Background/Objectives: Understanding the genetic diversity of soybean genotypes can provide valuable information that guides parental selection and the design of an effective hybridization strategy in a soybean breeding program. In order to identify genetically diverse, complementary, and prospective parental lines for breeding, this study set out to ascertain the genetic diversity, relationships, and population structure among 35 soybean genotypes based on agro-morphological traits and Single Nucleotide Polymorphic (SNP) marker data. Methods/Results: Cluster analysis, based on agro-morphological traits, grouped the studied genotypes into four clusters. The first two principal components accounted for 62.8% of the total phenotypic variation, where days to 50% flowering, days to 95% maturity, grain yield, shattering score, and lodging score had high and positive contributions to the total variation. Using the SNP marker information, mean values of 0.16, 0.19, 0.067, and 0.227 were obtained for minor allele frequency (MAF), polymorphic information content (PIC), observed heterozygosity (Ho), and expected heterozygosity (He), respectively. Using different clustering approaches (admixture population structure, principal component scatter plot, and hierarchical clustering), the studied genotypes were grouped into four major clusters. Conclusions:The agro-morphological and molecular analysis results indicated the existence of moderate genetic diversity among the studied genotypes. The traits identified to be significantly related to yield provide valuable information for the genetic improvement of soybeans for yield.

Soybean [Glycine max (L.) Merrill] is an important crop in southern Africa where it is cultivated in a wide range of agro-ecologies. Both spatial and seasonal variability is high in the region. As a result, breeders aim to release varieties with a fine balance of high productivity potential and stability. Genotype × environment interaction (GEI) limits the selection of superior genotypes in heterogeneous environments consequently slowing down breeding progress. This study determined the magnitude of GEI effects and genotype superiority index of soybean genotypes of different ages across three countries in southern Africa. Forty-two soybean genotypes that were released between 1966 and 2013 were evaluated for two seasons at thirteen diverse locations across the three countries. Additive main effects and multiplicative interaction (AMMI) and genotype superiority index tools were used to analyse both productivity and stability performance of these genotypes. The AMMI analysis showed that grain yield variation due to genotypes, environments main effects and GEI were highly significant (p < 0.001). Environments explained the greatest proportion (77%) of the total treatment sum of squares followed by GEI (17.4%) and genotypes (5.6%), justifying the need for multi-environmental trials over many seasons in this region. The two methods were useful in discriminating and identifying common productive and stable genotypes of different ages. The top four high-yielding (>5.0 tha⁻¹) genotypes displayed both stability and genotype superiority index. These findings have important implications for soybean genotype recommendations, breeding progress, and strategy.

A validated marker system is crucial to running an effective genomics-assisted breeding program. We used 36 Kompetitive Allele-Specific PCR (KASP) markers to genotype 376 clones from the biofortified cassava pipeline, and fingerprinted 93 of these clones with DArTseq markers to characterize breeding materials and evaluate their relationships. The discriminating ability of the 36-quality control (QC) KASP and 6602 DArTseq markers was assessed using 92 clones genotyped in both assays. In addition, trait-specific markers were used to determine the presence or absence of target genomic regions. Hierarchical clustering identified two major groups, and the clusters were consistent with the breeding program origins. There was moderate genetic differentiation and a low degree of variation between the identified groups. The general structure of the population was similar using both assays. Nevertheless, KASP markers had poor resolution when it came to differentiating the genotypes by seed sources and overestimated the prevalence of duplicates. The trait-linked markers did not achieve optimal performance as all markers displayed variable levels of false positive and/or false negative. These findings represent the initial step in the application of genomics-assisted breeding for the biofortified cassava pipeline, and will guide the use of genomic selection in the future.

