S. Groh et al., Analysis of factors influencing milling yield and their association to other traits by QTL analysis in two hexaploid oat populations, THEOR A GEN, 103(1), 2001, pp. 9-18
Milling yield, or the grain weight from which 100 kg of rolled groats is ob
tained upon milling. is an important quality characteristic of cultivated o
at (Avena sativa L.). Kernel morphology and the groat (caryopsis) percentag
e of the whole kernel including hull are factors that influence milling yie
ld. We mapped QTLs for kernel area, kernel length, kernel width, and groat
percentage in two populations of 137 recombinant inbred lines by RFLP and A
FLP analysis to evaluate the prospects of marker-assisted selection (MAS).
Phenotypic correlations between kernel morphology traits and groat percenta
ge were not significant. For kernel morphology traits and groat percentage,
one to five QTLs were detected, explaining 7.0-60.7% of the total phenotyp
ic variance depending on the trait. One QTL for kernel length in each popul
ation and one QTL for kernel width in one population were found at the same
location as a QTL for groat percentage., indicating that a change in kerne
l size or shape could have an influence on groat percentage. The positions
and effects of QTLs for kernel morphology and groat percentage were compare
d to QTLs detected previously for chemical grain composition (oil and P-glu
can concentration) and agronomic traits to evaluate the selection response
on these traits through MAS. Several regions of the oat genome were identif
ied that contained clusters of QTLs influencing two or more traits. While t
he allele from one parent at a QTL could simultaneously improve two or more
traits in one population. it could have opposite effects on the same trait
s at another QTL or in the other population. Associations among traits were
complex and will require careful consideration when employing QTL-marker a
ssociations in MAS to avoid negative selection response. Future research to
discover candidate genes for those QTL clusters could provide information
about trait associations and help in designing selection programs.