Groundnut is an important food and oil crop in the semiarid tropics, contributing to household food consumption and cash income. In Asia and Africa, yields are low attributed to various production constraints. This review paper highlights advances in genetics, genomics and breeding to improve the productivity of groundnut. Genetic studies concerning inheritance, genetic variability and heritability, combining ability and trait correlations have provided a better understanding of the crop's genetics to develop appropriate breeding strategies for target traits. Several improved lines and sources of variability have been identified or developed for various economically important traits through conventional breeding. Significant advances have also been made in groundnut genomics including genome sequencing, marker development and genetic and trait mapping. These advances have led to a better understanding of the groundnut genome, discovery of genes/variants for traits of interest and integration of marker‐assisted breeding for selected traits. The integration of genomic tools into the breeding process accompanied with increased precision of yield trialing and phenotyping will increase the efficiency and enhance the genetic gain for release of improved groundnut varieties.

Legumes are important components of sustainable agricultural production, food, nutrition and income systems of developing countries. In spite of their importance, legume crop production is challenged by a number of biotic (diseases and pests) and abiotic stresses (heat, frost, drought and salinity), edaphic factors (associated with soil nutrient deficits) and policy issues (where less emphasis is put on legumes compared to priority starchy staples). Significant research and development work have been done in the past decade on important grain legumes through collaborative bilateral and multilateral projects as well as the CGIAR Research Program on Grain Legumes (CRP‐GL). Through these initiatives, genomic resources and genomic tools such as draft genome sequence, resequencing data, large‐scale genomewide markers, dense genetic maps, quantitative trait loci (QTLs) and diagnostic markers have been developed for further use in multiple genetic and breeding applications. Also, these mega‐initiatives facilitated release of a number of new varieties and also dissemination of on‐the‐shelf varieties to the farmers. More efforts are needed to enhance genetic gains by reducing the time required in cultivar development through integration of genomics‐assisted breeding approaches and rapid generation advancement.

Early leaf spot (ELS) and late leaf spot (LLS) diseases are the two most destructive groundnut diseases in Ghana resulting in ≤ 70% yield losses which is controlled largely by chemical method. To develop leaf spot resistant varieties, the present study was undertaken to identify single nucleotide polymorphism (SNP) markers and putative candidate genes underlying both ELS and LLS. In this study, six multi-locus models of genome-wide association study were conducted with the best linear unbiased predictor obtained from 294 African groundnut germplasm screened for ELS and LLS as well as image-based indices of leaf spot diseases severity in 2020 and 2021 and 8,772 high-quality SNPs from a 48 K SNP array Axiom platform. Ninety-seven SNPs associated with ELS, LLS and five image-based indices across the chromosomes in the 2 two sub-genomes. From these, twenty-nine unique SNPs were detected by at least two models for one or more traits across 16 chromosomes with explained phenotypic variation ranging from 0.01 - 62.76%, with exception of chromosome (Chr) 08 (Chr08), Chr10, Chr11, and Chr19. Seventeen potential candidate genes were predicted at ± 300 kbp of the stable/prominent SNP positions (12 and 5, down- and upstream, respectively). The results from this study provide a basis for understanding the genetic architecture of ELS and LLS diseases in African groundnut germplasm, and the associated SNPs and predicted candidate genes would be valuable for breeding leaf spot diseases resistant varieties upon further validation.

Soybean [Glycine max (L.) Merrill] is an important oilseed crop worldwide and it has recently become the crop of interest in Ghana. In this study, 142 soybean accessions were genotyped with 34 SSR markers and concurrently evaluated for five quantitative and two qualitative phenotypic traits. Twenty‐nine of the SSR markers were polymorphic with mean allele number of 5.3, polymorphic information content (PIC) of 0.51 and gene diversity of 0.55. Molecular analysis based on unweighted paired group arithmetic mean (UPGMA) clustering and principal coordinate analysis (PCoA) was similar in explaining the extent of diversity within the accessions. Structure analysis placed most of the accessions into two subpopulations with 18 (12.7%) as admixtures. Principal component analysis (PCA) based on phenotypic traits revealed two clusters. Both UPGMA clustering‐based SSR data and PCA from phenotypic data showed similar results. The assembled germplasm is genetically diverse with high variation in flowering and maturity period, and key yield components which could be exploited in developing superior varieties well adapted to Ghana and West Africa.

