TABLE 7.

G2F_2015 data. Count of the number of times a model was better than another in terms of Normalized Root Mean Squared Error (NRMSE), both by environments and by traits. Prediction accuracy in terms of NRMSE. b0 denotes the absolute values of the intercept and b denotes the absolute value of 1-slope. Under an ideal model both b0 and b should be equal to zero. Relative efficiency (RE) or each model in percentage was computed regarding model M0 without environmental covariates. When the percentage is positive there is a gain in prediction accuracy regarding M0, while when the percentage is negative there is a loss in terms of prediction accuracy of any model regarding M0.

Model	Env		Trait		NRMSE	NRMSE	Cor	Cor	b0	b0	b	b
	Won	%	Won	%		RE (%)		RE (%)		RE (%)		RE (%)
	Models		Models
M0	340	35.42	30	37.50	9.411	0.00	0.523	0.00	0.336	0.00	0.090	0.00
M1	408	42.50	33	41.25	3.641	158.46	0.524	0.21	1.461	−76.97	0.098	−8.39
M2	307	31.98	26	32.50	9.015	4.39	0.480	−8.19	1.172	−71.30	0.050	79.46
M3	326	33.96	32	40.00	3.199	194.19	0.523	0.06	0.974	−65.47	0.092	−2.16
M4	264	27.50	17	21.25	4.643	102.67	0.443	−15.28	0.914	−63.18	0.166	−46.04
M5	309	32.19	26	32.50	3.794	148.04	0.523	0.10	0.788	−57.32	0.098	−8.76
M6	317	33.02	23	28.75	4.051	132.33	0.523	0.10	0.679	−50.48	0.092	−2.24
M7	287	29.90	17	21.25	4.492	109.48	0.442	−15.41	1.038	−67.59	0.167	−46.26
M8	293	30.52	26	32.50	5.929	58.73	0.439	−16.00	0.974	−65.47	0.166	−46.09
M9	246	25.63	6	7.50	5.145	82.90	0.473	−9.48	2.157	−84.40	0.070	28.20
M10	313	32.60	23	28.75	2.953	218.71	0.437	−16.46	0.964	−65.11	0.052	72.63
M11	309	32.19	26	32.50	4.114	128.75	0.475	−9.08	0.815	−58.72	0.164	−45.25
M12	445	46.35	46	57.50	3.213	192.86	0.486	−6.97	0.395	−14.86	0.134	−33.06
M13	442	46.04	50	62.50	3.139	199.82	0.522	−0.12	1.915	−82.43	0.094	−4.53
M14	424	44.17	39	48.75	3.793	148.10	0.522	−0.21	1.001	−66.37	0.084	6.35