MasakhaNEWS:News Topic Classification for African languages

African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. named entity recognition and machine translation) have standardized benchmark datasets covering several geographical and typologically-diverse African languages. In this paper, we develop MasakhaNEWS -- a new benchmark dataset for news topic classification covering 16 languages widely spoken in Africa. We provide an evaluation of baseline models by training classical machine learning models and fine-tuning several language models. Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API). Our evaluation in zero-shot setting shows the potential of prompting ChatGPT for news topic classification in low-resource African languages, achieving an average performance of 70 F1 points without leveraging additional supervision like MAD-X. In few-shot setting, we show that with as little as 10 examples per label, we achieved more than 90\% (i.e. 86.0 F1 points) of the performance of full supervised training (92.6 F1 points) leveraging the PET approach

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49\ub74% (95% uncertainty interval [UI] 46\ub74–52\ub70). The TFR decreased from 4\ub77 livebirths (4\ub75–4\ub79) to 2\ub74 livebirths (2\ub72–2\ub75), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83\ub78 million people per year since 1985. The global population increased by 197\ub72% (193\ub73–200\ub78) since 1950, from 2\ub76 billion (2\ub75–2\ub76) to 7\ub76 billion (7\ub74–7\ub79) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2\ub70%; this rate then remained nearly constant until 1970 and then decreased to 1\ub71% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2\ub75% in 1963 to 0\ub77% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2\ub77%. The global average age increased from 26\ub76 years in 1950 to 32\ub71 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59\ub79% to 65\ub73%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1\ub70 livebirths (95% UI 0\ub79–1\ub72) in Cyprus to a high of 7\ub71 livebirths (6\ub78–7\ub74) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0\ub708 livebirths (0\ub707–0\ub709) in South Korea to 2\ub74 livebirths (2\ub72–2\ub76) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0\ub73 livebirths (0\ub73–0\ub74) in Puerto Rico to a high of 3\ub71 livebirths (3\ub70–3\ub72) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2\ub70% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Funding: Bill & Melinda Gates Foundation

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4–52·0). The TFR decreased from 4·7 livebirths (4·5–4·9) to 2·4 livebirths (2·2–2·5), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3–200·8) since 1950, from 2·6 billion (2·5–2·6) to 7·6 billion (7·4–7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9–1·2) in Cyprus to a high of 7·1 livebirths (6·8–7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07–0·09) in South Korea to 2·4 livebirths (2·2–2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3–0·4) in Puerto Rico to a high of 3·1 livebirths (3·0–3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings: Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation: Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury

Population and fertility by age and sex for 195 countries and territories, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017

BACKGROUND: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. METHODS: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories

Global, regional, and national age-sex-specific mortality and life expectancy, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods: The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings: Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation: This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing

