INTROGRESSION OF DROUGHT TOLERANCE ROOT TRAITS INTO KENYAN COMMERCIAL CHICKPEA VARIETIES USING MARKER ASSISTED BACKCROSSING

Roots play critical roles in enhancing drought tolerance, more so under terminal drought conditions. The objective of this study was to introgress drought tolerant root traits into Kenyan chickpea varieties through marker assisted backcrossing (MABC). Eight simple sequence repeat (SSR) markers, linked to quantitative trait loci (QTL) for root traits, were used to screen parents at ICRISAT in India, and 1144 single nucleotide polymorphic (SNPs) markers at Legume Genomics Centre in the United Kingdom. Crosses were made between two selected varieties, ICCV 92944 (Chania Desi II) and ICCV 00108 (LDT 068); and ICC 4958, QTL donor parent. Polymorphic SSR and SNP markers were used to select offspring with root QTL at F1, BC1F1, and BC2F1, and later advanced to BC2F3. BC2F3 families were evaluated for root traits at Egerton University in Kenya in a pot experiment under rain shelter. The BC2F3 families were significantly (P<0.05) different for root dry weight (RDW), shoot dry weight (SDW), total plant dry weight (PDW), and root to shoot dry weight (R/S) ratio (R/S) for Chania Desi II x ICC 4958; while R/S was significantly different for LDT 068 x ICC 4958. Root length density (RLD) and RDW were positively and significantly (P<0.05) correlated with most of the traits, indicating its usefulness in the indirect selection of these traits. The utilisation of MABC is an effective and efficient method of introgressing complex root traits into commercial lines, expected to improve yields under drought. There is need for deployment of marker-assisted breeding in difficult to phenotypically select traits.Les racines jouent un r\uf4le essentiel dans l\u2019am\ue9lioration de la tol\ue9rance \ue0 la s\ue9cheresse, plus encore en cas de s\ue9cheresse terminale. L\u2019objectif de cette \ue9tude \ue9tait d\u2019introduire des traits de racine tol\ue9rants \ue0 la s\ue9cheresse dans des vari\ue9t\ue9s Kenyannes de chickpea par r\ue9trocroisement assist\ue9 par marqueurs (MABC). Huit marqueurs de r\ue9p\ue9tition de s\ue9quence simple (SSR), li\ue9s \ue0 des locus de traits quantitatifs (QTL) pour les traits racinaires, ont \ue9t\ue9 utilis\ue9s pour s\ue9lectionner les parents \ue0 l\u2019ICRISAT en Inde, et 1144 marqueurs polymorphes \ue0 un seul nucl\ue9otide (SNP) au Legume Genomics Center au Royaume-Uni. Des croisements ont \ue9t\ue9 r\ue9alis\ue9s entre deux vari\ue9t\ue9s s\ue9lectionn\ue9es, ICCV 92944 (Chania Desi II) et ICCV 00108 (LDT 068) ; et ICC 4958, parent donneur QTL. Des marqueurs SSR et SNP polymorphes ont \ue9t\ue9 utilis\ue9s pour s\ue9lectionner la prog\ue9niture avec un QTL racine \ue0 F1, BC1F1 et BC2F1, puis avanc\ue9 \ue0 BC2F3. Les familles BC2F3 ont \ue9t\ue9 \ue9valu\ue9es pour les traits racinaires \ue0 l\u2019Universit\ue9 d\u2019Egerton au Kenya dans une exp\ue9rience en pot sous abri contre la pluie. Les familles BC2F3 \ue9taient significativement diff\ue9rentes (P<0,05) pour le poids sec des racines (RDW), le poids sec des pousses (SDW), le poids sec total de la plante (PDW) et le rapport poids sec des racines sur les pousses (R/S) (R/S ) pour Chania Desi II x ICC 4958\ua0; tandis que R/S \ue9tait significativement diff\ue9rent pour LDT 068 x ICC 4958. La densit\ue9 de longueur des racines (RLD) et RDW \ue9taient corr\ue9l\ue9es positivement et significativement (P < 0,05) avec la plupart des traits, indiquant son utilit\ue9 dans la s\ue9lection indirecte de ces traits. L\u2019utilisation de MABC est une m\ue9thode efficace et efficiente d\u2019introgression de traits racinaires complexes dans des lign\ue9es commerciales, cens\ue9e am\ue9liorer les rendements en p\ue9riode de s\ue9cheresse. Il est n\ue9cessaire de d\ue9ployer la s\ue9lection assist\ue9e par marqueurs dans les caract\ue8res difficiles \ue0 s\ue9lectionner ph\ue9notypiquement

