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The success of a hybrid breeding program is dependent on available heterotic patterns for exploitation of grain-yield heterosis. The efficiency of the assignment of germplasm lines into heterotic groups is a prerequisite for obtaining useful heterotic patterns among germplasm lines. A total of 256 maize hybrids, comprising 244 top crosses, six diallel cross hybrids, and six checks, were grown under Striga infestation, drought, and optimal conditions, from 2015 to 2017. The study determined the combining abilities of the parental inbreds, classified the inbreds into heterotic groups, and compared the efficiencies of the following four grouping methods for classifying the inbreds: specific combining ability (SCA) effect of grain yield; general combining ability (GCA) effects of multiple traits (HGCAMT); SCA and GCA (HSGCA) for yield; and single nucleotide polymorphism-based genetic distance (SNP-based genetic distance (GD)). Significant GCA and/or SCA mean squares were revealed for most measured traits in all test environments. Sums of squares (SS) due to GCA were higher than SCA SS for measured traits in all test environments. The HSGCA, SCA, and SNP-based GD methods identified four heterotic groups, whereas the HGCAMT identified three groups, in all environments. The additive gene effect was preponderant in the inheritance of most measured traits. The efficiencies of the grouping methods varied with the test environments. The HSGCA and SCA methods were the most efficient for grouping in all test conditions. For practical breeding purposes, the HGCAMT and HSGCA methods were recommended under Striga infestation and drought, respectively. The heterotic patterns, which were revealed in this study, were effective for planning hybridization schemes for developing high-yielding, Striga-tolerant/resistant, and drought-tolerant maize hybrids for stressful environments.

Efficiencies of Heterotic Grouping Methods for Classifying Early Maturing Maize Inbred Lines