Maize cultivars with improved grain yields under nitrogen (N) stress are desirable for sub‐Saharan African maize growing environments. This study assesses N uptake, N utilization, and the genotype × environment (G × E) interaction of 16 tropical maize (Zea mays L.) hybrids differing in grain yield under low‐N conditions. Hybrids were evaluated under low‐N, medium‐N, and high‐N at Harare, Zimbabwe, in 2003 and 2004 and at Kiboko, Kenya, in 2003. At maturity, N accumulation in the aboveground biomass ranged from 47 to 278 kg N ha−1 in various experiments. Grain yields ranged from 1.5 to 4.3 Mg ha−1 and 10.6 to 14.9 Mg ha−1 for the same experiments, respectively. Significant G × E interactions were observed which became more pronounced as the difference in N stress intensity between two environments increased. High grain yield under low‐N was consistently associated with higher postanthesis N uptake, increased grain production per unit N accumulated, and an improved N harvest index. Additive main effect and multiplicative interaction analysis identified hybrids with specific adaptation to either low‐N or high‐N environments. Several hybrids produced high yields under both low‐N and high‐N conditions. More detailed studies with these hybrids are required to examine the underlying physiological mechanisms contributing to the N‐use efficiency.

Key message Intensive public sector breeding efforts and public-private partnerships have led to the increase in genetic gains, and deployment of elite climate-resilient maize cultivars for the stress-prone environments in the tropics. Abstract Maize (Zea mays L.) plays a critical role in ensuring food and nutritional security, and livelihoods of millions of resource-constrained smallholders. However, maize yields in the tropical rainfed environments are now increasingly vulnerable to various climate-induced stresses, especially drought, heat, waterlogging, salinity, cold, diseases, and insect pests, which often come in combinations to severely impact maize crops. The International Maize and Wheat Improvement Center (CIMMYT), in partnership with several public and private sector institutions, has been intensively engaged over the last four decades in breeding elite tropical maize germplasm with tolerance to key abiotic and biotic stresses, using an extensive managed stress screening network and on-farm testing system. This has led to the successful development and deployment of an array of elite stress-tolerant maize cultivars across sub-Saharan Africa, Asia, and Latin America. Further increasing genetic gains in the tropical maize breeding programs demands judicious integration of doubled haploidy, high-throughput and precise phenotyping, genomics-assisted breeding, breeding data management, and more effective decision support tools. Multi-institutional efforts, especially public–private alliances, are key to ensure that the improved maize varieties effectively reach the climate-vulnerable farming communities in the tropics, including accelerated replacement of old/obsolete varieties.

Core Ideas Single‐stage and two‐stage analysis of multienvironment trials yield very similar results. Single‐stage and two‐stage analysis are identical when the same set of variance values is used. Modeling genotypes as random helps to exploit correlations between agro‐ecological zones. In stage‐wise analysis, genotypes need to be taken as fixed through all stages except the last. Fully efficient two‐stage analysis is similar in spirit to meta‐analysis. Multienvironment trials can be analyzed using single‐stage or stage‐wise analysis. Single‐stage analysis is fully efficient, meaning that the estimators can be expected to be as close as possible to the corresponding true genotypic values, and so is often deemed preferable to two‐stage analysis. However, two‐stage analysis is often favored in practice over single‐stage analysis in the case of large datasets because of the larger computational burden of the latter and because the former allows separate analyses of individual trials in the first stage, accounting for any specifics of each trial. In this study we demonstrate the similarities of results of single‐stage and two‐stage analysis when information on mean estimates and the associated variance–covariance matrix is forwarded from the first stage to the second stage using four examples with maize (Zea mays L.) trial data from Ethiopia. A new fully efficient and an approximate two‐stage method with diagonal weighting matrix are used for weighting in the second stage. We extend the method to three‐stage analysis for multienvironment trials when sites are stratified by agro‐ecological zones and demonstrate how to obtain best linear unbiased predictions of genotype effects per zone using the information from neighboring zones. Two macros that compute weights for use in the fully efficient and diagonal weighting approaches are provided.

BackgroundQuality control (QC) analysis is an important component in maize breeding and seed systems. Genotyping by next-generation sequencing (GBS) is an emerging method of SNP genotyping, which is being increasingly adopted for discovery applications, but its suitability for QC analysis has not been explored. The objectives of our study were 1) to evaluate the level of genetic purity and identity among two to nine seed sources of 16 inbred lines using 191 Kompetitive Allele Specific PCR (KASP) and 257,268 GBS markers, and 2) compare the correlation between the KASP-based low and the GBS-based high marker density on QC analysis.ResultsGenetic purity within each seed source varied from 49 to 100 % for KASP and from 74 to 100 % for GBS. All except one of the inbred lines obtained from CIMMYT showed 98 to 100 % homogeneity irrespective of the marker type. On the contrary, only 16 and 21 % of the samples obtained from EIAR and partners showed ≥95 % purity for KASP and GBS, respectively. The genetic distance among multiple sources of the same line designation varied from 0.000 to 0.295 for KASP and from 0.004 to 0.230 for GBS. Five lines from CIMMYT showed ≤ 0.05 distance among multiple sources of the same line designation; the remaining eleven inbred lines, including two from CIMMYT and nine from Ethiopia showed higher than expected genetic distances for two or more seed sources. The correlation between the 191 KASP and 257,268 GBS markers was 0.88 for purity and 0.93 for identity. A reduction in the number of GBS markers to 1,343 decreased the correlation coefficient only by 0.03.ConclusionsOur results clearly showed high discrepancy both in genetic purity and identity by the origin of the seed sources (institutions) irrespective of the type of genotyping platform and number of markers used for analyses. Although there were some numerical differences between KASP and GBS, the overall conclusions reached from both methods was basically similar, which clearly suggests that smaller subset of preselected and high quality markers are sufficient for QC analysis that can easily be done using low marker density genotyping platforms, such as KASP. Results from this study would be highly relevant for plant breeders and seed system specialists.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2180-2) contains supplementary material, which is available to authorized users.

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