The Role of Soil Microorganisms as Inoculation in Maintaining Soil Fertility and Crop Productivity

Increasing human population while soil fertility depletion is becoming a serious problem. Fertile soil functions as a complex living system that provides various ecosystem services, such as preserving water quality and crop production, regulating decomposition of soil nutrient recycling, and eliminating atmospheric greenhouse gases. Soil fertility is closely related to sustainable farming; the key components of soil health are diversity and activity attributable to soil microorganisms. The ability of a crop production system to consistently produce food without environmental damage is agricultural sustainability. Arbuscular mycorrhizal fungi, cyanobacteria, and beneficial nematodes increase the efficiency of water use and the supply of nutrients to plants, the development of phytohormones, the cycling of soil nutrients, and plant resistance to environmental stress. Farming practices have shown that, by increasing the abundance, diversity, and operation of microorganisms to preserve soil fertility and increase crop quality, organic farming and tillage improve soil health. Conservation tillage may theoretically improve the profitability of the grower by reducing inputs and labor costs compared to traditional tillage, whereas organic farming can add additional management costs due to high labor demands for weeding and pest control and fertilizer inputs such as Nitrogen-based, which are usually less reliable than synthetic fertilizers in terms of uniformity and stability. This review has shown soil micro-organisms enhance soil fertility and crop productivity. Keywords: Soil fertility, Soil microorganisms, Inoculation, Crop productivity DOI: 10.7176/JBAH/13-2-01 Publication date: January 31st 202

Evaluating Soil Loss Using Geographical Information System and Remote Sensing for Soil and Water Resource Conservation: The Case of Yisir Watershed, Northwestern Ethiopia

Soil erosion is more sensitive in the highlands of Ethiopia.  The purpose of this study is estimating soil loss rate using RUSLE model with GIS and remote sensing to identify erosion potential areas for soil and water resources conservation plan and to prepare soil loss risk map. LANDSAT image of the study area and Digital Elevation Model from http://earthexplorer.usgs.gov as taken in 2017. Collected data were processed and analyzed using Arc GIS10.2 version. Total average annual soil loss from the 2,120.33ha was estimated at 7161.06tons. The lower soil loss rate was 2.5t/ha/yr on plantation and natural forest, the maximum value was 100.62tons/ha/yr in steep slope cultivated land and average soil loss was 50.31 tons/ha/yr. About 6.35% of the area is under extremely very severe soil erosion rate. Level soil bund, graded soil, stone or stone faced soil bund, fanyajju, cutoff- drain in the above part of the catchment, waterway along the slope, trenches on grazing land, check dam SWC measures at Quala got, integrated physical with biological measures like tree Lucerne, Vetiver grass are the recommended SWC measures. This approach can be applied in other basin or watershed for assessment of erosion risk potential using GIS and RS, and this can be used as a preliminary watershed planning tool for decision makers in Ethiopia like Woreda Agriculture and Natural Resources management Office. Keywords: Ethiopia, GIS, RUSLE, Soil and Water Resource, Yisir Watershed DOI: 10.7176/JRDM/66-02 Publication date:June 30th 202

The Procedure for the Creation of New Regional States under the FDRE Constitution: Some Overlooked Issues

The Ethiopian Federation which was created by the 1995 Federal Democratic Republic of Ethiopia (FDRE) Constitution had nine member states and one city administration. Apart from the creation of Dire Dawa as a city administration, no new state has been introduced in the Ethiopian federation since the adoption of the Constitution. However, several ethnic-based Zonal administrations in the country’s Southern Nations, Nationalities and Peoples (SNNP) region are now demanding to form their own regional states. Apparently, the demands are justified under Article 47(2) of the 1995 Ethiopian constitution which follows a purely ethnic-centered approach by giving “each nation, nationality and people” living in the nine States of the federation “the right to establish their own States at any time.” However, since this right has so far never been exercised in practice, the new demands are creating anxiety in some quarters and drawing a growing attention to the constitutional procedure for the creation of new states. This article aims to critically examine the relevant constitutional provisions dealing with the issue of creation of new states. Drawing insights from some other federations, we argue that the ethnic-centered approach taken under the FDRE Constitution for the creation of new states overlooks several important issues such as economic viability, administrative efficiency, equity, sustainable peace, and resilience of the federal system.Key terms: Creation of new states · Ethnic federalism · Self-determination · Nation, Nationality or People (NNP

The Role of Indigenous Social Institutions on Pastoral and Agro-pastoral Household

In both pastoral and agro-pastoral communities there is almost always strong inter-dependence and co-operation among households based on indigenous social institutions. However, those lucrative indigenous institutions are not known to the outsiders and this study filled this knowledge gap in literatures. Purposive sampling technique was employed to select study participants. Data were gathered from households using FGD, interview, key informant interview and case study to attain the objectives of the study. The study revealed that, mutual support is important in terms of each househol

Effects of different dose of nitrogen and lime on soil properties and maize (Zea mays L.) on acidic nitisols of Northwestern Ethiopia

