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Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach
Despite the routine collection of annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has integrated these data sources in estimating developing nations’ agricultural yields. In this paper, we explore the determinants of wheat output p...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Scientific Pub. Co
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5268337/ https://www.ncbi.nlm.nih.gov/pubmed/28163360 http://dx.doi.org/10.1016/j.fcr.2016.10.014 |
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author | Mann, Michael L. Warner, James M. |
author_facet | Mann, Michael L. Warner, James M. |
author_sort | Mann, Michael L. |
collection | PubMed |
description | Despite the routine collection of annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has integrated these data sources in estimating developing nations’ agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011–2013 principal Meher crop seasons at the kebele administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. Reflecting on the high interannual variability in output per hectare, we explore whether these changes can be explained by weather, shocks to, and management of rain-fed agricultural systems. The model identifies specific contributors to wheat yields that include farm management techniques (e.g. area planted, improved seed, fertilizer, and irrigation), weather (e.g. rainfall), water availability (e.g. vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their locally attainable wheat yields given their altitude, weather conditions, terrain, and plant health. In conclusion, we believe the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels. |
format | Online Article Text |
id | pubmed-5268337 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier Scientific Pub. Co |
record_format | MEDLINE/PubMed |
spelling | pubmed-52683372017-02-01 Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach Mann, Michael L. Warner, James M. Field Crops Res Research Paper Despite the routine collection of annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has integrated these data sources in estimating developing nations’ agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011–2013 principal Meher crop seasons at the kebele administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. Reflecting on the high interannual variability in output per hectare, we explore whether these changes can be explained by weather, shocks to, and management of rain-fed agricultural systems. The model identifies specific contributors to wheat yields that include farm management techniques (e.g. area planted, improved seed, fertilizer, and irrigation), weather (e.g. rainfall), water availability (e.g. vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their locally attainable wheat yields given their altitude, weather conditions, terrain, and plant health. In conclusion, we believe the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels. Elsevier Scientific Pub. Co 2017-02-01 /pmc/articles/PMC5268337/ /pubmed/28163360 http://dx.doi.org/10.1016/j.fcr.2016.10.014 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Mann, Michael L. Warner, James M. Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach |
title | Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach |
title_full | Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach |
title_fullStr | Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach |
title_full_unstemmed | Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach |
title_short | Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach |
title_sort | ethiopian wheat yield and yield gap estimation: a spatially explicit small area integrated data approach |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5268337/ https://www.ncbi.nlm.nih.gov/pubmed/28163360 http://dx.doi.org/10.1016/j.fcr.2016.10.014 |
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