	2	7	0.83	0.23	0.82	0.27
	3	10	0.81	0.26	0.79	0.26
	4	8	0.82	0.24	0.73	0.30
	5	8	0.81	0.25	0.77	0.30
	6	7	0.73	0.29	0.74	0.35