Isolation of bacterial strains for improved maize production

MSc. (Biology), North-West University, Mafikeng Campus, 2016BACKGROUND-The ever increasing world population has led to a continued demand for food. If the increase and sustenance of available food crops are not taken seriously, then there might be a crisis of food shortage to sustain all. Maize happens to be an important food crop, as a matter of fact, it is the third largest staple food crop in the world. In South Africa, it is the largest staple crop produced for human consumption. Its importance is not only for food purposes, but also for other vital uses which ease the existence of mankind. Maize is used in the pharmaceutical industry, it is a major ingredient in poultry feed, used in energy industries, paper manufacturing, and brewing industries. The major problems hindering maize production arises from the unavailability of fertile land for good cropping systems caused by land shortage from urbanization and by land pollution mainly through contamination. In order to combat these problems, farmers resort to using chemical fertilizers on the available land. Although this helps to improve the yield to some extent, it is derogatory in the sense that it causes loss of soil fertility on the long run as well as becomes a hazard and a threat to the population it is meant to help. In other words, the advantages of using chemical inputs can never be compared to the destructive activities it causes to the ecosystem and health. This entails the need for a more reliable and safe alternative which is found in nature itself in the form of plant growth promoting rhizobacteria (PGPR). These PGPRs have been used over time as bio-fertilizers. The aim of this study is to identify some potent PGPRs and their synergistic effect to produce a “super” effect on maize crop yield on the farm. METHOD: This study was carried out using a randomized block design. Each treatment was used in triplicates with the control having no treatment. Treatments were used in single organisms, consortia of two organisms and three organisms. Length of leaves, roots, stem, plant heights, numbers of leaves and weight of 100 seeds were taken at 4 and 8 weeks. The readings were compared to the control. OUTPUT: In this study, 31 strains designated A1-A31 were isolated from the rhizospheric soil of maize plants grown in the North West University farm, Molelwane, South Africa. Morphological, biochemical and physiological characteristics of these isolates as well as their plant growth promoting abilities were carried out. 16S rDNA gene sequencing and the nucleotide sequence phylogenetic analysis were determined. 93.5% were able to produce ammonia and just 35.5% could produce indole (IAA). Based on these assays, 3 isolates that showed the most promising result as PGPR were finally selected from the 31 isolates. Three Streptomyces isolates designated NWU4, NWU14 and NWU198 which were also assayed with the 31 isolates that were also selected. All 6 isolates produced oxidase as well as catalase but not all could produce protease. Only A18 and NWU4 produced HCN. Antifungal and antibacterial assays were carried out on the 6 selected isolates. All showed antagonistic activity against the fungal pathogen Fusarium graminearum except A18 that was not effective. A1 and NWU198 were the most active against this pathogen showing more than 70% activity while NWU14, NWU4 and A29 were all moderate in their activities showing 50% and the last two showed 40% activity. Based on these assays, the isolates were categorized in groups of two and three as well as single organisms and were used to inoculate maize seeds which were then planted on the farm inside the university campus. Isolate A1 was screened for its metabolite production due to its high antifungal activity against the fungal pathogen. Metabolites such as phthalan, tropone, ethylbenzene etc were detected. This study demonstrates the potential benefits of using microbial consortia in plant growth promotion as compared to single inoculant treatments. Significant increase was observed in all the parameters compared to the control as well as between the consortia treatments. The study also demonstrates the screening of useful metabolites from one of the effective isolates. Lastly, the study showed that the use of microbial consortia can be of advantage in the eradication of low maize yield as well as serve as reliable alternatives to chemical fertilizers. CONCLUSION: Eradication of chemical fertilizers is becoming more realistic as potent biofertilizers are being discovered daily. These studies show that combination of microorganisms as consortia organisms can enhance all round growth yield in maize. These can be used as efficient PGPR for maize production in field as it is friendly and safe to the environment as well as cost effective.Master

Analysis of Bambara groundnut (Vigna subterranea (L.) Verdc.) diversity towards improved yield

