Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

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

Dawd Gashu, R. M. Lark, Alice E. Milne, Tilahun Amede, Elizabeth H. Bailey, Christopher Chagumaira, S. J. Dunham, S. Gameda, Diriba B. Kumssa, Abdul‐Wahab Mossa, Markus Walsh, Lolita Wilson, Scott D. Young, E. Louise Ander, Martin R. Broadley, Edward J. M. Joy, S. P. McGrath

The Science of The Total Environment · 2020

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Summary

This spatial study characterised selenium concentration variation across teff and wheat grain in Amhara, Ethiopia, using geostatistical modelling informed by soil properties and environmental covariates. Selenium concentrations differed between the two grains but exhibited consistent broad spatial patterns, with substantial regional variation. The authors present a general methodological framework for mapping micronutrient adequacy in grain and identifying geographical targeting opportunities for nutritional interventions.

UK applicability

The methodology for spatial micronutrient mapping and uncertainty quantification is transferable, though UK cereal systems differ in climate, soil conditions, and current selenium status. The application to identifying population-level micronutrient deficits may be more relevant to other low-income settings with documented micronutrient gaps.

Key measures

Selenium concentration in grain (teff and wheat) and soil; remote-sensed covariates; digital elevation model predictors; prediction error variances; probability of inadequate selenium intake per serving

Outcomes reported

The study mapped predicted selenium concentrations across teff and wheat grain in Amhara Region, Ethiopia, and quantified spatial variation and uncertainty using geostatistical methods. It computed the probability that standard servings of grain would fail to provide the recommended daily allowance of selenium.

Theme
Nutrition & health
Subject
Micronutrients & dietary adequacy
Study type
Research
Study design
Observational field survey with spatial prediction modelling
Source type
Peer-reviewed study
Status
Published
Geography
Ethiopia
System type
Arable cereals
DOI
10.1016/j.scitotenv.2020.139231
Catalogue ID
BFmovi1txm-0izzel

Topic tags

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