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Spatial variation in fertilizer prices in Sub-Saharan Africa
Low crop yields in Sub-Saharan Africa are associated with low fertilizer use. To better understand patterns of, and opportunities for, fertilizer use, location specific fertilizer price data may be relevant. We compiled local market price data for urea fertilizer, a source of inorganic nitrogen, in...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6959603/ https://www.ncbi.nlm.nih.gov/pubmed/31935246 http://dx.doi.org/10.1371/journal.pone.0227764 |
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author | Bonilla Cedrez, Camila Chamberlin, Jordan Guo, Zhe Hijmans, Robert J. |
author_facet | Bonilla Cedrez, Camila Chamberlin, Jordan Guo, Zhe Hijmans, Robert J. |
author_sort | Bonilla Cedrez, Camila |
collection | PubMed |
description | Low crop yields in Sub-Saharan Africa are associated with low fertilizer use. To better understand patterns of, and opportunities for, fertilizer use, location specific fertilizer price data may be relevant. We compiled local market price data for urea fertilizer, a source of inorganic nitrogen, in 1729 locations in eighteen countries in two regions (West and East Africa) from 2010–2018 to understand patterns in the spatial variation in fertilizer prices. The average national price was lowest in Ghana (0.80 USD kg(-1)), Kenya (0.97 USD kg(-1)), and Nigeria (0.99 USD kg(-1)). Urea was most expensive in three landlocked countries (Burundi: 1.51, Uganda: 1.49, and Burkina Faso: 1.49 USD kg(-1)). Our study uncovers considerable spatial variation in fertilizer prices within African countries. We show that in many countries this variation can be predicted for unsampled locations by fitting models of prices as a function of longitude, latitude, and additional predictor variables that capture aspects of market access, demand and environmental conditions. Predicted within-country urea price variation (as a fraction of the median price) was particularly high in Kenya (0.77–1.12), Nigeria (0.83–1.34), Senegal (0.73–1.40), Tanzania (0.90–1.29) and Uganda (0.93–1.30), but much lower in Burkina Faso (0.96–1.04), Burundi (0.95–1.05), and Togo (0.94–1.05). The correlation coefficient of the country level models was between 0.17 to 0.83 (mean 0.52) and the RMSE varies from 0.005 to 0.188 (mean 0.095). In 10 countries, predictions were at least 25% better than a null-model that assumes no spatial variation. Our work indicates new opportunities for incorporating spatial variation in prices into efforts to understand the profitability of agricultural technologies across rural areas in Sub-Saharan Africa. |
format | Online Article Text |
id | pubmed-6959603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-69596032020-01-26 Spatial variation in fertilizer prices in Sub-Saharan Africa Bonilla Cedrez, Camila Chamberlin, Jordan Guo, Zhe Hijmans, Robert J. PLoS One Research Article Low crop yields in Sub-Saharan Africa are associated with low fertilizer use. To better understand patterns of, and opportunities for, fertilizer use, location specific fertilizer price data may be relevant. We compiled local market price data for urea fertilizer, a source of inorganic nitrogen, in 1729 locations in eighteen countries in two regions (West and East Africa) from 2010–2018 to understand patterns in the spatial variation in fertilizer prices. The average national price was lowest in Ghana (0.80 USD kg(-1)), Kenya (0.97 USD kg(-1)), and Nigeria (0.99 USD kg(-1)). Urea was most expensive in three landlocked countries (Burundi: 1.51, Uganda: 1.49, and Burkina Faso: 1.49 USD kg(-1)). Our study uncovers considerable spatial variation in fertilizer prices within African countries. We show that in many countries this variation can be predicted for unsampled locations by fitting models of prices as a function of longitude, latitude, and additional predictor variables that capture aspects of market access, demand and environmental conditions. Predicted within-country urea price variation (as a fraction of the median price) was particularly high in Kenya (0.77–1.12), Nigeria (0.83–1.34), Senegal (0.73–1.40), Tanzania (0.90–1.29) and Uganda (0.93–1.30), but much lower in Burkina Faso (0.96–1.04), Burundi (0.95–1.05), and Togo (0.94–1.05). The correlation coefficient of the country level models was between 0.17 to 0.83 (mean 0.52) and the RMSE varies from 0.005 to 0.188 (mean 0.095). In 10 countries, predictions were at least 25% better than a null-model that assumes no spatial variation. Our work indicates new opportunities for incorporating spatial variation in prices into efforts to understand the profitability of agricultural technologies across rural areas in Sub-Saharan Africa. Public Library of Science 2020-01-14 /pmc/articles/PMC6959603/ /pubmed/31935246 http://dx.doi.org/10.1371/journal.pone.0227764 Text en © 2020 Bonilla Cedrez et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bonilla Cedrez, Camila Chamberlin, Jordan Guo, Zhe Hijmans, Robert J. Spatial variation in fertilizer prices in Sub-Saharan Africa |
title | Spatial variation in fertilizer prices in Sub-Saharan Africa |
title_full | Spatial variation in fertilizer prices in Sub-Saharan Africa |
title_fullStr | Spatial variation in fertilizer prices in Sub-Saharan Africa |
title_full_unstemmed | Spatial variation in fertilizer prices in Sub-Saharan Africa |
title_short | Spatial variation in fertilizer prices in Sub-Saharan Africa |
title_sort | spatial variation in fertilizer prices in sub-saharan africa |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6959603/ https://www.ncbi.nlm.nih.gov/pubmed/31935246 http://dx.doi.org/10.1371/journal.pone.0227764 |
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