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Table 3 Admixture proportions allow predicting quantitative disease resistance to soil-borne pathogens in M. truncatula. (a) Linear model between admixture components and maximum symptom scores in response to Verticillium alfalfae in a collection of 242 accessions. (b) Linear model between admixture components and root rot index due to infection by Aphanomyces euteiches. Data from Bonhomme et al. [17]

From: WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants

 

Estimate

Std. error

t value

Pr (. > |t|)

(a)

 Intercept

2.4541

0.0861

28.50

0.0000

 Spanish Coastal

− 1.4147

0.2290

− 6.18

0.0000

 South Tunisian Coastal

− 0.7222

0.2367

− 3.05

0.0026

 Greek

0.6017

0.1636

3.68

0.0003

 Spanish-Moroccan Inland

− 0.8518

0.1804

− 4.72

0.0000

 r2 = 0.31. P = 2.2 × 10−16

(b)

 Intercept

2.7362

0.1237

22.12

0.0000

 Algiers

− 1.2335

0.2816

− 4.38

0.0000

 Spanish Coastal

− 1.1635

0.2353

− 4.95

0.0000

 North Tunisian Coastal

− 1.4798

0.3648

− 4.06

0.0001

 Atlas

− 0.7511

0.1918

− 3.92

0.0001

 French

− 0.5753

0.1963

− 2.93

0.0038

 Greek

− 0.3084

0.1812

− 1.70

0.0906

 r2 = 0.19. P = 1.8 × 10−7