Secondary metabolites are among the major contributors of host-plant resistance. Cowpea produces secondary metabolites that are known to enhance resistance to insect pests including flower bud thrips. However, environmental conditions tend to affect the production of secondary metabolites, thereby affecting the response of the host plants to insect pest. The objective of this study was to determine the effect of the genotype × environment interaction on the production of secondary metabolites and flower bud thrips resistance in cowpea. Six cowpea genotypes were evaluated for flower bud thrips damage and the contents of flavonoids, antioxidants, phenolics, proteins, lignin, tannins and reducing sugars in four environments with varying temperatures and rainfall patterns. The data collected were subjected to the analysis of variance and genotype and genotype × environment (GGE) analysis. Flower thrips damage, and the contents of flavonoids, antioxidants, lignin, tannins and reducing sugars varied significantly (p < 0.001) among genotypes. Genotype Sanzi produced high levels of antioxidants, while TVU-9820 led in phenolic concentrations respectively. Metabolite contents were significantly (p < 0.001) different among environments, with the long rain season of field experiments led to increased production of flavonoids, proteins, lignin and tannins. A resistant genotype, TVU-3804, produced relatively stable contents of flavonoids, antioxidants, phenolics, proteins and reducing sugars across environments. In this study, the environment influenced the concentration of the metabolites, which in turn affected the cowpea’s resistance to flower bud thrips.

Soybean is a high oil and protein-rich legume with several production constraints. Globally, several fungi, viruses, nematodes, and bacteria cause significant yield losses in soybean. Coniothyrium glycines (CG), the causal pathogen for red leaf blotch disease, is the least researched and causes severe damage to soybean. The identification of resistant soybean genotypes and mapping of genomic regions associated with resistance to CG is critical for developing improved cultivars for sustainable soybean production. This study used single nucleotide polymorphism (SNP) markers generated from a Diversity Arrays Technology (DArT) platform to conduct a genome-wide association (GWAS) analysis of resistance to CG using 279 soybean genotypes grown in three environments. A total of 6395 SNPs was used to perform the GWAS applying a multilocus model Fixed and random model Circulating Probability Unification (FarmCPU) with correction of the population structure and a statistical test p-value threshold of 5%. A total of 19 significant marker–trait associations for resistance to CG were identified on chromosomes 1, 5, 6, 9, 10, 12, 13, 15, 16, 17, 19, and 20. Approximately 113 putative genes associated with significant markers for resistance to red leaf blotch disease were identified across soybean genome. Positional candidate genes associated with significant SNP loci-encoding proteins involved in plant defense responses and that could be associated with soybean defenses against CG infection were identified. The results of this study provide valuable insight for further dissection of the genetic architecture of resistance to CG in soybean. They also highlight SNP variants and genes useful for genomics-informed selection decisions in the breeding process for improving resistance traits in soybean.

Soybean (Glycine max (L.) is an important oil crop with production below the real need in Africa. To increase the production, substantial upgrading must be accomplished by enlarging the genetic potential of new cultivars that relays on the parents' genetic diversity. We aimed to assess the genetic diversity and the population structure of soybean accessions, therefore, evaluate soybean value in terms of use for breeding purposes. To accomplish this, a set of 282 soybean accessions were genotyped using the Diversity Array Technology Sequencing with a high throughput of the Single-nucleotide polymorphisms (SNPs). A total of 6,935 high-quality SNPs were identified across the whole soybean genome. The mean value of genetic diversity, major alleles frequency, minor alleles frequency, expected heterozygosity, and the polymorphism information content was respectively estimated at 0.35, 0.77, 0.22, 0.33, and 0.29. The analysis of molecular variance reveals that the variance among the populations is lower than the variance within the populations. The soybean accessions could be classified into two groups based on the model-based population structure and the principal coordinate analysis or into three groups based on the discriminant analysis of the principal component and the Neighbor-joining tree. The information provided in this study will be helpful for breeders.