Genetic diversity and population structure of Peronosclerospora sorghi isolates of Sorghum in Uganda

Sorghum is the third most important staple cereal crop in Uganda after maize and millet. Downy mildew disease is one of the most devastating fungal diseases which limits the production and productivity of the crop. The disease is caused by an obligate fungus, Peronosclerospora sorghi (Weston & Uppal) with varying symptoms. Information on the genetic diversity and population structure of P.sorghi in sorghum is imperative for the screening and selection for resistant genotypes and further monitoring possible mutant(s) of the pathogen. Isolates of P. sorghi infecting sorghum are difficult to discriminate when morphological descriptors are used. The use of molecular markers is efficient, and reliably precised for characterizing P. sorghi isolates. This study was undertaken to assess the level of genetic diversity and population structure that exist in P. sorghi isolates in Uganda. A total of 195 P. sorghi isolates, sampled from 13 different geographic populations from 10 different regions (agro-ecological zones) was used. Eleven (11) molecular markers, comprising of four Random amplified microsatellite (RAM) and seven (7) Inter-Simple Sequence Repeat (ISSR) markers were used in this study. The analysis of molecular variation (AMOVA) based on 11 microsatellite markers showed significant (P < 0.001) intra-population (88.9 %, PhiPT = 0.111) and inter-population (8.4 %, PhiPR = 0.083) genetic variation, while the genetic variation among regions (2.7 %, PhiRT = 0.022) was not significant. The highest genetic similarity value (0.987 = 98.7 %) was recorded between Pader and Lira populations and the lowest genetic similarity (0.913 = 91.3 %) was observed between Namutumba and Arua populations. The mean Nei's genetic diversity index (H) and Shannon Information Index (I) were 0.308 and 0.471 respectively. Seven distinct cluster groups were formed from the 195 P. sorghi isolates based on their genetic similarity. Mantel test revealed no association between genetic differentiation and geographical distance (R2 = 0.0026, p = 0.02) within the 13 geographic populations

Genetic basis of maize resistance to multiple insect pests: integrated genome-wide comparative mapping and candidate gene prioritization

Several species of herbivores feed on maize in field and storage setups, making the development of multiple insect resistance a critical breeding target. In this study, an association mapping panel of 341 tropical maize lines was evaluated in three field environments for resistance to fall armyworm (FAW), whilst bulked grains were subjected to a maize weevil (MW) bioassay and genotyped with Diversity Array Technology’s single nucleotide polymorphisms (SNPs) markers. A multi-locus genome-wide association study (GWAS) revealed 62 quantitative trait nucleotides (QTNs) associated with FAW and MW resistance traits on all 10 maize chromosomes, of which, 47 and 31 were discovered at stringent Bonferroni genome-wide significance levels of 0.05 and 0.01, respectively, and located within or close to multiple insect resistance genomic regions (MIRGRs) concerning FAW, SB, and MW. Sixteen QTNs influenced multiple traits, of which, six were associated with resistance to both FAWandMW, suggesting a pleiotropic genetic control. Functional prioritization of candidate genes (CGs) located within 10–30 kb of the QTNs revealed 64 putative GWAS-based CGs (GbCGs) showing evidence of involvement in plant defense mechanisms. Only one GbCG was associated with each of the five of the six combined resistance QTNs, thus reinforcing the pleiotropy hypothesis. In addition, through in silico co-functional network inferences, an additional 107 network-based CGs (NbCGs), biologically connected to the 64 GbCGs, and di erentially expressed under biotic or abiotic stress, were revealed within MIRGRs. The provided multiple insect resistance physical map should contribute to the development of combined insect resistance in maize

Factors influencing genomic prediction accuracies of tropical maize resistance to fall armyworm and weevils

Genomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTSs) were designed. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW-resistance traits, and for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and these were at least two-fold those from BLUEs. For PBTS, FAW resistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant, since a positive correlation (R = 0.92***) between TS size and PAs was observed for RBTS, and for the PBTS, it was negative (R = 0.44**). This study pioneered the use of GS for maize resistance to insect pests in sub-Saharan Africa

