Table 3.

Parameter estimates, goodness of fit statistics, and correlations between predictions made by different methods obtained for milk technological properties when models were fitted to the entire data set, by trait and model¹

Trait2 and model	Variance		R2	DIC	pD/Terms	Correlations between predictions of different models
	Phenotypic	Residual				MPLS	Bayes RR	Bayes A	Bayes B
RCT	32.57
PLS		15.49	0.53	—	14	0.92	0.92	0.92	0.87
MPLS		12.69	0.61	—	15	—	0.96	0.96	0.94
Bayes RR		8.35	0.75	6,534	179	—	—	0.99	0.97
Bayes A		8.82	0.73	6,513	138	—	—	—	0.98
Bayes B		8.71	0.73	6,333	60	—	—	—	—
CYCURD	3.57
PLS		1.00	0.72	—	14	0.97	0.98	0.98	0.96
MPLS		0.92	0.74	—	11	—	0.98	0.99	0.98
Bayes RR		0.74	0.79	3,405	118	—	—	1.00	0.98
Bayes A		0.72	0.80	3,335	107	—	—	—	0.99
Bayes B		0.67	0.81	3,175	72	—	—	—	—
RECPROTEIN	5.81
PLS		2.69	0.54	—	15	0.89	0.87	0.87	0.84
MPLS		1.85	0.68	—	16	—	0.95	0.95	0.94
Bayes RR		1.06	0.82	4,029	210	—	—	0.99	0.98
Bayes A		1.14	0.81	4,050	179	—	—	—	0.98
Bayes B		1.08	0.81	3,844	110	—	—	—	—
RECFAT	12.84
PLS		9.44	0.27	—	10	0.89	0.95	0.91	0.88
MPLS		8.79	0.32	—	9	—	0.93	0.93	0.94
Bayes RR		7.71	0.41	6,209	104	—	—	0.97	0.95
Bayes A		7.57	0.42	6,152	88	—	—	—	0.96
Bayes B		7.48	0.42	6,079	59	—	—	—	—

¹PLS = partial least squares regression; MPLS = modified partial least squares regression, Bayes RR = Bayes ridge regression; R² = coefficient of determination calculated as the square of the correlation between observed and predicted values; DIC = deviance information criterion; pD/Terms = effective number of parameters/number of MPLS or PLS terms.

²RCT = rennet coagulation time, min; CY_CURD = cheese yield, weight of fresh curd as a percentage of the milk processed by weight; REC_PROTEIN = recovery of protein, protein of the curd as a percentage of the protein of the milk processed; REC_FAT = recovery of fat, fat of the curd as a percentage of the fat of the milk processed.