PhD (Biology), North-West University, Mahikeng CampusA considerable set of underutilized crops perform better than their more accepted counterparts when cultivated in less nutritive soils and grossly unfavorable environmental conditions. This advantage necessitates the development of these special crops for the good of sustainable agriculture. Based on the effect of a changing climate and the expected population increase, it is necessary to find a means of improving crop diversities and yield. Less valued crops need to be accepted and incorporated into the food system. Bambara groundnut (Vigna subterranea (L.) Verdc.) is one such crop with so much promise of help in enhancing food security. There is a need to find approaches to improve crop yield and stop this decline in food availability, especially in the less-developed world. Bambara groundnut (BGN) and other legumes with the basic compositions of required nutrients such as proteins, oils, and carbohydrates have been major sources of food for humans and animals alike. One of the ways used in selecting crops and improving yields is the application of multi-environment trials (MET) which have been employed in various crops to select the best cultivars that adapt well to various environments. This has aided in the development of many adaptive and stable cultivars across environments. More importantly, advances in next-generation sequencing (NGS) technologies coupled with improvements in bioinformatics tools have strengthened research in plant breeding to tackle food security. The use and accuracy of molecular breeding has been improved through marker-assisted selection (MAS), genotyping, and gene editing, among others. Improvements in genotyping by sequencing (GBS) have been widely successful in crops with reference genomes. Most less-studied crops do not have a reference genome yet, but other approaches can be employed, such as genome-wide association studies (GWAS), quantitative trait loci (QTL) analysis, and comparative genomics, among others. In this study, a set of 95 accessions of Bambara groundnut that have not been DArT-characterized were selected from the germplasm collection in the IITA Gene bank. These accessions were evaluated for morphological traits in a MET in 2018 and 2019 in Ibadan and Ikenne, South-West Nigeria. Ibadan is in the derived savanna and Ikenne is in the tropical rain forest. To validate their ability to enhance food and nutrition security, their nutrient, antinutrient, mineral components, and stress responses were accessed. The objectives of the field trials were to evaluate the diversities in the phenotypic and agro-morphological traits in the selected accessions, to examine the effect of the environment on the individual traits and accessions, to discover the most stable and adaptable accession in terms of yield among the selected accessions, and to select the best environment for the crop. Experiments were laid out in a randomized complete block design (RCBD), replicated three times. The plot area was 3m2 with 10 plants per plot. Spacing between each plant was 0.3m and inter-plot spacing was 1m. An alley of 1m separates each replicate. The plants were rainfed and irrigated as appropriate and all standard agronomic practices were observed. After planting, young leaves from 2-week-old plants were collected and DNA was extracted for DArT sequencing. Data were collected from the fields at the appropriate time using the field book. For the nutrient and antinutrient components, good-looking seeds were selected after harvest and analyzed in the Food and Nutrition laboratory. Drought assessment was carried out in the screen house in IITA, Ibadan. Wooden boxes were used and arranged using RCBD in three replicates. Five accessions were planted in each box with 6 plants per accession which were later thinned to 3 after 2 weeks. The boxes were irrigated to field capacity for 24hrs before planting and the moisture content at field capacity was recorded. After planting, watering was done regularly for 4 weeks when plants were fully established and the watering was stopped. Individual plants were scored for wilting, stem greenness, chlorophyll content, and leaf senescence. Scoring was done on days 7, 10, and 13 before watering was resumed. Boxes were watered to field capacity on the day of resumption of irrigation, thereafter once every 2 days for 2 weeks until the experiment was concluded. The collected data were subjected to ANOVA, and the means were separated using the Fischer LSD test. Principal component analysis (PCA), correlation, and cluster analysis were also evaluated for the different traits. Furthermore, a genome-wide analysis study was conducted on the stress-treated plants to identify genomic regions and candidate genes regulating the stress-response traits studied. The Eberhart and Russell method and GGE biplot were used to analyze the stability analysis and predict the best genotypes and best environment. Results showed that location was highly significant for all the traits (p <0.0001) except for plant height and leaf length. The accessions varied significantly in plant height, leaf length and width, chlorophyll content, number of petioles, germination count, petiole length, number of pods per plant, number of seeds, hundred seed weight, seed length, seed width, seed thickness, and yield (p <0.0001) while days to flowering (p<0.001) and days to 50% germination and total seed weight (p <0.01) were also significant but their responses to the trait days to emergence was not significant. The interaction effect of location and accession was highly significant (p <0.0001) on leaf width, chlorophyll content, number of petioles, germination count, number of pods, number of seeds, and yield, while plant height was also significant at