Progress and future prospects in groundnut improvement to feed Africa in the face of technological advancements

Crop productivity is crucial in meeting food demands to feed the growing population in the face of endemic biotic and abiotic stresses. Technological advancement and its application to boost crop productivity would be a pathway towards ensuring food and nutrition security. Dryland legumes including groundnut are suitable in diversification of farming systems as insurance crops to ensure productivity. Crop improvement is one of the pillars towards enhancing productivity by delivering products and services based on demand articulation such as high yielding resilient varieties that are nutrient dense to address the global nutrition agenda. Recent advancements in molecular technology has made it possible to sequence the groundnut genome, develop genetic maps and identification of quantitative trait loci (QTLs) for key traits of importance. These new developments need to be exploited to accelerate the design and development of quality products that fits within the African farming systems. The low genotyping cost has opened avenues for research centers in African countries to embrace the use of genomic selection tools in breeding. This should enhance efficiency in exploiting the wild genetic resource base, broadening the narrow genetic base of groundnut and fast tracking variety release. The use of molecular tools in breeding and wide hybridization techniques coupled with high throughput phenotyping is a new dawn to breeding programs and this would contribute significantly to food security and poverty alleviation in the long run. However, the success in the modernization of breeding for efficiency will be underpinned by pro-active engagement among different actors in the national, regional and international arena to leverage resources and expertise in the omics era for sustained outcomes. Healthy working partnerships are also key to the delivery and utilization of such technologies coupled with learning and feedback for product improvement

Quantitative Trait Loci Mapping in Maize for Resistance to Larger Grain Borer

Storability of maize grain is constrained by the larger grain borer (LGB) (Prostephanus truncatus). Host plant resistance is the most feasible way to manage LGB among smallholder farmers. Breeding for resistance to this pest inmaize is dependent on understanding genetic mechanisms underlying the resistance. The objective of this study was to map quantitative trait loci (QTL) associated with LGB resistance in tropical maize. A mapping populationof 203 F2:3 derived progenies was developed from a cross between susceptible and resistant inbred lines.The F2:3 progenies were crossed to a tester and testcrosses evaluated across six environments, followed by screening for resistance to LGB. Data was collected on husk cover tip length, and grain texture in the field. Biochemical traits were analyzed on the maize grain. Harvested grain was evaluated for resistance and data recorded on grain damage, weight loss, and several insects. Grain hardness was measured as a putative trait of resistance. Univariate analysis of variance for all the traits was done using the general linear model of the statistical analysis system.Genetic mapping was done using Joinmap 4, while QTL analysis was done using PLABQTL. The QTL for resistance were mapped to 6 out of the ten chromosomes. QTL for resistance traits were located in chromosomes 1, 5 and 9.Chromosome 1 had a common QTL linked to protein content, grain hardness, and husk cover tip length. Additive genetic effects were prevalent in all detected QTL. Overall, the studies show that breeding for resistance to LGB is possible

Responses of tropical maize landraces to damage by Chilo partellus stem borer

The potential to manage insect pests using host-plant resistance exists, but has not been exploited adequately. The objective of this study was to determine the resistance of 75 tropical maize landraces through artificial infestation with Chilo partellus Swinhoe. The trial was laid in alpha-lattice design and each seedling was infested with five neonates three weeks after planting, over two seasons in 2009 and 2010. The number of exit holes, tunnel length, ear diameter, ear length, plant height, stem diameter, stem lodging and grain yield were measured and a selection index computed. GUAT 1050 was the most resistant with an index of 0.56, while BRAZ 2179 was the most susceptible with an index of 1.66. Ear characteristics were negatively correlated with damage parameters. The principal component biplot suggested that exit holes, cumulative tunnel length, leaf damage, cob diameter, stem lodging, selection index, ear and plant height contributed 71.2% of the variation in resistance. The mean number of exit holes and tunnel length for resistant landraces and resistant hybrid checks were similar; at 5.5 and 2.48 cm, respectively. The identified resistant landraces (GUAT 1050, GUAT 280, GUAT 1093, GUAT 1082, GUAT 1014, CHIS 114, and GUAN 34) could be used to develop C. partellus stem borer-resistant maize genotypes.Key words: Chilo partellus, ear length, exit holes, stem borer resistance, tunnel length

QTL Mapping of Traits Associated with Dual Resistance to the African Stem Borer (Busseola fusca) and Spotted Stem Borer (Chilo partellus) in Sorghum (Sorghum bicolor)