This study was carried out on the nitisols of Burie district, Ethiopia to examine the effect of integrated use of lime and nitrogen on soil physicochemical properties and maize yield. Two levels of lime (0 and 0.5 t/ha) and five-level of nitrogen (0, 46, 92, 138 and 184 kg N/ ha) were laidout in randomized complete block design with three replications. The results indicated that among before planting, soil bulk density (BD), pH, soil organic carbon (OC), total nitrogen (TN), available P and CEC were 1.42 g/cm3, 5.2 (strongly acidic), 1.32% (very low), 0.12% (low), 8.86 mg /kg (very low), and 19.57 cmolc /kg  (medium), respectively.  The physicochemical properties except bulk density increased. The lowest soil BD (1.21 g/m3) was from plots treated with 0.5 t/ha lime and 184 kg N/ ha. The maximum soil pH (6.85) was obtained from plots treated with 184 kg N/ ha and 0.5 t/ha lime. The maximum soil CEC (35.38 (cmolc /kg) was obtained from plots treated with 184 kg N/ ha and 0.5 t/ha lime. Level of lime, nitrogen fertilizer, and interaction effects of lime and nitrogen fertilizer (L×N) significantly affected maize yield (p<0.001). Indeed yield of maize has positive correlations with most soil physicochemical properties but negative with BD (r= -0.543). The adjusted yield and net benefits was 6.4 t/ha and 1101.77$. Inherent physicochemical properties of the soil are changed either by sole or combined use of lime and N fertilizer. Soils tilled with 0.5 t/ha lime and 138 kg/ha  nitrogen were found in maximum net benefit. Residual long-term effects should be researched. Thus, liming should be given an emphasis on acidic soil amelioration. Moreover, the government may facilitate the supply of lime and nitrogen fertilizer to the farmers.

Spatial variation of zero fruits/vegetables consumption and associated factors among children aged 6–23 months in Ethiopia: geographical weighted regression analysis

BackgroundAfter 6 months, nutrient-dense, varied diets containing fruits and vegetables are crucial to supplement breastfeeding. Like many other low-income countries, Ethiopia has very low FV consumption. Zero vegetable or fruit (ZVF) consumption has been shown to significantly raise the risk of non-communicable diseases and has been ranked among the top 10 risk factors for mortality. And it is associated with poor health, an increased risk of obesity, and a higher risk of non-communicable diseases. Thus, this study’s goal was to investigate the spatial distribution of ZVF consumption and its spatial determinants among children aged 6–23 months in Ethiopia.MethodsA cross-sectional study design was employed. A total of 1,489 weighted samples were included from kids’ datasets from the 2019 Ethiopian mini-demographic and health survey. STATA version 16, ArcGIS version 10.8, Kuldorff’s SaTScan version 9.6, and MGWR version 2.0 software were used for analysis. Spatial regression analyses (geographical weighted regression and ordinary least squares analysis) were conducted. Models were compared using AICc and adjusted R2. A p-value of less than 0.05 was used to declare statistically significant spatial predictors, and the corresponding local coefficients were mapped.ResultsThe spatial distribution of ZVF consumption among children aged 6–23 months was non-random in Ethiopia. Spatial scan analysis revealed a total of 120 significant clusters. Maternal education, wealth status, age of the child, place of delivery, number of under-five children in the house, and current pregnancy status were significant predictors of the spatial variation of ZVF consumption.ConclusionSignificant geographic variation in ZVF consumption was found in this study throughout Ethiopia’s regions. Significant predictors of the spatial variation in ZVF consumption were maternal education, wealth status, child age, place of delivery, number of under-five children in the home, and status as a pregnant woman at the time of birth. Therefore, in order to improve children’s adequate consumption of fruit and vegetables, area-based interventions that can consider these significant factors into account are needed

Anxiety and depression among cancer patients in Ethiopia: a systematic review and meta-analysis

IntroductionAnxiety and depression are among the common comorbidities of people diagnosed with cancer. However, despite the progress in therapeutic options and outcomes, mental health care and support have lagged behind for cancer patients. Estimating the extent and determinants of mental health disorders among cancer patients is crucial to alert concerned bodies for action. In view of this, we aimed to determine the pooled prevalence and determinants of anxiety and depression among cancer patients in Ethiopia.MethodsRelevant literatures were searched on PubMed, African Journals Online, Hinari, Epistemonikos, Scopus, EMBASE, CINAHL, Cochrane Library, and Gray literature sources. Data were extracted into an Excel spreadsheet and analyzed using STATA 17 statistical software. The random effect model was used to summarize the pooled effect sizes with their respective 95% confidence intervals. The I2 statistics and Egger’s regression test in conjunction with the funnel plot were utilized to evaluate heterogeneity and publication bias among included studies respectively.ResultsA total of 17 studies with 5,592 participants were considered in this review. The pooled prevalence of anxiety and depression among cancer patients in Ethiopia were 45.10% (95% CI: 36.74, 53.45) and 42.96% (95% CI: 34.98, 50.93), respectively. Primary and above education (OR= 0.76, 95% CI: 0.60, 0.97), poor social support (OR= 2.27, 95% CI: 1.29, 3.98), occupational status (OR= 0.59; 95% CI: 0.43, 0.82), advanced cancer stage (OR= 2.19, 95% CI: 1.38, 3.47), comorbid illness (OR= 1.67; 95% CI: 1.09, 2.58) and poor sleep quality (OR= 11.34, 95% CI: 6.47, 19.89) were significantly associated with depression. Whereas, advanced cancer stage (OR= 1.59, 95% CI: 1.15, 2.20) and poor sleep quality (OR= 12.56, 95% CI: 6.4 1, 24.62) were the factors associated with anxiety.ConclusionThis meta-analysis indicated that a substantial proportion of cancer patients suffer from anxiety and depression in Ethiopia. Educational status, occupational status, social support, cancer stage, comorbid illness and sleep quality were significantly associated with depression. Whereas, anxiety was predicted by cancer stage and sleep quality. Thus, the provision of comprehensive mental health support as a constituent of chronic cancer care is crucial to mitigate the impact and occurrence of anxiety and depression among cancer patients. Besides, families and the community should strengthen social support for cancer patients.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023468621

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.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.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