Drought and high temperature are two major factors limiting maize productivity in sub-Saharan Africa. An increase in temperature above 30 • C reduces yield by 1% under optimal rain-fed condition and by 1.7% under drought stress (DS) and up to 40% under combined drought and heat stress (DSHTS). Approaches that improve performance under the two stresses are essential to sustain productivity. The objectives of this study were to (i) assess the extent of variation in tolerance to DSHTS from among the existing best drought tolerant (DT) hybrids; (ii) examine the response patterns of the hybrids to DSHTS; (iii) identify traits that contributed to better performance under DSHTS; and (iv) select the best hybrids with tolerance to DSHTS stress. We evaluated 40 DT hybrids under DSHTS, DS, and well-watered (WW) conditions for three years. Highly significant (p < 0.001) differences were found among hybrids for grain yield and other traits. Moderately to low repeatability values were detected for grain yield under DS (0.63) and under DSHTS (0.48). Grain yield under DS was not correlated with grain yield under DSHTS (r = 0.29; p = 0.06), but it was correlated with grain yield under WW (r = 0.74; p < 0.001). Grain yield was strongly correlated with ears per plant, ear and pant aspects, days to anthesis and silking under both DS and DSHTS. Tassel blast accounted for 28% of the yield reduction under DSHTS. The top five DT hybrids produced 9 to 26% more grain yields than the best commercial hybrid. Three hybrids produced high grain yields under DTHTS and DS as well as under WW. These hybrids will be tested further in collaboration with partners for possible release.

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Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize.

Vitamin A Deficiency (VAD) is a major public health problem in Sub-Saharan Africa affecting 33 million preschool-age children. Enrichment of maize varieties with provitamin A could provide sustainable and affordable solution to VAD. This study was conducted to understand the extent of GEI effects on both grain yield and provitamin A content in 21 maize synthetics and identify synthetics combining stable performance with high level provitamin A content across diverse environments in West Africa. Combined analysis of variance found significant (p \ 0.01) GEI effects that prompted further investigation of the GEI magnitude using mixed model with factor analysis. Factors 1 and 2 explained 71% of the total variability. G5, G4, G12, G18, G2 and G14 were broadly adapted to a range of environments and considered the most stable and high yielding. G8, G1, and G10 were specifically adapted to a group of environments. Whereas, G21, G19 and G17 were found to be the worst and unstable genotypes. G4 combined stable performance with high provitamin A content, whereas G20 and G18 were stable but had low provitamin A contents. Three genotypes, G4, G12 and G14 were found to combine stability with high provitamin A contents. These genotypes can be recommended for production in the low-land tropics of West and Central Africa with similar environments.

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