Current Practices and Prospects of Climate-Smart Agriculture in Democratic Republic of Congo: A Review

peer reviewedClimate-smart agriculture (CSA) is one of the innovative approaches for sustainably increasing the agricultural productivity, improving livelihoods and incomes of farmers, while at the same time improving resilience and contributing to climate change mitigation. In spite of the fact that there is neither explicit policy nor practices branded as CSA in Democratic Republic of Congo (DRC), farmers are utilizing an array of farming practices whose attributes meet the CSA criteria. However, the intensity, distribution, efficiency, and dynamics of use as well as the sources of these technologies are not sufficiently documented. Therefore, this review paper provides a comprehensive evidence of CSA-associated farming practices in DRC, public and private efforts to promote CSA practices, and the associated benefits accruing from the practices as deployed by farmers in the DRC. We find evidence of progress among farming communities in the use of practices that can be classified as CSA. Communities using these practices are building on the traditional knowledge systems and adaptation of introduced technologies to suit the local conditions. Reported returns on use of these practices are promising, pointing to their potential continued use into the future. While progressive returns on investment are reported, they are relatively lower than those reported from other areas in sub-Saharan Africa deploying similar approaches. We recommend for strategic support for capacity building at various levels, including public institutions for policy development and guidance, extension and community level to support uptake of technologies and higher education institutions for mainstreaming CSA into curricula and training a generation of CSA sensitive human resources

Scoping study on existing CIS/CSA relevant units/engagements in Democratic Republic of Congo

RUFORUM conducted a scoping study to identify areas of CSA/CIS convergence for member universities from 20th November to March 2022. Consultations were made with the Deans of the Faculties of Agriculture and related disciplines of Congolese member universities in eastern DRC, through zoom and then individual questionnaires to identify the focal persons who are involved in Climate Smart Agriculture teaching and research. Selected staff of the considered universities [Université Evangélique en Afrique (UEA), Université de Kisangani (UNIKIS) and Université Officielle de Bukavu (UOB)] were convened to a three day workshop in Benin, as a side event during the RUFORUM Triennial Conference and Annual General Meeting from 11th to 13th December 2021. A total of Twenty-one (21) CSA and CIS experts representing 9 countries were invited in the meeting. Participants included representatives from Kenya, Zambia, Ethiopia, Democratic republic of Congo, Benin, Burundi, Uganda, Ghana and Zimbabwe. They analysed the causes of low adoption and utilization of CSA practices & CIS tools and identified the different interventions needed to enhance this shortcoming. Seven prioritoes were identified and it was agreed that the proposed priority CSA will be subjected to national wide consultations in the respective countries. Subsequent to the workshop, the experts were tasked to i) review and compile information about CSA and conduct an inventory of existing programmes and courses related to CSA and potential resource persons in the universities in their respective countries; and ii) conduct country specific consultations and consensus building on the priority CSA. At the university/ academic level, various courses and course units with aspects of CSA and CIS are taught in the considered universities. These courses cover a wide range of the proposed clustered priority areas. These are course units offered in both undergraduate and post graduate programmes

Volatile organic compound based markers for the aroma trait of rice grain

A study was conducted to determine the volatile organic compounds (VOCs) associated with rice grain aroma in 37 commonly grown lines within Uganda, as well as elites. The aim of the study was to identify potential volatile biochemical markers, if any, for the rice grain aroma trait. Certified rice seeds were obtained from the Uganda National Crops Resources Research Institute germplasm collection. The seeds were sown into experimental plots, under field conditions and the mature paddy harvested. Polished rice grains were heated to 80 oC and the liberated VOCs subjected to untargeted metabolite analysis using gas chromatography-time-of-flight mass spectrometry. In total, nine functional groups were present; hydrocarbons, alcohols, ketones, aldehydes, N-containing compounds, S-containing compounds, esters, oxygen heterocycles and carboxylic acids. More specifically, 148 VOCs were identified across the 37 rice lines, of which 48 (32.4%) including 2-acetyl-1-pyrroline (2-AP) appeared to elucidate the difference between non-aromatic and aromatic rice. Furthermore, 41 (27.7%) VOCs were found to be significantly correlated with 2-AP abundance, the principle rice aroma compound. Amongst the 41 VOCs, only ten compounds were found to contribute highly towards variation in 2-AP abundance, indicative of their possible modulation roles in regard to rice aroma. Within the ten influential volatiles, three aroma active compounds; toluene, 1-hexanol, 2-ethyl and heptane, 2,2,4,6,6-pentamethyl- were established as the most reliable biochemical surrogates to the rice aroma trait. Thus, the aforementioned compounds may be used in rice breeding programme for enhancing development of the grain aroma trait

Maize Combined Insect Resistance Genomic Regions and Their Co-localization With Cell Wall Constituents Revealed by Tissue-Specific QTL Meta-Analyses