Socio-economic determinants for the deployment of Climate-Smart One-Health innovations. A meta-analysis approach prioritizing Ghana and Benin

Open Access Journal; Published online: 14 Mar 2023An ecosystem is inhabited by organisms that rely on it for their livelihoods. For an ecosystem to sustain life, its life-supporting components must be alive to be able to preserve both the ecosystem’s life-supporting components like soil, vegetation, water, etc., and the living organisms inhabiting the ecosystem like humans, birds, domestic, and wild animals, termed as the One-Health concept. This is indispensable for the sustainability of life. Several factors determine the ability of the ecosystem to provide ecosystem services and support life, more so amidst climate change. Hence, climate-smart (CS) One-Health innovations are essential to maintain the integrity of the ecosystem to be able to support life. However, factors that could effectively determine the deployment of such CS One-Health innovations are not well identified. This paper, closes the knowledge gap through a systematic review of literature for a meta-analysis of the socio-economic determinants for the successful deployment of CS One-Health innovations. Using a scoping review methodology, search engines like Google Scholar, PubMed, Scopus, and AgriEcon were explored extensively for literature on CS One-Health innovations. Search results were then screened and only articles that met the inclusion criteria were considered in this study. Subsequently, appropriate articles were identified for data extraction. Results revealed that political will, community participation, knowledge of CS One-Health practices, the willingness of parties to engage in multi-disciplinary collaborative activities, and level of investment (income/funds) were enablers for the deployment of CS One-Health innovations. On the other hand, behavior incompatibility with innovations, policy failure to restrict the use of toxic substances in agriculture, poor community knowledge of CS One-Health innovations, and language barriers between communities and innovators, hindered such deployment. Hence, multiple factors (fostering and hindering) must be addressed in a multi-disciplinary framework to ensure the successful deployment of CS One-Health innovations

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Intra-specific variation in West African and Asian germplasm of okra (Abelmoschus spp L.)

Ten quantitative agromorpho-economic traits, six inter-simple sequence repeat (ISSR) primers, and three sequenced regions were employed to study intra-specific genetic diversity among twenty-eight accessions of West African and Asian okra (Abelmoschus spp L.) collected from eight geographical regions of Ghana. Pod yield per plant was analysed as dependent variable in relation to other agromorpho-economic traits, showing the correlation and contribution of each trait to crop yield. 50% germination and flowering were the most significant traits followed by plant height and average seeds per plant. Principal coordinate analysis defined three sets of traits, while Agglomerative Hierarchical Clustering (AHC) defined three clusters of the germplasms. ISSR detected very low level of polymorphism among the accessions. Testing the correlation between molecular data and morphological traits using Mantel test showed a significant positive correlation (r-value = 0.71, 0.90) with 50% flowering, fruiting and number of leaves per plant. Eclectic variation between Indiana and the rest of the accessions for both agromorpho-economic traits and molecular markers affirms its potential usefulness as a source of diverse genes for future breeding programmes. Sequencing of regions from all accessions, suggests that they are identical with a common ancestry. Outcomes of this study is timely for an ongoing okra hybridisation programme in Ghana

Rainfall–runoff modelling of railway embankment steep slopes

A distributed 1D rainfall–runoff model is presented. It consists of the Saint Venant continuity andmomentum equations for overland flow and a modified Green-Ampt model for the infiltration on railway embankmentsteep slopes. The model is applied to adjacent 10-m-wide erosion control experimental plots with differentpercentages of grass cover. A relationship between the 2-day antecedent rainfall and initial moisture content wasestablished and used to predict the saturated hydraulic conductivity (Ks). Average values of Ks for 0, 50 and 100%grass cover were found to be 0.1, 1.19 and 2.56 mm/h, respectively. For the majority of cases, the model simulatedrunoff with acceptable accuracy, 68% having Nash-Sutcliffe efficiency (NSE) values above 0.50. The averageNSE value varied between 0.60 and 0.80, with 0% grass-covered plots yielding the highest values. As expected,the runoff volume decreased with increasing percentage of grass cover