130 research outputs found

    Morphological Variation and Inter-Relationships of Quantitative Traits in Enset (Ensete ventricosum (welw.) Cheesman) Germplasm from South and South-Western Ethiopia

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    This is the final version. Available on open access from MDPI via the DOI in this recordEnset (Ensete ventricosum (Welw.) Cheesman) is Ethiopia's most important root crop. A total of 387 accessions collected from nine different regions of Ethiopia were evaluated for 15 quantitative traits at Areka Agricultural Research Centre to determine the extent and pattern of distribution of morphological variation. The variations among the accessions and regions were significant (p ≀ 0.01) for all the 15 traits studied. Mean for plant height, central shoot weight before grating, and fermented squeezed kocho yield per hectare per year showed regional variation along an altitude gradient and across cultural differences related to the origin of the collection. Furthermore, there were significant correlations among most of the characters. This included the correlation among agronomic characteristics of primary interest in enset breeding such as plant height, pseudostem height, and fermented squeezed kocho yield per hectare per year. Altitude of the collection sites also significantly impacted the various characteristics studied. These results reveal the existence of significant phenotypic variations among the 387 accessions as a whole. Regional differentiations were also evident among the accessions. The implication of the current results for plant breeding, germplasm collection, and in situ and ex situ genetic resource conservation are discussed.This study was part of the PhD research work of the first author, and we acknowledge the McKnight Foundation for financial support

    Farmers' knowledge and perception of enset Xanthomonas wilt in southern Ethiopia

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    This is the final version. Available on open access from BMC via the DOI in this recordAvailability of data and materials: The dataset supporting the conclusions of this article is included within the article (“Additional file 1 Datasets”).Background: Enset Xanthomonas wilt (EXW) was first reported in 1939 and continues to threaten the sustainability of farming systems in south and southwestern parts of Ethiopia. The present study was conducted in the central zones of southern Ethiopia to assess farmers' knowledge and perception about EXW, its etiology and mode of transmission, and its implications for the management of EXW. Methods: A survey was conducted in 240 households across Hadiya, Kembata-Tembaro and Wolaita zones of southern Ethiopia using focus group discussions and a structured questionnaire to assess farmers' perceptions of causes and modes of EXW transmission, and their knowledge on symptom identification. In addition, EXW prevalence, incidence and severity were determined for each zone. Data were analyzed through descriptive statistics. Results: The results showed that a significant number of farmers are aware of EXW, its symptoms, etiology and transmission and spread, but they are not able to readily relate modes of spread to control methods. Since 2002, EXW became prominent in Hadiya, with the highest EXW incidence and severity, followed by Wolaita, and Kembata-Tembaro. Farmers identified EXW as the major cause for declining production and productivity of enset in the region. Conclusion: EXW has spread widely and rapidly in southern Ethiopia, with significant socioeconomic impacts in smallholders' livelihoods. There is a need for developing knowledge-based strategies and awareness-raising campaign for EXW management.This work was supported by the McKnight foundation, Africa RISING and Ethiopian Biodiversity Institute (EBI)

    Detection of associations with rare and common SNPs for quantitative traits: a nonparametric Bayes-based approach

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    We propose a nonparametric Bayes-based clustering algorithm to detect associations with rare and common single-nucleotide polymorphisms (SNPs) for quantitative traits. Unlike current methods, our approach identifies associations with rare genetic variants at the variant level, not the gene level. In this method, we use a Dirichlet process prior for the distribution of SNP-specific regression coefficients, conduct hierarchical clustering with a distance measure derived from posterior pairwise probabilities of two SNPs having the same regression coefficient, and explore data-driven approaches to select the number of clusters. SNPs falling inside the largest cluster have relatively low or close to zero estimates of regression coefficients and are considered not associated with the trait. SNPs falling outside the largest cluster have relatively high estimates of regression coefficients and are considered potential risk variants. Using the data from the Genetic Analysis Workshop 17, we successfully detected associations with both rare and common SNPs for a quantitative trait. We conclude that our method provides a novel and broadly applicable strategy for obtaining association results with a reasonably low proportion of false discovery and that it can be routinely used in resequencing studies

    Brain alterations in regions associated with end‐organ diabetic microvascular disease in diabetes mellitus: A UK Biobank study

