YIELD STABILITY AND MEGA ENVIRONMENT ANALYSIS BASED ON THE PERFORMANCE OF QUALITY PROTEIN MAIZE IN SUB-SAHARAN AFRICA

• Main Author: Issa, AbduRahman Beshir
• Other Authors: Dr A van Biljon
• Format: Others
• Language: en-uk
• Published: University of the Free State 2014
• Subjects: Plant Sciences
• Online Access: http://etd.uovs.ac.za//theses/available/etd-08072014-094755/restricted/

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.