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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