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. 2012 May 1;2(5):579–595. doi: 10.1534/g3.112.002303

Table 5. Significant QTL and the percentage of genetic variance explained by the full QTL model for photosynthate acquisition, accumulation, and partitioning traits in the DOR364 × BAT477 mapping population grown under drought stress and nonstress conditions at four different locations in three countries (Colombia, Ethiopia, and Malawi) using multienvironment mixed model genome scan.

% of Genetic Varianceb
Trait QTLa LG Marker LOD Wald Prwald Stress Nonstress
Yield Yld8.1 8 P103 2.83 3.03 0.003 19.45 14.45
Canopy biomass Cbm3.1 3 AD1801 4.14 3.37 0.011 0.70 5.35
Pod harvest index Phi6.1 6 Y501 3.30 4.92 0.001 0.00 6.45
Pod partitioning index Ppi3.1 3 Q1701 3.14 3.28 0.013 0.95 10.00
Stem biomass reduction Sbr9.1 9 Y1701 2.88 8.42 0.004 2.15 4.20
Harvest index Hri3.1 3 Q1701 2.85 3.03 0.019 0.65 4.55
Stem TNC Stc5.1 5 F601 4.77 11.72 0.000 1.20 17.60
Stc6.1 6 M501 3.68 17.35 0.000 11.60 3.60
SPAD chlorophyll meter reading Scr6.1 6 BMc238 10.79 11.39 0.000 19.68 42.23
Leaf area index Lai10.1 10 N601 2.76 11.52 0.001 0.00 3.40

QTL, quantitative trait loci; LG, linkage group; LOD, log of odds; Prwald = Wald probability; TNC, total nonstructural carbohydrate content; SPAD, XXX.

a

QTL name based on association with yield (Yld), canopy biomass (Cbm), pod harvest index (Phi), Pod partitioning index (Ppi), stem biomass reduction (Sbr), harvest index (Hri), stem total nonstructural carbohydrate (Stc), SPAD chlorophyll meter reading (Scr), and leaf area index (Lai). Numbers indicate chromosome association (first number) and order of identification (second number after decimal point).

b

The percentage of variance explained for each QTL under the full QTL model drought stress and nonstress conditions was calculated as average across the sites for the trait in respective drought stress and nonstress environments.