Regular measurement of realized genetic gain allows plant breeders to assess and review the effectiveness of their strategies, allocate resources efficiently, and make informed decisions throughout the breeding process. Realized genetic gain estimation requires separating genetic trends from nongenetic trends using the linear mixed model (LMM) on historical multi‐environment trial data. The LMM, accounting for the year effect, experimental designs, and heterogeneous residual variances, estimates best linear unbiased estimators of genotypes and regresses them on their years of origin. An illustrative example of estimating realized genetic gain was provided by analyzing historical data on fresh cassava ( Manihot esculenta Crantz) yield in West Africa ( https://github.com/Biometrics‐IITA/Estimating‐Realized‐Genetic‐Gain ). This approach can serve as a model applicable to other crops and regions. Modernization of breeding programs is necessary to maximize the rate of genetic gain. This can be achieved by adopting genomics to enable faster breeding, accurate selection, and improved traits through genomic selection and gene editing. Tracking operational costs, establishing robust, digitalized data management and analytics systems, and developing effective varietal selection processes based on customer insights are also crucial for success. Capacity building and collaboration of breeding programs and institutions also play a significant role in accelerating genetic gains.

Background: Understanding the genetic diversity and population structure of maize inbred lines is fundamental for effective hybrid development and strategic heterosis exploitation. The objective of this study was to refine and validate heterotic groups within a diverse collection of extra-early and early maturing tropical yellow and orange maize inbred lines. A total of 1,437 elite tropical yellow and orange maize inbred lines spanning early and extra-early maturing groups were genotyped using a panel of 3,305 DArTag SNP markers. In addition, the study evaluated 280 hybrids comprising 276 hybrids (from 214 inbred lines crossed with four standard testers) and four commercial checks. The yield performance trials used a 14 × 20 alpha-lattice design with two replicates over two years. Results: Marker-based diversity analysis revealed average marker polymorphism of 0.328, minor allele frequency of 0.265, and expected heterozygosity of 0.315. Principal component analysis (PCA), discriminant analysis of principal components (DAPC), and ancestral admixture analysis revealed three genetic clusters, while phylogenetic analysis supported the existence of two major clusters with groups one and three from DAPC and admixture methods combined into a single phylogenetic group. Several sub-groups were identified within the main genetic pools and maturity rather than kernel color was the major driver of these sub-groups. For operational ease in breeding applications, the lines were assigned to two major heterotic groups. The average performance of the hybrid for grain yield and heterosis estimates from between maturity-based heterotic subgroups were consistently and significantly ( p < 0.001) higher than those from within maturity-based heterotic subgroups. Conclusion: These results provide a robust framework for parental line selection, heterotic grouping, and hybrid breeding strategies, facilitating the development of extra-early and early superior yellow/orange maize hybrids adapted to tropical environments.

Cassava brown streak disease (CBSD) remains the most severe threat to cassava production in the Great Lakes region and Southern Africa. Screening for virus resistance by subjecting cassava to high virus pressure in the epidemic zone (hotspots) is a common but lengthy process because of unpredictable and erratic virus infections requiring multiple seasons for disease evaluation. This study investigated the feasibility of graft-infections to provide a highly controlled infection process that is robust and reproducible to select and eliminate susceptible cassava at the early stages and to predict the resistance of adapted and economically valuable varieties. To achieve this, a collection of cassava germplasm from the Democratic Republic of Congo and a different set of breeding trials comprising two seed nurseries and one preliminary yield trial were established. The cassava varieties OBAMA and NAROCASS 1 infected with CBSD were planted one month after establishment of the main trials in a 50 m² plot to serve as the source of the infection and to provide scions to graft approximately 1 ha. Grafted plants were inspected for virus symptoms and additionally tested by RT-qPCR for sensitive detection of the viruses. The incidence and severity of CBSD and cassava mosaic disease (CMD) symptoms were scored at different stages of plant growth and fresh root yield determined at harvesting. The results from the field experiments proved that graft-infection with infected plants showed rapid symptom development in susceptible cassava plants allowing instant exclusion of those lines from the next breeding cycle. High heritability, with values ranging from 0.63 to 0.97, was further recorded for leaf and root symptoms, respectively. Indeed, only a few cassava progenies were selected while clones DSC260 and two species of M. glaziovii (Glaziovii20210005 and Glaziovii20210006) showed resistance to CBSD. Taken together, grafting scions from infected cassava is a highly efficient and cost-effective method to infect cassava with CBSD even under rugged field conditions. It replaces an erratic infection process with a controlled method to ensure precise screening and selection for virus resistance. The clones identified as resistant could serve as elite donors for introgression, facilitating the transfer of resistance to CBSD.