p <0.001, leaf length and seed length were significant at p <0.01, and seed width was significant at p <0.05. However, the interaction between accession and year was highly significant for plant height, leaf width, number of pods, and number of seeds (p <0.0001) and leaf length (p <0.001). There was a highly significant effect of location, accession, and year interaction on leaf length, leaf width, petiole length, number of pods, and number of seeds (p <0.0001), plant height and days to flowering (p <0.01), and hundred seed weight (p <0.05). This implies that high levels of variability and heterogeneity exist among accessions, locations, and years in response to the traits scored. Principal components 1 (24.67%) and 2 (17.63%) account for 42.3% of the total variance observed. Among the variables, seed width (19.53%), seed thickness (19.58%), hundred seed weight (16.98%), seed length (15.93%) and yield (9.76%) were the major contributing traits in PC1, while number of seeds (21.78%), number of pods (18.48%), total seed weight (13.96%), plant height (9.12%), and petiole length (8.93%) were the major contributing traits in PC2. From the biplot, accessions loading on PC1 are high yielding with thick seeds and long seeds while at the same time having high hundred seed weight. Accessions loaded on PC2 have a high number of seeds, number of pods, and total seed weight. The cluster analysis grouped the accessions into 4 clusters (red, green, blue, and purple) based on the agro-morphological traits with the clusters in red having the highest number of accessions (37 accessions) followed by the ones in green (30), blue having 11, and the purple cluster with 17 accessions. There are lots of significant correlations among the traits scored. In the analysis of the genetic parameters, the phenotypic variance is higher than the genotypic variance in all the traits. Yield (kg ha−1) reported higher phenotypic (19,476.39) and genotypic (5,159.09) variances, while the lower phenotypic (0.68) and genotypic (0.23) variances were observed in leaf width. The traits such as LLE (GCV 7.18, PCV 19.95), GCT (GCV 6.50, PCV 19.61), DTF (GCV 6.31, PCV 10.81), SEEDL (GCV 14.41, PCV 18.19), SEEDW (GCV 11.84, PCV 16.13), and SEEDT (GCV 13.48, PCV 17.66) showed below 20% of phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV). Yield stability analysis showed that seed yield was significantly affected by genotype, environment, and GEI. The mean squares of the accessions were highly significant, also the effect of the environment over the years. Out of the 95 accessions studied, 22 were found to be good-performing and stable, 6 were found to be adaptable, while the remaining accessions were not affected by the environmental factors. The biplot explained 80% of the total variation observed. The first principal component (axis1) explained 48.59% and the second principal component (axis2) explained 31.41%. Accessions TVSu-1866, TVSu-2022, TVSu-2017, TVSu-1943, TVSu-1892, TVSu-2060, and TVSu-1557 were all located at the corners of the polygon in the "which won where" view of the relationship between accessions and environments, indicating that these accessions were outstanding in those environments. TVSu-1706, TVSu-2018, TVSu-1785, TVSu- 1895, and TVSu-1951 accessions performed consistently across all environments. IB2019 was the closest to being an ideal environment, while TVSu-2020 and TVSu-1649 were the most ideal accessions, followed by accessions TVSu-2021, TVSu-1664, TVSu-1866, and TVSu-2025. However, accessions TVSu-1557, TVSu-2060, TVSu-2056, and TVSu-2042 were the worst accessions in terms of yield performance as they are located far from the center of the concentric circle. The result of the nutrient and antinutrient composition shows a highly significant difference for the traits. The two components account for 41.2% of the total variations observed. The clustering based on the traits depicts four main groups. According to the correlation matrix, protein was significantly correlated with ash, fat, and phytate. Fat correlated with moisture content and tannin; tryptophan correlated slightly with protein content and correlated highly with tannin; moisture content and tannin were also highly correlated. Correlation between drought response traits showed a significant positive correlation between chlorophyll content and recovery. PCA of the traits showed variation in response levels on the three different days that data was taken. Further clustering analysis grouped the accessions based on the response traits. A total of twenty significant SNPs (considering thresholds of log (p) ≤ 0.001 with R2 ≥ 9%) from both the GLM (15) and MLM (5) models were identified by GWAS analysis of the BGN accessions in response to water stress using the Mungbean reference genome. In the study, twelve SNPs associated with drought stress response were identified. These SNPs are co-localized with the Vradi07g31020, Vradi05g01630, Vradi06g04840, Vradi06g03310, and Vradi04g08510 genes which encode for a transaldolase, pectin esterase, proline transporter 1, GDSL esterase, and outer plastidial membrane protein porin respectively. As well as the Vradi03g05310, Vradi10g10930, Vradi03g08520, and Vradi02g06260 genes encoding for cell division cycle 20.2- cofactor of APC complex, putative tRNA (cytidine(32)/guanosine(34)-2'-O)-methyltransferase, UDP- glycosyltransferase 76F1, and SHUGOSHIN 2 respectively. Finally, the genes Vradi04g01720, Vradi02g02440, and Vradi07g10090 were discovered, which encode the origin of replication complex subunit 1A, alanine--tRNA ligase, and salicylic acid-binding protein 2. This study showed that BGN can help improve food and nutritional security, and the accessions used can serve as a source of parent lines for improved varieties.Doctora

