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

OAR@ICRISAT

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Relation http://oar.icrisat.org/11547/
https://doi.org/10.1016/j.scitotenv.2020.139231
doi:10.1016/j.scitotenv.2020.139231
 
Title Spatial prediction of the concentration of selenium (Se) in grain across part of Amhara Region, Ethiopia
 
Creator Gashu, D
Lark, R M
Milne, A E
Amede, T
Bailey, E H
Chagumaira, C
Dunham, S J
Gameda, S
Kumssa, D B
Mossa, A W
Walsh, M G
Wilson, L
Young, S D
Ander, E L
Broadley, M R
Joy, E J M
McGrath, S P
 
Subject GIS Techniques/Remote Sensing
Plant Nutrition
Wheat
 
Description Grain and soilwere 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
grainswere developed, and the predicted values, alongwith observed concentrations in the two grainswere 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. Crossvalidation
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.
 
Publisher Elsevier
 
Date 2020-05
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Identifier http://oar.icrisat.org/11547/1/1-s2.0-S0048969720327480-main.pdf
Gashu, D and Lark, R M and Milne, A E and Amede, T and Bailey, E H and Chagumaira, C and Dunham, S J and Gameda, S and Kumssa, D B and Mossa, A W and Walsh, M G and Wilson, L and Young, S D and Ander, E L and Broadley, M R and Joy, E J M and McGrath, S P (2020) Spatial prediction of the concentration of selenium (Se) in grain across part of Amhara Region, Ethiopia. Science of The Total Environment (TSI), 733. pp. 1-16. ISSN 0048-9697