George Mahuku

Maize Production in a Changing Climate: Impacts, Adaptation, and Mitigation Strategies

Abstract Plant breeding and improved management options have made remarkable progress in increasing crop yields during the past century. However, climate change projections suggest that large yield losses will be occurring in many regions, particularly within sub-Saharan Africa. The development of climate-ready germplasm to offset these losses is of the upmost importance. Given the time lag between the development of improved germplasm and adoption in farmers’ fields, the development of improved breeding pipelines needs to be a high priority. Recent advances in molecular breeding provide powerful tools to accelerate breeding gains and dissect stress adaptation. This review focuses on achievements in stress tolerance breeding and physiology and presents future tools for quick and efficient germplasm development. Sustainable agronomic and resource management practices can effectively contribute to climate change mitigation. Management options to increase maize system resilience to climate-related stresses and mitigate the effects of future climate change are also discussed.

Genomic Selection and Prediction in Plant Breeding

The availability of thousands of genome-wide molecular markers has made possible the use of genomic selection in plants and animals. However, the evaluation of models for genomic selection in plant breeding populations remains limited. In this study, we provide an overview of several models for genomic selection, whose predictive ability we investigate using two plant data sets. The first data set comprises historical phenotypic records of a series of wheat (Triticum aestivum L.) trials evaluated in 10 environments and recently generated genomic data. The second data set pertains to international maize (Zea mays L.) trials in which two disease traits (Exserohilum turcicum and Cercospora zeae-maydis) of maize lines evaluated in five environments were measured. Results showed that models including marker information yielded important gains in predictive ability relative to that of a pedigree-based model, this with a modest number of markers. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction was an important component of genetic variability. Overall, the study provided evidence from real populations indicating that genomic selection could be an effective tool for improving traits of economic importance in commercial crops.

Genome-enabled prediction of genetic values using radial basis function neural networks

The availability of high density panels of molecular markers has prompted the adoption of genomic selection (GS) methods in animal and plant breeding. In GS, parametric, semi-parametric and non-parametric regressions models are used for predicting quantitative traits. This article shows how to use neural networks with radial basis functions (RBFs) for prediction with dense molecular markers. We illustrate the use of the linear Bayesian LASSO regression model and of two non-linear regression models, reproducing kernel Hilbert spaces (RKHS) regression and radial basis function neural networks (RBFNN) on simulated data and real maize lines genotyped with 55,000 markers and evaluated for several trait–environment combinations. The empirical results of this study indicated that the three models showed similar overall prediction accuracy, with a slight and consistent superiority of RKHS and RBFNN over the additive Bayesian LASSO model. Results from the simulated data indicate that RKHS and RBFNN models captured epistatic effects; however, adding non-signal (redundant) predictors (interaction between markers) can adversely affect the predictive accuracy of the non-linear regression models.

Cloning and characterization of a putative GS3 ortholog involved in maize kernel development.

The GS3 gene was the first identified gene controlling the grain size in rice. It has been proven to be involved in the evolution of grain size during domestication. We isolated the maize ortholog, ZmGS3 and investigated its role in the evolution of maize grain size. ZmGS3 has five exons encoding a protein with 198 amino acids, and has domains in common with the rice GS3 protein. Compared with teosinte, maize has reduced nucleotide diversity at ZmGS3, and the reduction is comparable to that found in neutrally evolving maize genes. No positive selection was detected along the length of the gene using either the Hudson–Kreitman–Aguadé or Tajima’s D tests. Phylogenetic analysis reveals a distribution of maize sequences among two different clades, with one clade including related teosinte sequences. The nucleotide polymorphism analysis, selection test and phylogenetic analysis reveal that ZmGS3 has not been subjected to selection, and appears to be a neutrally evolving gene. In maize, ZmGS3 is primarily expressed in immature ears and kernels, implying a role in maize kernel development. Association mapping analysis revealed one polymorphism in the fifth exon that is significantly associated with kernel length in two environments. Also one polymorphism in the promoter region was found to affect hundred kernel weight in both environments. Collectively, these results imply that ZmGS3 is involved in maize kernel development but with different functional polymorphisms and thus, possibly different mechanisms from that of the rice GS3 gene.

