Selecting elite groundnut (Arachis hypogaea L) genotypes for symbiotic N nutrition, water-use efficiency and pod yield at three field sites, using 15N and 13C natural abundance.

About 70% of the groundnut (Arachis hypogaea L.) produced in Ghana is from the Guinea savanna. However, low soil nutrients, especially N, together with erratic rainfall distribution have often resulted in poor grain yield. The aim of this study was to evaluate plant growth, N2-fixing efficiency, N contribution, water-use efficiency and pod yield of 21 elite groundnut genotypes in the Guinea savanna of Ghana, using the 15N natural abundance technique. The data revealed significant variations in plant growth, symbiotic N contribution, and pod yield among the 21 genotypes tested at each field site. Average N contribution by groundnut genotypes ranged from 48 to 108 kg N ha-1. Also, mean pod yield ranged from 0.58 to 2.1 t ha-1. Genotypes ICGV-IS 08837, ICG 6222, ICGV 03315 and NKATIESARI demonstrated superior plant growth, symbiotic N contribution and greater pod yield. In fact, ICGV-IS 08837 yielded almost 2.5 fold more than CHINESE which is the most widely cultivated variety in the region. Genotypes ICGV-IS 08837, ICG 6222, ICGV 03315 and ICGV 99247 are therefore recommended for development into varieties for the Guinea savanna of Ghana. Genotypes ICG (FDRS) 4, ICGV00362 and ICGV99247 exhibited increased water-use efficiency, but were low in N2 fixation and N contribution, and would therefore be good parental material in breeding programs aimed at enhancing water-use efficiency in high N2-fixing genotypes.

The groundnut improvement network for Africa (GINA) germplasm collection: a unique genetic resource for breeding and gene discovery.

Cultivated peanut or groundnut (Arachis hypogaea L.) is a grain legume grown in many developing countries by smallholder farmers for food, feed, and/or income. The speciation of the cultivated species, that involved polyploidization followed by domestication, greatly reduced its variability at the DNA level. Mobilizing peanut diversity is a prerequisite for any breeding program for overcoming the main constraints that plague production and for increasing yield in farmer fields. In this study, the Groundnut Improvement Network for Africa assembled a collection of 1,049 peanut breeding lines, varieties, and landraces from 9 countries in Africa. The collection was genotyped with the Axiom_Arachis2 48K SNP array and 8,229 polymorphic single nucleotide polymorphism (SNP) markers were used to analyze the genetic structure of this collection and quantify the level of genetic diversity in each breeding program. A supervised model was developed using dapc to unambiguously assign 542, 35, and 172 genotypes to the Spanish, Valencia, and Virginia market types, respectively. Distance-based clustering of the collection showed a clear grouping structure according to subspecies and market types, with 73% of the genotypes classified as fastigiata and 27% as hypogaea subspecies. Using STRUCTURE, the global structuration was confirmed and showed that, at a minimum membership of 0.8, 76% of the varieties that were not assigned by dapc were actually admixed. This was particularly the case of most of the genotype of the Valencia subgroup that exhibited admixed genetic heritage. The results also showed that the geographic origin (i.e. East, Southern, and West Africa) did not strongly explain the genetic structure. The gene diversity managed by each breeding program, measured by the expected heterozygosity, ranged from 0.25 to 0.39, with the Niger breeding program having the lowest diversity mainly because only lines that belong to the fastigiata subspecies are used in this program. Finally, we developed a core collection composed of 300 accessions based on breeding traits and genetic diversity. This collection, which is composed of 205 genotypes of fastigiata subspecies (158 Spanish and 47 Valencia) and 95 genotypes of hypogaea subspecies (all Virginia), improves the genetic diversity of each individual breeding program and is, therefore, a unique resource for allele mining and breeding.

RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa.

