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Given high animal protein costs, protein deficiency is a prevalent form of malnutrition in sub‐Saharan Africa (SSA). Soybean [Glycine max (L.) Merr.] can provide a cheaper high‐quality protein source and fortify lysine‐limited cereal‐based diets. Breeding soybean for seed composition in SSA requires understanding genotype by environment interactions (G × E). African breeding programs submit cultivars for evaluation in the Pan‐African Soybean Variety Trials (PATs), providing the opportunity to examine G × E across diverse environments. With PAT data, we conducted additive main effects and multiplicative interaction (AMMI) and genotype plus genotype‐by‐environment (GGE) biplot analyses on seed protein and oil content of 17 cultivars grown with two replications in nine environments across Zimbabwe. Across environments, protein ranged from 322.8 to 445.1 g kg−1 and oil ranged from 164.8 to 242.7 g kg−1. For protein AMMI analysis, MAKWACHA performed best for both stability and a combination of stability plus content. For oil AMMI analysis, SC SPIKE performed best for stability and KALEYA performed best for a combination of stability plus content. GGE biplot analyses identified three different mega‐environments for protein and oil, with SC EXPT2, KALEYA, and SC EXPT1 having highest protein content and TGX 2002‐9FM, LUKANGA, and SC EXPT3 having highest oil content. We also evaluated genetic diversity of 19 PAT cultivars through phylogenetic analyses with 1059 USDA Germplasm Resources Information Network (GRIN) diversity panel accessions. We recommend stable and adaptable PAT cultivars to breeders and producers while highlighting genetically distinct accessions with valuable traits as a resource for breeding programs. Core Ideas: This is a comprehensive report on seed composition stability within Pan‐African Soybean Variety Trials (PATs).Genotype by environment interaction explained a significant amount of variation in seed protein and oil content.Additive main effects and multiplicative interaction (AMMI) and genotype plus genotype‐by‐environment (GGE) biplot analyses identified PAT cultivars with the highest stability and adaptability in Zimbabwe.We highlight the genetic relatedness of PAT cultivars relative to USDA Germplasm Resources Information Network (GRIN) diversity panel accessions. Plain Language Summary: Soybean is currently promoted in sub‐Saharan Africa as a high‐quality protein source. Breeding soybean for improved seed composition requires understanding how cultivars interact with these new environments. This study evaluated genotype by environment interactions and the genetic diversity of cultivars grown in the Pan‐African Soybean Variety Trials. We used stability analyses to evaluate how the environment, cultivar, and their interaction impacted protein and oil across Zimbabwe. We identified cultivars with increased protein or oil in specific environments or stable performance across environments. We also compared the genetic diversity of the African cultivars to over 1000 genetically diverse accessions from around the world. Our analyses showed that the African cultivars have relatively low genetic diversity and are most closely related to American accessions. Our results provide valuable resources for improving soybean seed composition in sub‐Saharan Africa. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Thirty soybean [Glycine max (L.) Merr.] genotypes, along with three checks, were evaluated over three seasons across five communes in Benin. The experiments were laid out in an alpha lattice design with three replicates. Additive multiplicative mean interaction (AMMI) and best linear unbiased predictor (BLUP) analysis were combined to assess differential agronomic performance and yield stability among genotypes. There was significant variation (p < 0.001) between genotypes for all traits, with highly significant environmental and genotype × environment interaction (GEI) effects on soybean grain yield (p < 0.001). The likelihood ratio test indicated that both genotype and interaction effects were highly significant (p < 0.001). The low R² (0.21) for GEI reflected the presence of high residual variation in the GEI component, in contrast to the AMMI analysis of variance, which explained a high proportion of the GEI through the first two interaction principal component axes (52%). The very high value of the predictive accuracy (0.89) confirmed the model’s reliability in selecting superior genotypes. The low (0.33) genotypic correlation between environments indicated that it was difficult to select superior genotypes for each environment. Based on the superiority index (weighted average absolute scores from BLUP for yield) of BLUP, simultaneous selection led to the identification of Jenguma 2.67 ± 0.06 t ha−1 as the most stable and productive genotype across environments, followed by Favour 2.34 ± 0.08 t ha−1, and Afayak 2.46 ± 0.08 t ha−1. The agronomic performance of soybean in this study suggested great potential for diversifying cotton-based cropping systems in Benin, thereby improving their sustainability. The effect of these soybean genotypes on the productivity of intercrop combinations and sequences of cash crops, such as cotton, is yet to be investigated. [ABSTRACT FROM AUTHOR]

Pod shattering is a major production constraint of soybean [Glycine max (L.)]. The objectives of this study were to (i) estimate heritability for pod shattering resistance, (ii) determine the frequency of the pod shattering resistance allele pdh1 in the International Institute for Tropical Agriculture (IITA) soybean germplasm and Zambian commercial varieties, and (iii) determine the effectiveness of the DNA marker for the pod shattering resistance allele pdh1. A total of 59 genotypes were evaluated for pod shattering in field trials conducted in Malawi and Zambia and genotyped with a marker for pdh1. TGx2002‐8FM and TGx2002‐9FM were the most resistant among genotypes in early and medium maturity classes and can be used for genetic enhancement of pod shattering resistance in these specific maturity classes. Narrow sense heritability estimates for pod shattering ranged from 0.27 to 0.80. Of the 59 genotypes, 57 (96.6%) carried the resistance allele pdh1 while only two genotypes (3.6%) carried the susceptible allele, suggesting near‐fixation of the resistance allele pdh1 in the IITA germplasm. The marker for pdh1 was highly effective in selecting resistant genotypes. [ABSTRACT FROM AUTHOR]

Artemisia annua is an important medicinal crop used for the production of the anti-malarial compound artemisinin. In order to assist in the production of affordable high quality artemisinin we have carried out an A. annua breeding programme aimed at improving artemisinin concentration and biomass. Here we report on a combining ability analysis of a diallel cross to identify robust parental lines for hybrid breeding. The parental lines were selected based on a range of phenotypic traits to encourage heterosis. The general combining ability (GCA) values for the diallel parental lines correlated to the positive alleles of quantitative trait loci (QTL) in the same parents indicating the presence of beneficial alleles that contribute to parental performance. Hybrids generated from crossing specific parental lines with good GCA were identified as having an increase in both artemisinin concentration and biomass when grown either in glasshouse or experimental field trials and compared to controls. This study demonstrates that combining ability as determined by a diallel cross can be used to identify elite parents for the production of improved A. annua hybrids. Furthermore, the selection of material for breeding using this approach was found to be consistent with our QTL-based molecular breeding approach. [ABSTRACT FROM AUTHOR]