Combinatorial insect attacks on maize leaves, stems, and kernels cause significant yield losses and mycotoxin contaminations. Several small effect quantitative trait loci (QTL) control maize resistance to stem borers and storage pests and are correlated with secondary metabolites. However, efficient use of QTL in molecular breeding requires a synthesis of the available resistance information. In this study, separate meta-analyses of QTL of maize response to stem borers and storage pests feeding on leaves, stems, and kernels along with maize cell wall constituents discovered in these tissues generated 24 leaf (LIR), 42 stem (SIR), and 20 kernel (KIR) insect resistance meta-QTL (MQTL) of a diverse genetic and geographical background. Most of these MQTL involved resistance to several insect species, therefore, generating a significant interest for multiple-insect resistance breeding. Some of the LIR MQTL such as LIR4, 17, and 22 involve resistance to European corn borer, sugarcane borer, and southwestern corn borer. Eleven out of the 42 SIR MQTL related to resistance to European corn borer and Mediterranean corn borer. There KIR MQTL, KIR3, 15, and 16 combined resistance to kernel damage by the maize weevil and the Mediterranean corn borer and could be used in breeding to reduce insect-related post-harvest grain yield loss and field to storage mycotoxin contamination. This meta-analysis corroborates the significant role played by cell wall constituents in maize resistance to insect since the majority of the MQTL contain QTL for members of the hydroxycinnamates group such as p-coumaric acid, ferulic acid, and other diferulates and derivates, and fiber components such as acid detergent fiber, neutral detergent fiber, and lignin. Stem insect resistance MQTL display several co-localization between fiber and hydroxycinnamate components corroborating the hypothesis of cross-linking between these components that provide mechanical resistance to insect attacks. Our results highlight the existence of combined-insect resistance genomic regions in maize and set the basis of multiple-pests resistance breeding

Relationship between 2-acetyl-1-pyrroline and aroma in Uganda rice populations with Oryza (barthi, glaberrima and sativa) backgrounds

The sweet popcorn aroma conferred by 2-acetyl-1-pyrroline (2AP) is a highly economic trait of rice grain attracting premium price worldwide. This research study was conducted to determine the levels of 2AP in Ugandan rice lines with the aim of establishing a better understanding on the level and classes of 2AP and aroma phenotype. Concentration of 2AP was assayed using two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF-MS) in tandem with sensory evaluation. Substantial variations in aroma intensity within and between the Uganda rice families were recorded. However, the levels of aroma variation were strongly influenced by the type of rice, and the breeding population it was derived from. Hence, three aroma based categories, namely, nonaromatic, moderately aromatic and highly aromatic were identified. GC with complementary sensory evaluation suggested a highly complex nature of rice aroma, as several rice lines were re-classified on the basis of this study. The 2AP contents and aroma intensity for genotypes with O. glaberrima were low compared to O. sativa and O. barthi. Genotypes of Supa 5, Supa 1052, Yasmin aromatic and MET 3 contained high 2AP levels whereas MET 16, MET 6, AGRA 78, AGRA 55, AGRA 41 and Sande TXD 306 exhibited moderate 2AP contents. Therefore, in developing an optimal breeding strategy aimed at improving the aroma in rice, quantitative information about 2AP and complementary sensory evaluation are a prerequisite

Factors influencing genomic prediction accuracies of tropical maize resistance to fall armyworm and weevils

This book is a printed edition of the Special Issue Advances in Cereal Crops Breeding that was published in PlantsGenomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTSs) were designed. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW-resistance traits, and for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and these were at least two-fold those from BLUEs. For PBTS, FAW resistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant, since a positive correlation (R = 0.92***) between TS size and PAs was observed for RBTS, and for the PBTS, it was negative (R = 0.44**). This study pioneered the use of GS for maize resistance to insect pests in sub-Saharan Africa

Current Practices and Prospects of Climate-Smart Agriculture in Democratic Republic of Congo: A Review

peer reviewedClimate-smart agriculture (CSA) is one of the innovative approaches for sustainablyincreasing the agricultural productivity, improving livelihoods and incomes of farmers, while at thesame time improving resilience and contributing to climate change mitigation. In spite of the factthat there is neither explicit policy nor practices branded as CSA in Democratic Republic of Congo(DRC), farmers are utilizing an array of farming practices whose attributes meet the CSA criteria.However, the intensity, distribution, efficiency, and dynamics of use as well as the sources of thesetechnologies are not sufficiently documented. Therefore, this review paper provides a comprehensiveevidence of CSA-associated farming practices in DRC, public and private efforts to promote CSApractices, and the associated benefits accruing from the practices as deployed by farmers in theDRC. We find evidence of progress among farming communities in the use of practices that canbe classified as CSA. Communities using these practices are building on the traditional knowledgesystems and adaptation of introduced technologies to suit the local conditions. Reported returns onuse of these practices are promising, pointing to their potential continued use into the future. Whileprogressive returns on investment are reported, they are relatively lower than those reported fromother areas in sub-Saharan Africa deploying similar approaches. We recommend for strategic supportfor capacity building at various levels, including public institutions for policy development andguidance, extension and community level to support uptake of technologies and higher educationinstitutions for mainstreaming CSA into curricula and training a generation of CSA sensitive humanresources