Table A2.

Dataset 3 EYT 2014–2015

	Models and methods					Models and methods
	BRR	GBLUP	GK	PK	SK	BRR	GBLUP	GK	PK	SK
Scenario	Without G × E (WI)					With G × E (I)
DTHD
MT	4.71	4.71	4.49	4.50	7.75	3.81	3.77	3.29	3.41	7.82
MT_P	4.56	4.56	4.34	4.36	7.46	3.74	3.71	3.22	3.32	7.58
DTMT
MT	5.85	5.85	5.72	5.74	7.90	5.01	5.04	4.42	4.50	7.86
MT_P	5.77	5.77	5.64	5.69	7.70	4.98	4.99	4.38	4.47	7.69

Average mean squared error (MSE) prediction, across environments for five model-methods: BRR, Bayesian ridge regression; GBLUP, genomic best linear unbiased predictor; GK, Gaussian kernel; PK, polynomial kernel; SK, sigmoidal kernel without G × E (WI) and with G × E (I) for two scenarios (MT and MT_P) and two traits (DTHD, days to heading and DTMT, days to maturity). Boldface indicates model-method with the lowest MSE for the scenario.