Early Leaf Spot (ELS) caused by the fungus Passalora arachidicola and Late Leaf Spot (LLS) also caused by the fungus Nothopassalora personata, are the two major groundnut (Arachis hypogaea L.) destructive diseases in Ghana. Accurate phenotyping and genotyping to develop groundnut genotypes resistant to Leaf Spot Diseases (LSD) and to increase groundnut production is critically important in Western Africa. Two experiments were conducted at the Council for Scientific and Industrial Research-Savanna Agricultural Research Institute located in Nyankpala, Ghana to explore the effectiveness of using RGB-image method as a high-throughput phenotyping tool to assess groundnut LSD and to estimate yield components. Replicated plots arranged in a rectangular alpha lattice design were conducted during the 2020 growing season using a set of 60 genotypes as the training population and 192 genotypes for validation. Indirect selection models were developed using Red-Green-Blue (RGB) color space indices. Data was collected on conventional LSD ratings, RGB imaging, pod weight per plant and number of pods per plant. Data was analyzed using a mixed linear model with R statistical software version 4.0.2. The results showed differences among the genotypes for the traits evaluated. The RGB-image method traits exhibited comparable or better broad sense heritability to the conventionally measured traits. Significant correlation existed between the RGB-image method traits and the conventionally measured traits. Genotypes 73-33, Gha-GAF 1723, Zam-ICGV-SM 07599, and Oug-ICGV 90099 were among the most resistant genotypes to ELS and LLS, and they represent suitable sources of resistance to LSD for the groundnut breeding programs in Western Africa.

Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea L.) germplasm.

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.

Genetic diversity and population structure of groundnut (Arachis hypogaea L.) accessions using phenotypic traits and SSR markers: implications for rust resistance breeding.

Groundnut (Arachis hypogaea L.) is a multi-purpose legume serving millions of farmers and their value chain actors globally. Use of old poor-performing cultivars contributes to low yields (< 1 t/ha) of groundnut in sub-Saharan Africa including Tanzania. The objectives of this study were to determine the extent of genetic variation among diverse groundnut collections using phenotypic traits and simple sequence repeat (SSR) markers to select distinct and complementary genotypes for breeding. One hundred and nineteen genotypes were evaluated under field conditions for agronomic traits and susceptibility to rust and leaf spot diseases. The study was conducted in two locations across two seasons. In addition, the 119 accessions were profiled with 13 selected SSR markers. Genotype and genotype by environment interaction effects were significant (p < 0.05) for days to flowering (DTF), late leaf spot score at 85 and 100 days after planting, pod yield (PDY), kernel yield (KY), hundred seed weight (HSW) and shelling percentage (SP). Principal components analysis revealed that plant stand, KY, SP, NPP (number of pods per plant), late leaf spot and rust disease scores accounted for the largest proportion of the total variation (71.9%) among the tested genotypes. Genotypes ICGV-SM 08587 and ICGV-SM 16579 had the most stable yields across the test environments. Moderate genetic variation was recorded with mean polymorphic information content of 0.34 and gene diversity of 0.63 using the SSR markers. The majority (74%) of genotypes showed high membership coefficients to their respective sub-populations, while 26% were admixtures after structure analysis. Much of the variation (69%) was found within populations due to genotypic differences. The present study identified genotypes ICGV-SM 06737, ICGV-SM 16575, ICG 12725 and ICGV-SM 16608 to be used for development of mapping population, which will be useful for groundnut improvement. This study provided a baseline information on characterization and selection of a large sample of groundnut genotypes in Tanzania for effective breeding and systematic conservation.

Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits.

