Wheat Grain Yield Estimation Based on Image Morphological Properties and Wheat Biomass

Table 7

The summary of performance evaluation of the best linear regression, linear, and quadratic SVM model, where SSE is the square sum error of the estimate, is the coefficient of determination, adj. is -squared adjusted for the degree of freedom, and RMSE.

	Mdl1		Mdl2		Mdl3		Mdl4		Mdl5		Mdl6
	V502	V9023	V502	V9023	V502	V9023	V502	V9023	V502	V9023	V502	V9023
SSE	2.096	2.311	2.035	2.184	8.137	10.07	15.55	9.841	6.333	14.46	5.326	7.405
R^2	0.9893	0.9869	0.986	0.987	0.9563	0.931	0.8993	0.9319	0.9665	0.9032	0.9652	0.9492
R^2 adj	0.9892	0.9869	0.986	0.987	0.9562	0.9309	0.8991	0.9317	0.9664	0.9032	0.9651	0.9491
RMSE	0.0684	0.0718	0.0764	0.1204	0.1348	0.1499	0.1863	0.1482	0.1189	0.1796	0.1092	0.1286

V502 = “Luyuan 502” and V9023 = “Zhengmai 9023”.