Genetic trends for yield and key agronomic traits in pre-commercial and commercial maize varieties between 2008 and 2020 in Uganda.

Estimating genetic gains is vital to optimize breeding programs for increased efficiency. Genetic gains should translate into productivity gains if returns to investments in breeding and impact are to be realized. The objective of this study was to estimate genetic gain for grain yield and key agronomic traits in pre-commercial and commercial maize varieties from public and private breeding programs tested in (i) national performance trials (NPT), (ii) era trial and, (iii) compare the trends with the national average.

Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils.

Genomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTSs) were designed.

On-farm performance and farmers' participatory assessment of new stress-tolerant maize hybrids in Eastern Africa.

The development and deployment of high-yielding stress tolerant maize hybrids are important components of the efforts to increase maize productivity in eastern Africa. This study was conducted to: i) evaluate selected, stress-tolerant maize hybrids under farmers' conditions; ii) identify farmers' selection criteria in selecting maize hybrids; and iii) have farmers evaluate the new varieties according to those criteria. Two sets of trials, one with 12 early-to-intermediate maturing and the other with 13 intermediate-to-late maturing hybrids, improved for tolerance to multiple stresses common in farmers' fields in eastern Africa (drought, northern corn leaf blight, gray leaf spot, common rust, maize streak virus), were evaluated on-farm under smallholder farmers' conditions in a total of 42 and 40 environments (site-year-management combinations), respectively, across Kenya, Uganda, Tanzania and Rwanda in 2016 and 2017.

Maize Combined Insect Resistance Genomic Regions and Their Co-localization With Cell Wall Constituents Revealed by Tissue-Specific QTL Meta-Analyses.

Combinatorial insect attacks on maize leaves, stems, and kernels cause significant yield losses and mycotoxin contaminations. Several small effect quantitative trait loci (QTL) control maize resistance to stem borers and storage pests and are correlated with secondary metabolites. However, efficient use of QTL in molecular breeding requires a synthesis of the available resistance information.