Development of a predictive tool for rapid assessment of soil total nitrogen in wheat-corn double cropping system with hyperspectral data

Figures & data

Figure 1. Research area showing the experimental plots and soil sampling locations.

Table 1. Total nitrogen content (g/kg) in soil samples.

	Sample sets	Sample size	Maximum value	Minimum value	Mean value	Standard deviation
Wheat harvest	Modeling data set	29	1.493	0.9388	1.2734	0.1544
	Validation data set	18	1.510	0.9720	1.3214	0.1267
Corn harvest	Modeling data set	28	1.491	0.9269	1.2285	0.1417
	Validation data set	17	1.430	1.1070	1.3042	0.0931

Table 2. T-test of total nitrogen content of the validation set and the modeling set.

				T-test for Equality of Means
		Levene’s test for equality of variances							95% Confidence Interval of the Difference
		F	Sig.	t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	Lower	Upper
	Equal variances assumed	2.267	0.136	1.196	90	0.235	.0347	.0291	−0.023	0.092
	Equal variances not assumed			1.199	89.330	0.234	.0347	.0290	−0.023	0.092

Figure 2. Difference original reflectance of soil samples in wheat (a) and corn (b) seasons.

Figure 3. Correlation degree between soil reflectance and soil total nitrogen content after pretreatment of soil reflectance in wheat (a) and corn (b) seasons.

Figure 4. Comparison of correlation coefficients between wheat season (a) and corn (b) season soil reflectance before and after SASI calculation.

Figure 5. Measured vs. Predicted values of MLR, BPNN, PLSR modeling data (a), validation data (b) of wheat seasons.

Figure 6. Measured vs. Predicted values of MLR, BPNN, PLSR modeling data (a), validation data (b) of corn seasons.

Table 3. Model analysis accuracy of different modeling methods for wheat-corn double cropping system.

Model	Wheat harvest					Corn harvest					Wheat harvest+Corn harvest
	Modeling samples		Verification samples			Modeling samples		Verification samples			Modeling samples		Verification samples
	R^2	RMSE	R^2	RMSE	RPD	R^2	RMSE	R^2	RMSE	RPD	R^2	RMSE	R^2	RMSE	RPD
Multiple Linear Regression	0.727	0.081	0.475	0.093	1.946	0.690	0.084	0.780	0.051	1.385	0.498	0.106	0.410	0.082	0.834
Back Propagation Neural Network	0.801	0.071	0.782	0.092	2.219	0.895	0.054	0.887	0.035	1.970	0.692	0.107	0.370	0.087	0.940
Partial least Squares Regression	0.721	0.082	0.472	0.092	1.927	0.682	0.078	0.550	0.056	1.491	0.495	0.089	0.400	0.084	0.816

Figure 7. Infrared spectrum of corn (a) and wheat (b) seasons soil.