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    Background Diabetes mellitus (DM) is associated with structural grey matter alterations in the brain, including changes in the somatosensory and pain processing regions seen in association with diabetic peripheral neuropathy. In this case-controlled biobank study, we aimed to ascertain differences in grey and white matter anatomy in people with DM compared with non-diabetic controls (NDC). Methods This study utilises the UK Biobank prospective, population-based, multicentre study of UK residents. Participants with diabetes and age/gender-matched controls without diabetes were selected in a three-to-one ratio. We excluded people with underlying neurological/neurodegenerative disease. Whole brain, cortical, and subcortical volumes (188 regions) were compared between participants with diabetes against NDC corrected for age, sex, and intracranial volume using univariate regression models, with adjustment for multiple comparisons. Diffusion tensor imaging analysis of fractional anisotropy (FA) was performed along the length of 50 white matter tracts. Results We included 2404 eligible participants who underwent brain magnetic resonance imaging (NDC, n = 1803 and DM, n = 601). Participants with DM had a mean (±standard deviation) diagnostic duration of 18 ± 11 years, with adequate glycaemic control (HbA1C 52 ± 13 mmol/mol), low prevalence of microvascular complications (diabetic retinopathy prevalence, 5.8%), comparable cognitive function to controls but greater self-reported pain. Univariate volumetric analyses revealed significant reductions in grey matter volume (whole brain, total, and subcortical grey matter), with mean percentage differences ranging from 2.2% to 7% in people with DM relative to NDC (all p < 0.0002). The subcortical (bilateral cerebellar cortex, brainstem, thalamus, central corpus callosum, putamen, and pallidum) and cortical regions linked to sensorimotor (bilateral superior frontal, middle frontal, precentral, and postcentral gyri) and visual functions (bilateral middle and superior occipital gyri), all had lower grey matter volumes in people with DM relative to NDC. People with DM had significantly reduced FA along the length of the thalamocortical radiations, thalamostriatal projections, and commissural fibres of the corpus callosum (all; p < 0·001). Interpretation This analysis suggests that anatomic differences in brain regions are present in a cohort with adequately controlled glycaemia without prevalent microvascular disease when compared with volunteers without diabetes. We hypothesise that these differences may predate overt end-organ damage and complications such as diabetic neuropathy and retinopathy. Central nervous system alterations/neuroplasticity may occur early in the natural history of microvascular complications; therefore, brain imaging should be considered in future mechanistic and interventional studies of DM

    Factors that transformed maize productivity in Ethiopia

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    Published online: 26 July 2015Maize became increasingly important in the food security of Ethiopia following the major drought and famine that occurred in 1984. More than 9 million smallholder house- holds, more than for any other crop in the country, grow maize in Ethiopia at present. Ethiopia has doubled its maize produc- tivity and production in less than two decades. The yield, currently estimated at >3 metric tons/ha, is the second highest in Sub-Saharan Africa, after South Africa; yield gains for Ethiopia grew at an annual rate of 68 kg/ha between 1990 and 2013, only second to South Africa and greater than Mexico, China, or India. The maize area covered by improved varieties in Ethiopia grew from 14 % in 2004 to 40 % in 2013, and the application rate of mineral fertilizers from 16 to 34 kg/ ha during the same period. Ethiopia ’ s extension worker to farmer ratio is 1:476, compared to 1:1000 for Kenya, 1:1603 for Malawi and 1:2500 for Tanzania. Increased use of im- proved maize varieties and mineral fertilizers, coupled with increased extension services and the absence of devastating droughts are the key factors promoting the accelerated growth in maize productivity in Ethiopia. Ethiopia took a homegrown solutions approach to the research and development of its maize and other commodities. The lesson from Ethiopia ’ s experience with maize is that sustained investment in agricul- tural research and development and policy support by the national government are crucial for continued growth of agricultur

    SUDOSCAN: A Simple, Rapid, and Objective Method with Potential for Screening for Diabetic Peripheral Neuropathy.

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    Clinical methods of detecting diabetic peripheral neuropathy (DPN) are not objective and reproducible. We therefore evaluated if SUDOSCAN, a new method developed to provide a quick, non-invasive and quantitative assessment of sudomotor function can reliably screen for DPN. 70 subjects (45 with type 1 diabetes and 25 healthy volunteers [HV]) underwent detailed assessments including clinical, neurophysiological and 5 standard cardiovascular reflex tests (CARTs). Using the American Academy of Neurology criteria subjects were classified into DPN and No-DPN groups. Based on CARTs subjects were also divided into CAN, subclinical-CAN and no-CAN. Sudomotor function was assessed with measurement of hand and foot Electrochemical Skin Conductance (ESC) and calculation of the CAN risk score. Foot ESC (ÎŒS) was significantly lower in subjects with DPN [n = 24; 53.5(25.1)] compared to the No-DPN [77.0(7.9)] and HV [77.1(14.3)] groups (ANCOVA p<0.001). Sensitivity and specificity of foot ESC for classifying DPN were 87.5% and 76.2%, respectively. The area under the ROC curve (AUC) was 0.85. Subjects with CAN had significantly lower foot [55.0(28.2)] and hand [53.5(19.6)] ESC compared to No-CAN [foot ESC, 72.1(12.2); hand ESC 64.9(14.4)] and HV groups (ANCOVA p<0.001 and 0.001, respectively). ROC analysis of CAN risk score to correctly classify CAN revealed a sensitivity of 65.0% and specificity of 80.0%. AUC was 0.75. Both foot and hand ESC demonstrated strong correlation with individual parameters and composite scores of nerve conduction and CAN. SUDOSCAN, a non-invasive and quick test, could be used as an objective screening test for DPN in busy diabetic clinics, insuring adherence to current recommendation of annual assessments for all diabetic patients that remains unfulfilled

    Relationship Between Risk Factors and Mortality in Type 1 Diabetic Patients in Europe: The EURODIAB Prospective Complications Study (PCS)

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    OBJECTIVE—The purpose of this study was to examine risk factors for mortality in patients with type 1 diabetes
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