Groundnut, the most important grain legume in Ghana, is largely cultivated under rainfed conditions within the Guinea savanna zone of the country. The pods and haulms are important sources of income for smallholder farmers in the region. There is an emerging market for groundnut haulms as livestock feed in Ghana. A population of 30 groundnut genotypes were evaluated for yield (pod and haulm) and its components as well as good haulm nutritive value. High significant differences were observed among the genotypes for all agronomic traits. Average pod yield ranged from 1.6 to 5.7 t/ha with SAMNUT 23 and ICGV-IS 13081 being the most productive. Eight out of the 30 genotypes produced haulm yields above 8 t/ha. There was no significant difference among genotypes for in vitro gas production, digestible organic matter, ash, neutral detergent fibre, and metabolizable energy. However, crude protein, crude fibre, and acid detergent fibre were significantly different. Crude protein content was highest (12.53%) in GAF 1723 and lowest (8.00%) in ICGV-IS 08837. Genotypes GAF 1723, ICGV 00064, and ICGV-IS 13998 combined good pod/haulm yield with high haulm nutritive quality. Their utilization will improve farmers’ income and livelihoods in the Guinea savanna of Ghana.

In this paper, we present a procedure for implementing field-based high-throughput plant phenotyping (HTPP) that can be used in resource-constrained research programs. The procedure relies on opensource tools with the only expensive item being one-off purchase of a drone. It includes acquiring images of the field of interest, stitching the images to get the entire field in one image, calculating and extracting the vegetation indices of the individual plots, and analyzing the extracted indices according to the experimental design. Two populations of groundnut genotypes with different maturities were evaluated for their reaction to early and late leaf spot (ELS, LLS) diseases under field conditions in 2020 and 2021. Each population was made up of 12 genotypes in 2020 and 18 genotypes in 2021. Evaluation of the genotypes was done in four locations in each year. We observed a strong correlation between the vegetation indices and the area under the disease progress curve (AUDPC) for ELS and LLS. However, the strength and direction of the correlation depended upon the time of disease onset, level of tolerance among the genotypes and the physiological traits the vegetation indices were associated with. In 2020, when the disease was observed to have set in late in medium duration population, at the beginning of the seed stage (R5), normalized green-red difference index (NGRDI) and variable atmospheric resistance index (VARI) derived at the beginning pod stage (R3) had a positive relationship with the AUDPC for ELS, and LLS. On the other hand, NGRDI and VARI derived from images taken at R5, and physiological maturity (R7) had negative relationships with AUDPC for ELS, and LLS. In 2021, when the disease was observed to have set in early (at R3) also in medium duration population, a negative relationship was observed between NGRDI and VARI and AUDPC for ELS and LLS, respectively. We found consistently negative relationships of NGRDI and VARI with AUDPC for ELS and LLS, respectively, within the short duration population in both years. Canopy cover (CaC), green area (GA), and greener area (GGA) only showed negative relationships with AUDPC for ELS and LLS when the disease caused yellowing and defoliation. The rankings of some genotypes changed for NGRDI, VARI, CaC, GA, GGA, and crop senescence index (CSI) when lesions caused by the infections of ELS and LLS became severe, although that did not affect groupings of genotypes when analyzed with principal component analysis. Notwithstanding, genotypes that consistently performed well across various reproductive stages with respect to the vegetation indices constituted the top performers when ELS, LLS, haulm, and pod yields were jointly considered.