• New stress-tolerant maize hybrids were tested in four East African countries. • They were evaluated by 2,0252025 farmers (55% women) at 27 sites in Kenya and Rwanda. • New hybrids had 18% higher yields than commercial checks under farmers’ conditions. • Their yields were similar to those of commercial checks under optimal conditions. • Farmers generally gave the highest scores to the hybrids with the highest yields.

Several species of herbivores feed on maize in field and storage setups, making the development of multiple insect resistance a critical breeding target. In this study, an association mapping panel of 341 tropical maize lines was evaluated in three field environments for resistance to fall armyworm (FAW), whilst bulked grains were subjected to a maize weevil (MW) bioassay and genotyped with Diversity Array Technology’s single nucleotide polymorphisms (SNPs) markers. A multi-locus genome-wide association study (GWAS) revealed 62 quantitative trait nucleotides (QTNs) associated with FAW and MW resistance traits on all 10 maize chromosomes, of which, 47 and 31 were discovered at stringent Bonferroni genome-wide significance levels of 0.05 and 0.01, respectively, and located within or close to multiple insect resistance genomic regions (MIRGRs) concerning FAW, SB, and MW. Sixteen QTNs influenced multiple traits, of which, six were associated with resistance to both FAW and MW, suggesting a pleiotropic genetic control. Functional prioritization of candidate genes (CGs) located within 10–30 kb of the QTNs revealed 64 putative GWAS-based CGs (GbCGs) showing evidence of involvement in plant defense mechanisms. Only one GbCG was associated with each of the five of the six combined resistance QTNs, thus reinforcing the pleiotropy hypothesis. In addition, through in silico co-functional network inferences, an additional 107 network-based CGs (NbCGs), biologically connected to the 64 GbCGs, and differentially expressed under biotic or abiotic stress, were revealed within MIRGRs. The provided multiple insect resistance physical map should contribute to the development of combined insect resistance in maize.

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. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW-resistance traits, and for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and these were at least two-fold those from BLUEs. For PBTS, FAW resistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant, since a positive correlation (R = 0.92***) between TS size and PAs was observed for RBTS, and for the PBTS, it was negative (R = 0.44**). This study pioneered the use of GS for maize resistance to insect pests in sub-Saharan Africa.

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 (PA) 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 BS was the remainder whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTS) were designed. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW resistance traits, and, for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and, these were at least two-fold those from BLUEs. For PBTS, FAW resistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant since a positive correlation (R=0.92***) between TS size and PAs was observed for RBTS and, for the PBTS, it was negative (R=0.44**). This study pioneers the use of GS for maize resistance to insect pests in sub-Saharan Africa.

Agriculture employs 65–70% of the labour force and is therefore pivotal to Uganda’s socio-economic transformation. Farmers grow diverse crops for food, nutrition and income security. This diversity provides insurance and enhances resilience and sustainable production under climate change-induced stresses such as drought, pests and diseases. The nature of food systems and biodiversity is linked to cultural norms and heritage. Landraces provide genetic resources that drive diverse trait requirements across cultural setups. The dominant crops in Uganda, including bananas, cassava, sweet potato, coffee, and cocoa, which are the major drivers of the national economy in terms of food, income, employment, and exports, are largely dependent on landraces. These landraces have evolved over generations through farmer selections and advancements. Through natural and farmer selections, elite, high-yielding and resilient cultivars are being utilised. Consequently, landraces serve as vital trait reservoirs for crop improvement. It is for the same reason that the plant genetic resources centre of Uganda gives due consideration to landraces in its conservation agenda, guided by the National Development Plan IV and other frameworks. This chapter elaborates on the significance of landraces in maintaining biodiversity, unlocking adaptive and consumer-preferred traits, sustainable production and driving the national economy. It also highlights case studies for key crops for which landraces are invaluable genetic resources.

Maize (Zea mays L.) ear rots caused by Aspergillus flavus, Fusarium graminearum and Stenocarpella maydis affect grain quality and are associated with mycotoxins that pose precarious food and feed safety issues. The objective of this study was to determine the inheritance of multiple resistance to major fungal pathogens (Aspergillus flavus, Fusarium graminearum and Stenocarpella maydis) in maize in the tropical Africa. A total of 30 tropical inbred lines with varying resistance to A. flavus and both F. graminearum and S. maydis, were mated in a North Carolina II Design and the progeny consisting of single crosses, test crosses and their parents evaluated for single infection and yield performance. Resistance to the three ear rot pathogens and grain yield was found to be inherited independently. Therefore the three fungal infections had low or negligible effect on grain yield, though adversely reduced the grain quality. Multiple resistance to the three ear rot pathogens was majorly additive in nature. Some non-additive gene effects like dominance and epistasis could be contributing to multiple ear rot resistance. Maize hybrid vigour was found to enhance ear rot resistance.