Assessment of Early‐Maturing Maize Hybrids and Testing Sites Using GGE Biplot Analysis

Abstract

Identification of outstanding maize (Zea mays L.) hybrids for target environments is complicated by genotype × environment interactions. Thirty‐two early‐maturity maize hybrids were evaluated at eight locations in Nigeria and six locations in Ghana for 2 yr to (i) identify high‐yielding, stable hybrids across locations and/or hybrids specifically adapted to different locations, and (ii) identify ideal test sites for selection of superior hybrids in the two countries. Genotype, country, year, location (country), and their interactive effects were significant (P < 0·01) for grain yield, days to anthesis and silking, anthesis‐silking interval, plant and ear aspects, and ears per plant. Mean grain yield of the hybrids ranged from 3177 kg ha−1 for EWH‐5 to 4596 kg ha−1 for EWH‐29. The genotype main effects plus genotype × environment interaction (GGE) biplot analysis revealed that EWH‐29, EWH‐8, and EWH‐30 did not differ significantly in grain yield and were the most stable hybrids in both countries, whereas EWH‐26 and EWH‐32 were the most stable hybrids only in Ghana. The GGE biplot analysis identified Samaru, Kafin Soli, and Minjibir in Nigeria and Nyankpala, Damongo, and Fumesua in Ghana as the most discriminating locations. Minjibir (Nigeria) and Nyankpala (Ghana), being most discriminating and representative locations, were considered the ideal testing sites for the respective countries. The type of cultivars evaluated determined the most suitable locations for multilocation testing within Ghana and Nigeria. Whereas hybrids EWH‐29, EWH‐8, and EWH‐30 should be suitable for production in Nigeria, EWH‐26 and EWH‐32 should be promoted for production in Ghana.

Gains in Genetic Enhancement of Early Maturing Maize Hybrids Developed during Three Breeding Periods under Striga-Infested and Striga-Free Environments

“…The significance of hybrid × environment interaction as well as period × environment interaction effects for most measured traits, including grain yield in both Striga-infested and optimal research environments, signified contrasting performance of the hybrids under the research conditions. This result emphasized the importance of testing genotypes in multiple environments, in years, and locations prior to recommendations for commercialization [20]. The high estimates of repeatability recorded for several traits in both research environments implied that the hybrids would be consistent in the expression of the measured traits in the research environments.…”

Analysis of genotype-environment interactions of silage maize cultivars under environmental trials

“…The AMMI model could be used to thoroughly analyze GEI interaction information, and the AMMI model was significantly better than traditional regression models. Therefore, the AMMI model could effectively overcome the limitations of linear regression analysis in evaluating the stability of plant genotypes (Oyekunle et al 2017). -and ** same as in Table 3.…”

Genetic Variation of Growth Traits and Genotype-by-Environment Interactions in Clones of Catalpa bungei and Catalpa fargesii f. duclouxii

“…The genotype and genotype × environment (GGE) model overcomes this defect by considering the effects of both genotype and genotype × environment. To date, GGE has been widely used to evaluate the growth stability in crop yield [18][19][20]. However, as the majority of crops are therophytes or biennials, GEI studies of crops mostly focused on site effects.…”