Skip to main content

Table 1 DL application to genomic selection

From: A review of deep learning applications for genomic selection

Obs Year Authors Crop Topology Response variable(s) Comparison with
1 2011 Gianola et al. [61] Wheat and Jersey cows MLP Grain yield (GY), fat yield, milk yield, protein yield, fat yield Bayesian Ridge regression (BRR)
2 2012 Pérez-Rodríguez et al. [62] Wheat MLP GY and days to heading (DTHD) BL, BayesA, BayesB, BRR, Reproducing Kernel Hilbert Spaces (RKHS) regression
3 2012 Gonzalez-Camacho et al. [6] Maize MLP GY, female flowering (FFL) or days to silking, male flowering time (MFL) or days to anthesis, and anthesis-silking interval (ASI) RKHS regression, BL
4 2015 Ehret et al. [63] Holstein-Friesian and German Fleckvih cattle MLP Milk yield, protein yield, and fat yield GBLUP
5 2016 Gonzalez-Camacho et al. [64] Maize and wheat MLP GY Probabilistic neural network (PNN)
6 2016 McDowell [65] Arabidopsis, maize and wheat MLP Days to flowering, dry matter, grain yield (GY), spike grain, time to young microspore. OLS, RR, LR, ER, BRR
7 2017 Rachmatia et al. [66] Maize DBN GY, female flowering (FFL) (or days to silking), male flowering (MFL) (or days to anthesis), and the anthesis-silking interval (ASI) RKHS, BL and GBLUP
8 2018 Ma et al. [67] Wheat CNN and MLP Grain length (GL), grain width (GW), thousand-kernel weight (TW), grain protein (GP), and plant height (PH) RR-BLUP, GBLUP
9 2018 Waldmann [68] Pig data and TLMAS2010 data MLP Trait number of live born piglets GBLUP, BL
10 2018 Montesinos-López et al. [70] Maize and wheat MLP Grain yield GBLUP
11 2018 Montesinos-López et al. [71] Maize and wheat MLP Grain yield (GY), anthesis-silking interval (ASI), PH, days to heading (DTHD), days to maturity (DTMT) BMTME
12 2018 Bellot et al. [72] Human traits MLP and CNN Height and bone heel mineral density BayesB, BRR
13 2019 Montesinos-López et al. [73] Wheat MLP GY, DTHD, DTMT, PH, lodging, grain color (GC), leaf rust and stripe rust SVM, TGBLUP
14 2019 Montesinos-López et al. [74] Wheat MLP GY, DH, PH GBLUP
15 2019 Khaki and Wang [75] Maize MLP GY, check yield, yield difference LR, regression tree
16 2019 Azodi et al. [77] 6 species MLP 18 traits rrBLUP, BRR, BA, BB, BL, SVM, GTB
17 2019 Liu et al. [78] Soybean CNN GY, protein, oil, moisture, PH rrBLUP, BRR, BayesA, BL
18 2020 Abdollahi-Arpanahi et al. [79] Holstein bulls MLP and CNN Sire conception rate GBLUP, BayesB and RF
19 2020 Zingaretti et al. [80] Strawberry and blueberry MLP and CNN Average fruit weight, early marketable yield, total marketable weight, soluble solid content, percentage of culled fruit RKHS, BRR, BL,
22 2020 Montesinos-López et al. [81] Wheat MLP Fusarium head blight BRR and GP
20 2020 Waldmann et al. [43] Pig data CNN Trait number of live born piglets GBLUP, BL
21 2020 Pook et al. [82] Arabidopsis MLP and CNN Arabidopsis traits GBLUP, EGBLUP, BayesA
23 2020 Pérez-Rodríguez et al. [83] Maize and wheat MLP Leaf spot diseases, Gray Leaf Spot Bayesian ordered probit linear model
  1. RF denotes random forest. Ordinal least square (OLS), Classical Ridge regression (RR), Classical Lasso Regression (LR) and classic elastic net regression (ER). Bayesian Lasso (BL), DBN denotes deep belief networks. GTB denotes Gradient Tree Boosting. GP denotes generalized Poisson regression. EGBLUP denotes extended GBLUP