| Summary: | Quality protein maize (QPM) which is nutritionally enhanced, has the potential to alleviate
malnutrition and related diseases in communities where maize is a dietary staple and often the
only source of proteins. The wide dissemination and utilisation of QPM in Africa depends on
the competitiveness of cultivars for grain yield and other agronomic traits compared to
normal maize. This study was conducted to (i) evaluate the grain yield performance and
stability of newly developed early maturing QPM hybrids under stress and non-stress
environments of ESA (ii) analyse mega-environments of SSA based on the primary and
secondary traits of QPM (iii) asses the adaptation pattern of QPM in SSA based on
multivariate analysis techniques (iv) identify and recommend best performing and widely
adapted early maturing open pollinated QPM varieties for large scale production in the region
and (v) enhance the role of QPM in combating protein energy malnutrition and attendant
diseases in SSA.
The result of the evaluation of 96 single cross hybrids (95 QPM and one normal maize) for
grain yield and stability showed that the candidate varieties out yielded the normal check
based on combined ANOVA across 15 environments. Nine parametric and non-parametric
measures were used to analyse grain yield stability. The parameters ranked the entries
differently mainly due to the inclusion of extreme (stress) environments in the analysis and
the less stable nature of single cross hybrids. Most of the stability parameters were
significantly and positively correlated.
AMMI and GGE biplots were effective for the analysis of the multi environment data set.
The models were used to identify stable genotypes, discriminating environments and
adaptation patterns of the entries in ESA. Entries 40 and 37 were the highest yielding while
entry 60 was the most stable. The optimum environments in Harare, Zimbabwe were the most
discriminating and representative. Mega-environment analysis using the GGE biplot grouped
the environments into four groups, with each having more than one site except Chisumbanje,
Zimbabwe which was identified as a separate mega-environment. AMMI2 explained 60% of
the G x E interaction which was higher than the GGE2 (50%) which in turn was higher than
the AMMI1 (35.73%) model. The GGE biplot options allow better visualisation of the
complex multi-environment data than the AMMI model. Candidate QPM OPVs out yielded the normal maize commercial variety, Katumani in 37
environments of ECA based on two sets of trials conducted during 2006-2008. However,
Katumani was earliest maturing in all the environments. The environments were grouped into
different mega-environments based on grain yield and days to anthesis. The classification of
environments into similar mega-environments will facilitate germplasm exchange among
environments and will assist the large scale production of QPM in similar environments. It
was found that recycling of QPM OPVs for more than three years or seasons will result in
significant yield reduction. Hence, seeds should be renewed after three generations of
recycling.
Although this study should significantly contribute to the role of QPM in reducing
malnutrition and related diseases in SSA through best performing genotypes, the fast-track
deployment of QPM in the region, however, depends upon the presence of a functional maize
seed system. A viable maize seed system will improve access and availability of QPM seeds,
particularly OPV seeds, to resource poor farmers who are the most vulnerable to food and
nutritional insecurity. Future research can also deal with the effect of diverse growing
conditions of SSA on the nutritional quality of QPM and how farmers can maintain the seed
and protein quality of OPVs.
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