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

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

Wheat and teff grain mineral micronutrient concentration and field data from GeoNutrition on-farm field experiments in Western Amhara region, Ethiopia

The data set comprises primary data for the concentration of over 25 mineral micronutrients including zinc (Zn) and selenium (Se) in wheat (Triticum aestivum L.) and teff (Eragrostis tef (Zucc.) Trotter) grown over two cropping seasons (2018 and 2019) in the Western Amhara region of Ethiopia. Wheat and teff were grown across a landscape gradient (hill slope, mid-slope, foot slope) and supplied with different rates of mineral nitrogen fertilizer and different Zn and Se fertilizer application methods (basal, basal + side dressing, basal + foliar fertilizer) across different farms. The data set also comprises of field data including specific study site, crop variety, fertilizer rates, and crop yields. Wheat experiments were performed in Debre Mewi and Markuma, and experiments with teff were performed in Debre Mewi and Aba Gerima. The concentrations of micronutrients in grain were measured using inductively coupled plasma mass spectrometry (ICP-MS). Laboratory standards, sample replicates and blank samples were included for quality assurance. The work provide insights on an effect of Zn, Se and N fertilizer, landscape position, and its interaction with micronutrient fertilizers on grain micronutrient concentrations. Agronomic biofortification of wheat and teff with micronutrient fertilizers was influenced by landscape position, the micronutrient fertilizer application method and N fertilizer management. The complexity of smallholder environmental settings and different farmer socio-economic opportunities calls for the optimization of nutritional agronomy landscape trials, with targeted application of micronutrient fertilizers across a landscape gradient required as an additional factor for consideration in ongoing agronomic biofortification interventions