Sorghum (Sorghum bicolor (L.) Moench) is an important food crop in semi-arid tropics. The crop grain yield ranges from 0.5 t/ha to 0.8 t/ha compared to potential yields of 10 t/ha. The African stem borer Busseola fusca Fuller (Noctuidae) and the spotted stem borer Chilo partellus Swinhoe (Crambidae), are among the most economically important insect pests of sorghum. The two borers can cause 15% - 80% grain yield loss in sorghum. Mapping of QTLs associated with resistance traits to the two stem borers is important towards marker-assisted breeding. The objective of this study was to map QTLs associated with resistance traits to B. fusca and C. partellus in sorghum. 243 F9:10 sorghum RILs derived from ICSV 745 (S) and PB 15520-1 (R) were selected for the study with 4,955 SNP markers. The RILs were evaluated in three sites. Data was collected on leaf feeding, deadheart, exit holes, stem tunnels, leaf toughness, seedling vigour, bloom waxiness, and leaf glossiness. ANOVA for all the traits was done using Genstat statistical software. Insect damage traits and morphological traits were correlated using Pearson’s correlation coefficients. Genetic mapping was done using JoinMap 4 software, while QTL analysis was done using PLABQTL software. A likelihood odds ratio (LOD) score of 3.0 was used to declare linkage. Joint analyses across borer species and sites revealed 4 QTLs controlling deadheart formation; 6 controlling leaf feeding damage; 5 controlling exit holes and stem tunneling damages; 2 controlling bloom waxiness, leaf glossiness, and seedling vigour; 4 conditioning trichome density; and 6 conditioning leaf toughness. Joint analyses for B. fusca and C. partellus further revealed that marker CS132-2 colocalised for leaf toughness and stem tunneling traits on QTLs 1 and 2, respectively; thus, the two traits can be improved using the same linked marker. This study recommended further studies to identify gene(s) underlying the mapped QTLs

Genetic diversity analysis in tropical maize germplasm for stem borer and storage pest resistance using molecular markers and phenotypic traits

One hundred maize inbred lines and eighty four hybrids were characterized for resistance to maize stem borer and post-harvest insect pests. This was achieved using genetic distance and population structure based on simple sequence repeat (SSR) markers and biophysical traits. The test materials were evaluated for stem borer, maize weevil and larger grain borer (LGB) resistance. Leaf samples were harvested from 10 healthy plants per genotype and bulked. Genomic DNA was extracted using a modified version of mini-prep Cetyl Trimethyl Ammonium Bromide (CTAB) method. The samples were genotyped with 55 SSRs makers. Univariate analysis of variance was done using the general linear model procedure of SAS statistical package. Rodgers genetic distance was calculated for all data sets as a measure of genetic distance using NTSYS-pc for Windows. The distance matrices were used to generate phenograms using the unweighted pair group method based on arithmetic average (UPGMA) method in MEGA5. The genotypes were assigned into different populations using population structure software. The data was further subjected to discriminant and principal component analysis to group the gnotyoes. Analysis of molecular variance within and among the different populations was done using arlequin. There were significant differences (P ≤ 0.001) for all the biophysical traits evaluated. The SSR marker data estimated successfully the close relationship among different hybrids and inbred lines within clusters. Comparisons of the different multivariate analyses revealed high concordance among the different approaches of analyses. The results of this study can be directly used by breeding programs to develop resistant genotypes

Genotype-by-environment interactions for grain yield of Valencia groundnut genotypes in East and Southern Africa

Grain yield is a quantitatively inherited trait in groundnut (Arachis hypogea L.) and subject to genotype by environment interactions. Groundnut varieties show wide variation in grain yield across different agro-ecologies. The objectives of this study were to evaluate Valencia groundnut genotypes for yield stability and classify environments to devise appropriate breeding strategies. Seventeen multi-location trials were conducted in six countries, viz., Malawi, Tanzania, Uganda, Zimbabwe, Mozambique and Zambia, from 2013 to 2016. The experiments were laid out following a resolvable incomplete block design, with two replications at each location (hereafter referred to as ‘environments’) using 14 test lines and two standard checks. The additive main effects and multiplicative interaction (AMMI) analysis was conducted. Variation attributable to environments, genotypes and genotype × environment interaction for grain yield was highly significant (P<0.001). Genotype, environment and genotype × environment interactions accounted for 7%, 53 % and 40% of the total sum of squares respectively. Superior-performing genotypes possessing high to moderate adaptability and stability levels included ICGV-SM 0154, ICGV-SM 07539, ICGV-SM 07536, ICGV-SM 7501, ICGV-SM 99568 and ICGV SM 07520. Nachingwea 2013 in Tanzania, Nakabango 2014 in Uganda and Chitedze 2015 in Malawi were the most representative and discriminative environments. Considering the implications of interactions for Valencia groundnut breeding in East and Southern Africa we propose that different varieties should be targeted for production in different environments and at the same time used for breeding in specific environments