Maize Production in a Changing Climate

Abstract Plant breeding and improved management options have made remarkable progress in increasing crop yields during the past century. However, climate change projections suggest that large yield losses will be occurring in many regions, particularly within sub-Saharan Africa. The development of climate-ready germplasm to offset these losses is of the upmost importance. Given the time lag between the development of improved germplasm and adoption in farmers’ fields, the development of improved breeding pipelines needs to be a high priority. Recent advances in molecular breeding provide powerful tools to accelerate breeding gains and dissect stress adaptation. This review focuses on achievements in stress tolerance breeding and physiology and presents future tools for quick and efficient germplasm development. Sustainable agronomic and resource management practices can effectively contribute to climate change mitigation. Management options to increase maize system resilience to climate-related stresses and mitigate the effects of future climate change are also discussed.

Dispensing synthetic green leaf volatiles in maize fields increases the release of sesquiterpenes by the plants, but has little effect on the attraction of pest and beneficial insects.

Maize plants respond to feeding by arthropod herbivores by producing a number of secondary plant compounds, including volatile organic compounds (VOCs). These herbivore-induced VOCs are not only known to attract natural enemies of the herbivores, but they may also prime inducible defences in neighbouring plants, resulting in stronger and faster defence responses in these VOC-exposed plants. Among the compounds that cause this priming effect, green leaf volatiles (GLVs) have received particular attention, as they are ubiquitous and rapidly emitted upon damage. In this study, we investigated their effects under realistic conditions by applying specially devised dispensers to release four synthetic GLVs at physiologically relevant concentrations in a series of experiments in maize fields. We compared the VOC emission of GLV-exposed maize plants to non-exposed plants and monitored the attraction of herbivores and predators, as well as parasitism of the caterpillar Spodoptera frugiperda, the most common herbivore in the experimental maize fields. We found that maize plants that were exposed to GLVs emitted increased quantities of sesquiterpenes compared to non-exposed plants. In several replicates, herbivorous insects, such as adult Diabrotica beetles and S. frugiperda larvae, were observed more frequently in GLV-treated plots and caused more damage to GLV-exposed plants than to non-exposed plants. Parasitism of S. frugiperda was only weakly affected by GLVs and overall parasitism rates of S. frugiperda were similar in GLV-exposed and non-exposed plots. The effects on insect presence depended on the distance from the GLV-dispensers at which the plants were located. The results are discussed in the context of strategies to improve biological control by enhancing plant-mediated attraction of natural enemies.

Genome-wide association mapping reveals novel sources of resistance to northern corn leaf blight in maize

BackgroundNorthern corn leaf blight (NCLB) caused by Exserohilum turcicum is a destructive disease in maize. Using host resistance to minimize the detrimental effects of NCLB on maize productivity is the most cost-effective and appealing disease management strategy. However, this requires the identification and use of stable resistance genes that are effective across different environments.ResultsWe evaluated a diverse maize population comprised of 999 inbred lines across different environments for resistance to NCLB. To identify genomic regions associated with NCLB resistance in maize, a genome-wide association analysis was conducted using 56,110 single-nucleotide polymorphism markers. Single-marker and haplotype-based associations, as well as Anderson-Darling tests, identified alleles significantly associated with NCLB resistance. The single-marker and haplotype-based association mappings identified twelve and ten loci (genes), respectively, that were significantly associated with resistance to NCLB. Additionally, by dividing the population into three subgroups and performing Anderson-Darling tests, eighty one genes were detected, and twelve of them were related to plant defense. Identical defense genes were identified using the three analyses.ConclusionAn association panel including 999 diverse lines was evaluated for resistance to NCLB in multiple environments, and a large number of resistant lines were identified and can be used as reliable resistance resource in maize breeding program. Genome-wide association study reveals that NCLB resistance is a complex trait which is under the control of many minor genes with relatively low effects. Pyramiding these genes in the same background is likely to result in stable resistance to NCLB.