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Table 3 Wheat datasets – two classes

From: Genome-enabled prediction using probabilistic neural network classifiers

    

Number of individuals

Number of individuals

Data set

Agronomic management

Site in Mexico

Year

Upper

Lower

Upper

Lower

    

15 %

85 %

30 %

70 %

GY-1

Drought-bed

Cd. Obregon

2009

46

260

92

214

GY-2

Drought-bed

Cd. Obregon

2010

47

259

92

214

GY-3

Drought-flat

Cd. Obregon

2010

39

224

80

183

GY-4

Full irrigation-bed

Cd. Obregon

2009

46

258

92

212

GY-5

Full irrigation-bed

Cd. Obregon

2010

46

260

94

212

GY-6

Heat-bed

Cd. Obregon

2010

46

260

94

212

GY-7

Full irrigation-flat-borders

Cd. Obregon

2010

39

224

79

184

    

Lower

Upper

Lower

Upper

    

15 %

85 %

30 %

70 %

DTH-1

Drought-bed

Cd. Obregon

2009

53

253

100

206

DTH-2

Drought-bed

Cd. Obregon

2010

50

256

93

213

DTH-3

Drought-flat

Cd. Obregon

2010

40

223

86

177

DTH-4

Full irrigation-bed

Cd. Obregon

2009

59

247

107

199

DTH-5

Full irrigation-bed

Cd. Obregon

2010

47

259

101

205

DTH-6

Toluca

Toluca

2009

122

184

122

184

DTH-7

El Batan

El Batan

2009

66

240

104

202

DTH-8

Small observation plot

Cd. Obregon

2009

58

243

101

200

DTH-9

Small observation plot

Cd. Obregon

2010

45

218

100

163

DTH-10

Agua Fria

Agua Fria

2010

49

212

81

160

  1. Environment code of 12 combinations of sites in Mexico, agronomic management, and year for two wheat traits (grain yield, GY, and days to heading, DTH) from [11]. Number of markers, total number of individuals, number of individuals in the upper 15 and 30 % classes, and in the lower 85 and 70 % classes