Summary
This study developed spatially-explicit predictive models for selenium concentration in teff and wheat grain across Amhara Region, Ethiopia, integrating soil measurements, remote-sensing data, and topographic variables. Substantial spatial variation in grain selenium was observed, with wheat and teff showing different absolute concentrations but similar broad spatial patterns. The authors propose this geospatial approach could target interventions for selenium deficiency and be adapted to map other micronutrients in similar settings.
UK applicability
The methodology for spatial prediction of crop micronutrient concentration and uncertainty characterisation is transferable to UK cereal production contexts, though the specific soil–climate–crop relationships and baseline selenium status differ markedly. UK grain selenium is generally adequate due to higher soil selenium availability and imported feeds, making direct application less urgent but the statistical framework potentially valuable for other micronutrient mapping.
Key measures
Selenium concentration in grain (teff and wheat) and soils; soil physicochemical properties; remote-sensing and digital elevation model derivatives; cross-validated prediction error variances; probability of meeting selenium dietary adequacy per serving
Outcomes reported
The study mapped spatial variation in selenium concentration across teff and wheat grain in Amhara Region, Ethiopia, using predictive models incorporating soil properties and remote-sensing covariates. Uncertainty in predictions was characterised by computing the probability that grain selenium content would meet recommended daily allowance targets.
Topic tags
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