Table 4.

Genome‐wide predictions for various traits in crops

Crop	Training population	Markers used	Traits analysed	Predictive ability/Prediction accuracy	Model	References
Wheat	1100 PYT lines (F3:6)	27 000 SNPs	Grain yield	0.17–0.28	GBLUP	Belamkar et al. (2018)
	10 375 lines	18 101 SNPs	Grain yield, relative maturity, glaucousness and thousand‐kernel weight	0.59–0.98	Maximal model (GBLUP)	Norman et al. (2018)
	330 lines from HarvestPlus Association Mapping (HPAM) panel	24 497 SNPs	Grain zinc and iron concentrations, thousand‐kernel weight and days to maturity	0.324–0.76	GBLUP using the reaction norm model	Velu et al. (2016)
	208 lines	6211 DArTseq‐SNPs	Grain yield, thousand‐grain weight, grain number, days to anthesis, days to maturity, plant height and normalized difference vegetation index at vegetative and grain filling	0.34–0.68	GBLUP	Sukumaran et al. (2018)
	287 advanced elite lines (WAMI panel)	15 000 SNPs	Grain yield, thousand‐grain weight), grain number, thermal time for flowering	0.27–0.63	GBLUP	Sukumaran et al. (2017)
	1378 breeding lines	–	Grain yield and yield stability	up to 0.54	Reaction norm models	Jarquín et al. (2017)
	2992 F2:4 lines	25 000 SNPs	Grain yield	0.125–0.127	GBLUP	Edwards et al. (2019)
	2325 inbred lines	12 642 SNPs	Fusarium head blight, Septoria tritici blotch	up to 0.6	RR‐BLUP, Bayes Cπ, RKHS, EG‐BLUP	Mirdita et al. (2015)
Soybean	301 elite breeding lines	52 349 SNPs	Grain yield	0.43–0.68	G‐BLUP, G°G, Kaa, G_G°G, G_Kaa	Jarquín et al. (2014)
Maize	169 doubled haploid lines and 190 testcrosses	20 473 SNPs	Grain yield, plant height, anthesis‐silking interval, normalized difference vegetative index (NDVI), the green leaf area duration (GLAD)	0.16–0.48	rrBLUP	Cerrudo et al. (2018)
	4120 lines from 22 biparental populations	200 SNPs	Grain yield, anthesis date, plant height	0.18–0.38	rrBLUP	Zhang et al. (2017)
	284 inbred lines	55 000 SNPs	Female flowering, male flowering, grain yield, anthesis‐silking interval	0.28–0.84	Bayesian LASSO (BL), radial basis function neural network (RBFNN), reproducing kernel Hilbert space (RKHS)	Crossa et al. (2014)
Barley	750 lines	11 203 SNPs	Earing, hectolitre weight, spikes per square metre, thousand‐kernel weight and yield	0.31–0.71	GBLUP	Thorwarth et al. (2017)
Pea	315 RILs	400–500 SNPs	Grain yield	0.4–0.5	BL, rrBLUP, support vector regression (SVR)	Annicchiarico et al. (2017)
	339 accessions	13 200 SNPs	Thousand seed weight, the number of seeds per plant and the date of flowering	up to 0.83	Kernel partial least squares regression (kPLSR), least absolute shrinkage and selection operator (LASSO), genomic best linear unbiased prediction (GBLUP), BayesA and BayesB using	Tayeh et al. (2015)
Chickpea	320 breeding lines	3000 DArTs and DArTSeq‐SNPs	Days to flowering, days to maturity, 100‐seed weight and seed yield	0.138–0.912	RR‐BLUP, Kinship Gauss, BayesCp, BayesB, BayesLASSO, and Random Forest	Roorkiwal et al. (2016)
	320 breeding lines	90 000 SNPs	Yield and yield‐related traits	–	Multiplicative reaction norm model (MRNM)	Roorkiwal et al. (2018)
	132 advanced breeding lines and varieties	147 777 SNPs	Yield and yield‐related traits	0.25	RR‐BLUP, Bayesian LASSO, and Bayesian ridge regression (BRR)	Li et al. (2018)