Summary
This study conducted a large-scale spatial survey of selenium concentration in teff and wheat grain across Amhara Region, Ethiopia, motivated by documented selenium deficiency in the population. Using predictive linear mixed models incorporating soil properties and remote-sensed environmental covariates, the authors developed maps of grain selenium concentration with quantified uncertainty, demonstrating substantial spatial variation and differing but parallel patterns between the two grain types. The approach provides a generalizable methodology for targeting micronutrient interventions and could be adapted to map other micronutrients and crops in similar agroecological settings.
UK applicability
The spatial modelling methodology may be transferable to UK cereal production systems to identify regional variation in grain micronutrient concentrations, though UK selenium status differs substantially from Ethiopia. The approach could inform precision agronomic interventions and food composition databases in temperate climates.
Key measures
Grain selenium concentration (teff and wheat); soil selenium concentration (multiple extractants); soil properties; remote-sensed covariates and digital elevation model variables; prediction error variances; probability of adequate selenium intake per serving
Outcomes reported
The study mapped spatial variation in selenium concentration across teff and wheat grain in Amhara Region, Ethiopia, using predictive models based on soil properties and remote-sensed covariates. The predictions included quantified uncertainty and probability estimates of whether grain selenium content would meet recommended daily allowance thresholds.
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