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8 results on '"Kumssa, D. B."'

2. Cereal grain mineral micronutrient and soil chemistry data from GeoNutrition surveys in Ethiopia and Malawi

Author

Kumssa, D. B., Mossa, A. W., Amede, T., Ander, E. L., Bailey, E. H., Botoman, L., Chagumaira, C., Chimungu, J. G., Davis, K., Gameda, S., Haefele, S. M., Hailu, K., Joy, E. J. M., Lark, R. M., Ligowe, I. S., McGrath, S. P., Milne, A., Muleya, P., Munthali, M., Towett, E., Walsh, M. G., Wilson, L., Young, S. D., Haji, I. R., Broadley, M. R., Gashu, D., and Nalivata, P. C.

Published
2022
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3. The nutritional quality of cereals varies geospatially in Ethiopia and Malawi

Author

Gashu, D., Nalivata, P. C., Amede, T., Ander, E. L., Bailey, E. H., Botoman, L., Chagumaira, C., Gameda, S., Haefele, S. M., Hailu, K., Joy, E. J. M., Kalimbira, A. A., Kumssa, D. B., Lark, R. M., Ligowe, I. S., McGrath, S. P., Milne, A. E., Mossa, A. W., Munthali, M., Towett, E. K., Walsh, M. G., Wilson, L., Young, S. D., and Broadley, M. R.

Published
2021
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4. Selenium Concentration in Cattle Serum and Fodder from Two Areas in Ethiopia with Contrasting Human Selenium Concentration

Author

Hailu, K., Gashu, D., Joy, E., Alonso, S., Gizaw, S., Gameda, S., Ander, E. L., Bailey, E., Wilson, L., Lark, R. M., Kumssa, D. B., and Broadley, M.

Subjects
Selenium, Cattle feed, General Immunology and Microbiology, Humans, Female, Amhara region, General Medicine, Ethiopia, Animal Feed, General Biochemistry, Genetics and Molecular Biology, Cattle selenium deficiency
Abstract

INTRODUCTION: Selenium (Se) is an essential mineral for livestock health and productivity. In cattle, Se deficiency is associated with delayed conception, growth retardation, and increased morbidity and mortality. METHODS: We conducted a survey of cattle serum (n = 224) and feed (n = 81) samples from two areas with contrasting human and cereal grain Se concentration in Ethiopia. The fodder samples include stover, straw, hay and pasture grass. Se concentration of the samples were measured using inductively coupled plasma-mass spectrometry. RESULTS: Serum Se concentration ranged from 14.9 to 167.8 μg L-1 (median, 41.4 μg L-1). Cattle from East Amhara had significantly greater serum Se concentration compared to cattle from West Amhara (median: 68.4 μg L-1 vs 25.7 μg L-1; p < 0.001). Overall, 79.8% of cattle had Se deficiency (

Published
2022

5. Soil and landscape factors influence geospatial variation in maize grain zinc concentration in Malawi

Author

Botoman, L., Chagumaira, C., Mossa, A. W., Amede, T., Ander, E. L., Bailey, E. H., Chimungu, J. G., Gameda, S., Gashu, D., Haefele, S. M., Joy, E. J. M., Kumssa, D. B., Ligowe, I. S., McGrath, S. P., Milne, A. E., Munthali, M., Towett, E., Walsh, M. G., Wilson, L., Young, S. D., Broadley, M. R., Lark, R. M., and Nalivata, P. C.

Subjects
Malawi, Minerals, Soil, Zinc, Multidisciplinary, Humans, Pentetic Acid, Edible Grain, Zea mays
Abstract

Dietary zinc (Zn) deficiency is widespread globally, and in particular among people in sub-Saharan Africa (SSA). In Malawi, dietary sources of Zn are dominated by maize and spatially dependent variation in grain Zn concentration, which will affect dietary Zn intake, has been reported at distances of up to ~ 100 km. The aim of this study was to identify potential soil properties and environmental covariates which might explain this longer-range spatial variation in maize grain Zn concentration. Data for maize grain Zn concentrations, soil properties, and environmental covariates were obtained from a spatially representative survey in Malawi (n = 1600 locations). Labile and non-labile soil Zn forms were determined using isotopic dilution methods, alongside conventional agronomic soil analyses. Soil properties and environmental covariates as potential predictors of the concentration of Zn in maize grain were tested using a priori expert rankings and false discovery rate (FDR) controls within the linear mixed model (LMM) framework that informed the original survey design. Mean and median grain Zn concentrations were 21.8 and 21.5 mg kg−1, respectively (standard deviation 4.5; range 10.0–48.1). A LMM for grain Zn concentration was constructed for which the independent variables: soil pH(water), isotopically exchangeable Zn (ZnE), and diethylenetriaminepentaacetic acid (DTPA) extractable Zn (ZnDTPA) had predictive value (p

Published
2021

6. Selenium deficiency risks in sub-Saharan African food systems and their geospatial linkages

Author

Ligowe, I. S., primary, Phiri, F. P., additional, Ander, E. L., additional, Bailey, E. H., additional, Chilimba, A. D. C., additional, Gashu, D., additional, Joy, E. J. M., additional, Lark, R. M., additional, Kabambe, V., additional, Kalimbira, A. A., additional, Kumssa, D. B., additional, Nalivata, P. C., additional, Young, S. D., additional, and Broadley, M. R., additional

Published
2020
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8. Spatial prediction of the concentration of selenium (Se) in grain across part of Amhara Region, Ethiopia.

Author

Gashu D, Lark RM, Milne AE, Amede T, Bailey EH, Chagumaira C, Dunham SJ, Gameda S, Kumssa DB, Mossa AW, Walsh MG, Wilson L, Young SD, Ander EL, Broadley MR, Joy EJM, and McGrath SP

Subjects
Edible Grain, Ethiopia, Soil, Triticum, Selenium
Abstract

Grain and soil were sampled across a large part of Amhara, Ethiopia in a study motivated by prior evidence of selenium (Se) deficiency in the Region's population. The grain samples (teff, Eragrostis tef, and wheat, Triticum aestivum) were analysed for concentration of Se and the soils were analysed for various properties, including Se concentration measured in different extractants. Predictive models for concentration of Se in the respective grains were developed, and the predicted values, along with observed concentrations in the two grains were represented by a multivariate linear mixed model in which selected covariates, derived from remote sensor observations and a digital elevation model, were included as fixed effects. In all modelling steps the selection of predictors was done using false discovery rate control, to avoid over-fitting, and using an α-investment procedure to maximize the statistical power to detect significant relationships by ordering the tests in a sequence based on scientific understanding of the underlying processes likely to control Se concentration in grain. Cross-validation indicated that uncertainties in the empirical best linear unbiased predictions of the Se concentration in both grains were well-characterized by the prediction error variances obtained from the model. The predictions were displayed as maps, and their uncertainty was characterized by computing the probability that the true concentration of Se in grain would be such that a standard serving would not provide the recommended daily allowance of Se. The spatial variation of grain Se was substantial, concentrations in wheat and teff differed but showed the same broad spatial pattern. Such information could be used to target effective interventions to address Se deficiency, and the general procedure used for mapping could be applied to other micronutrients and crops in similar settings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2020
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