Genome mining of Escherichia coli WG5D from drinking water source: unraveling antibiotic resistance genes, virulence factors, and pathogenicity

Abstract Background Escherichia coli, a ubiquitous inhabitant of the gut microbiota, has been recognized as an indicator of fecal contamination and a potential reservoir for antibiotic resistance genes. Its prevalence in drinking water sources raises concerns about the potential dissemination of antibiotic resistance within aquatic ecosystems and the subsequent impact on public health. The ability of E. coli to acquire and transfer resistance genes, coupled with the constant exposure to low levels of antibiotics in the environment, underscores the need for comprehensive surveillance and rigorous antimicrobial stewardship strategies to safeguard the quality and safety of drinking water supplies, ultimately mitigating the escalation of antibiotic resistance and its implications for human well-being. Methods WG5D strain, isolated from a drinking water distribution source in North-West Province, South Africa, underwent genomic analysis following isolation on nutrient agar, anaerobic cultivation, and DNA extraction. Paired-end Illumina sequencing with a Nextera XT Library Preparation kit was performed. The assembly, annotation, and subsequent genomic analyses, including phylogenetic analysis using TYGS, pairwise comparisons, and determination of genes related to antimicrobial resistance and virulence, were carried out following standard protocols and tools, ensuring comprehensive insights into the strain’s genomic features. Results This study explores the notable characteristics of E. coli strain WG5D. This strain stands out because it possesses multiple antibiotic resistance genes, encompassing tetracycline, cephalosporin, vancomycin, and aminoglycoside resistances. Additionally, virulence-associated genes indicate potential heightened pathogenicity, complemented by the identification of mobile genetic elements that underscore its adaptability. The intriguing possibility of bacteriophage involvement and factors contributing to pathogenicity further enriches our understanding. We identified E. coli WG5D as a potential human pathogen associated with a drinking water source in South Africa. The analysis provided several antibiotic resistance-associated genes/mutations and mobile genetic elements. It further identified WG5D as a potential human pathogen. The occurrence of E. coli WG5D raised the awareness of the potential pathogens and the carrying of antibiotic resistance in drinking water. Conclusions The findings of this study have highlighted the advantages of the genomic approach in identifying the bacterial species and antibiotic resistance genes of E. coli and its potential as a human pathogen

The functionality of plant-microbe interactions in disease suppression

The plant microbiome can enhance disease suppression by providing life-supporting functions to their host, including stress resilience, health, and growth. However, our understanding of the core mechanisms of microbiome assembly and activity is still emerging. This article explores the role of plant-associated microbes in enhancing host resistance against pathogen infection through disease suppression. We discuss the factors that influence the community assembly and functioning of the plant microbiome, along with an overview of the mechanisms of disease suppression by the plant microbiota. Additionally, we highlight plant characteristics and mechanisms that recruit and stimulate microbial allies for disease suppression. By uncovering the power of plant-microbe interactions, we can create sustainable disease management strategies in agriculture and beyond