Detailed knowledge on genetic diversity among germplasm
is important for hybrid maize (
Zea mays
L.) breeding. The
objective of the study was to determine genetic diversity
in widely grown hybrids in Southern Africa, and compare
effectiveness of phenotypic analysis models for determining
genetic distances between hybrids. Fifty hybrids were
evaluated at one site with two replicates. The experiment was a
randomized complete block design. Phenotypic and genotypic
data were analyzed using SAS and Power Marker respectively.
There was significant (p < 0.01) variation and diversity among
hybrid brands but small within brand clusters. Polymorphic
Information Content (PIC) ranged from 0.07 to 0.38 with
an average of 0.34 and genetic distance ranged from 0.08
to 0.50 with an average of 0.43. SAH23 and SAH21 (0.48)
and SAH33 and SAH3 (0.47) were the most distantly related
hybrids. Both single nucleotide polymorphism (SNP) markers
and phenotypic data models were effective for discriminating
genotypes according to genetic distance. SNP markers revealed
nine clusters of hybrids. The 12-trait phenotypic analysis
model, revealed eight clusters at 85%, while the five-trait
model revealed six clusters. Path analysis revealed significant
direct and indirect effects of secondary traits on yield. Plant
height and ear height were negatively correlated with grain
yield meaning shorter hybrids gave high yield. Ear weight,
days to anthesis, and number of ears had highest positive
direct effects on yield. These traits can provide good selection
index for high yielding maize hybrids. Results confirmed that
diversity of hybrids is small within brands and also confirm
that phenotypic trait models are effective for discriminating
hybrids.