In this study, the differential rankings of 36 groundnut genotypes under varying environmental conditions were studied at various levels of phenotype. Locations that are generally accepted by the crop- and soil-based research community to represent the entire Guinea and Sudan Savanna agro-ecological zones in Ghana were characterized, this time using a crop. The characterization was done based on four farmer-preferred traits (early and late leaf spot disease ratings, and haulm and pod yields) using three models (i.e., AMMI, GGE, and Finlay-Wilkinson regression). These models were used to capture specific levels of phenotype, namely, genotype-by-environment interaction (GE), genotype main effect plus GE (G+GE), and environment and genotype main effects plus GE (E+G+GE), respectively. The effect of three major environmental covariables was also determined using factorial regression. Location main effect was found to be highly significant (p < 0.001), confirming its importance in cultivar placement. However, unlike genotypes where the best is usually adjudged through statistical ranking, locations are judged against a benchmark, particularly when phenotyping for disease severity. It was also found that the locations represent one complex mega-environment, justifying the need to test new technologies, including genotypes in all of them before they can be approved for adoption nationally. Again, depending on the phenotypic level considered, genotypic rankings may change, causing environmental groupings to change. For instance, all locations clustered to form one group in 2017 for early and late leaf spot diseases and pod yield when GE was considered, but the groupings changed when G+GE was considered for the same traits in the same year. As a result, assessing genotypic performance at the various levels to arrive at a consensus decision is suggested. Genotypes ICGV-IS 141120 and ICGV-IS 13937 were found to be the best performing.

Multienvironment Testing for Trait Stability and G × E Interaction on N2 Fixation, Plant Development, and Water-Use Efficiency of 21 Elite Groundnut (Arachis hypogaea L.) Genotypes in the Guinea Savanna.

Groundnut production constitutes an integral part of the livelihoods of the people in the Guinea savanna of West Africa. This region accounts for over 70% of the total groundnut production in Ghana, 90% in Nigeria, and 100% in Mali and Burkina Faso. However, harsh environmental conditions often result in drastic yield reductions. In this study, we identified groundnut genotypes with superior symbiotic efficiency, greater pod yield, and plant water-use efficiency from 21 advanced groundnut breeding lines from ICRISAT after testing them at three locations in the Guinea savanna of Ghana over two consecutive years. Average N contribution by the groundnut genotypes ranged from 48 to 108 kg N ha-1, and mean pod yield from 580 to 2,100 kg ha-1. Genotype 17 (ICGV-IS 08837) produced about 2.5-fold more pods than genotype 1 (Chinese), which was the most widely cultivated variety by farmers. Of the 21 genotypes studied, genotype 16 (ICGV 99247) recorded the highest shoot δ13C value and was superior in water-use efficiency, which was consistent with stability estimates and mean performance. We also measured the effects of G × E on pod yield, N2 fixation, shoot δ13C, and mega-environments for testing groundnut in the Guinea savanna, and these were all significant, although the effect was minimal on shoot δ13C values. Of the locations studied, Nyankpala and Damongo were more discriminating, and each constituted a mega-environment for conducting future groundnut trials in the Guinea savanna. Genotype 3 (ICG 6222) emerged as the best cultivar for the Damongo mega-environment, while genotype 17 was the best genotype for the Nyankpala mega-environment. The genotypes exhibiting the highest sensitivity of N2 fixation in the environment included genotype 3 (ICG 6222), genotype 4 (ICGV 00068), and genotype 10 (ICGV 03315) (bi > 1.3), while Pi estimates ranked genotypes 3, 10, and 17 as the best groundnut cultivars in terms of symbiotic N contribution. Based on the results of this study, genotype 17 (ICGV-IS 08837), genotype 3 (ICG 6222), genotype 10 (ICGV 03315), and genotype 4 (ICGV 00068), which were the most outstanding in terms of the overall pod yield, shoot biomass production, and amount of N-fixed, were the most suitable candidates to recommend for use in developing new varieties for the Guinea savanna of Ghana. Genotype 17 (ICGV-IS 08837) has already been released as a commercial variety for the Guinea savanna of Ghana since October 2018.

Genetics, genomics and breeding of groundnut (Arachis hypogaea L.).

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.

Genomics, genetics and breeding of tropical legumes for better livelihoods of smallholder farmers.

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.