Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics
Much of the current analysis on agricultural productivity is hampered by the lack of consistent, high quality data on soil health and how it is changing under past and current management. Historically, plot-level statistics derived from household s...
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| Format: | Working Paper |
| Language: | English en_US |
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World Bank, Washington, DC
2017
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| Online Access: | http://documents.worldbank.org/curated/en/748621494523429244/Collecting-the-dirt-on-soils-advancements-in-plot-level-soil-testing-and-implications-for-agricultural-statistics http://hdl.handle.net/10986/26736 |
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okr-10986-267362021-06-14T10:14:16Z Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics Carletto, Calogero Aynekulu, Ermias Gourlay, Sydney Shepherd, Keith LAND PRODUCTIVITY HOUSEHOLD SURVEYS SOIL SPECTROSCOPY SOIL FERTILITY LOCAL KNOWLEDGE AGRICULTURE STATISTICS Much of the current analysis on agricultural productivity is hampered by the lack of consistent, high quality data on soil health and how it is changing under past and current management. Historically, plot-level statistics derived from household surveys have relied on subjective farmer assessments of soil quality or, more recently, publicly available geospatial data. The Living Standards Measurement Study of the World Bank implemented a methodological study in Ethiopia, which resulted in an unprecedented data set encompassing a series of subjective indicators of soil quality as well as spectral soil analysis results on plot-specific soil samples for 1,677 households. The goals of the study, which was completed in partnership with the World Agroforestry Centre and the Central Statistical Agency of Ethiopia, were twofold: (1) evaluate the feasibility of integrating a soil survey into household socioeconomic data collection operations, and (2) evaluate local knowledge of farmers in assessing their soil quality. Although a costlier method than subjective assessment, the integration of spectral soil analysis in household surveys has potential for scale-up. In this study, the first large scale study of its kind, enumerators spent approximately 40 minutes per plot collecting soil samples, not a particularly prohibitive figure given the proper timeline and budget. The correlation between subjective indicators of soil quality and key soil properties, such as organic carbon, is weak at best. Evidence suggests that farmers are better able to distinguish between soil qualities in areas with greater variation in soil properties. Descriptive analysis shows that geospatial data, while positively correlated with laboratory results and offering significant improvements over subject assessment, fail to capture the level of variation observed on the ground. The results of this study give promise that soil spectroscopy could be introduced into household panel surveys in smallholder agricultural contexts, such as Ethiopia, as a rapid and cost-effective soil analysis technique with valuable outcomes. Reductions in uncertainties in assessing soil quality and, hence, improvements in smallholder agricultural statistics, enable better decision-making. 2017-05-23T22:28:59Z 2017-05-23T22:28:59Z 2017-05 Working Paper http://documents.worldbank.org/curated/en/748621494523429244/Collecting-the-dirt-on-soils-advancements-in-plot-level-soil-testing-and-implications-for-agricultural-statistics http://hdl.handle.net/10986/26736 English en_US Policy Research Working Paper;No. 8057 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper Africa Ethiopia |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English en_US |
| topic |
LAND PRODUCTIVITY HOUSEHOLD SURVEYS SOIL SPECTROSCOPY SOIL FERTILITY LOCAL KNOWLEDGE AGRICULTURE STATISTICS |
| spellingShingle |
LAND PRODUCTIVITY HOUSEHOLD SURVEYS SOIL SPECTROSCOPY SOIL FERTILITY LOCAL KNOWLEDGE AGRICULTURE STATISTICS Carletto, Calogero Aynekulu, Ermias Gourlay, Sydney Shepherd, Keith Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics |
| geographic_facet |
Africa Ethiopia |
| relation |
Policy Research Working Paper;No. 8057 |
| description |
Much of the current analysis on
agricultural productivity is hampered by the lack of
consistent, high quality data on soil health and how it is
changing under past and current management. Historically,
plot-level statistics derived from household surveys have
relied on subjective farmer assessments of soil quality or,
more recently, publicly available geospatial data. The
Living Standards Measurement Study of the World Bank
implemented a methodological study in Ethiopia, which
resulted in an unprecedented data set encompassing a series
of subjective indicators of soil quality as well as spectral
soil analysis results on plot-specific soil samples for
1,677 households. The goals of the study, which was
completed in partnership with the World Agroforestry Centre
and the Central Statistical Agency of Ethiopia, were
twofold: (1) evaluate the feasibility of integrating a soil
survey into household socioeconomic data collection
operations, and (2) evaluate local knowledge of farmers in
assessing their soil quality. Although a costlier method
than subjective assessment, the integration of spectral soil
analysis in household surveys has potential for scale-up. In
this study, the first large scale study of its kind,
enumerators spent approximately 40 minutes per plot
collecting soil samples, not a particularly prohibitive
figure given the proper timeline and budget. The correlation
between subjective indicators of soil quality and key soil
properties, such as organic carbon, is weak at best.
Evidence suggests that farmers are better able to
distinguish between soil qualities in areas with greater
variation in soil properties. Descriptive analysis shows
that geospatial data, while positively correlated with
laboratory results and offering significant improvements
over subject assessment, fail to capture the level of
variation observed on the ground. The results of this study
give promise that soil spectroscopy could be introduced into
household panel surveys in smallholder agricultural
contexts, such as Ethiopia, as a rapid and cost-effective
soil analysis technique with valuable outcomes. Reductions
in uncertainties in assessing soil quality and, hence,
improvements in smallholder agricultural statistics, enable
better decision-making. |
| format |
Working Paper |
| author |
Carletto, Calogero Aynekulu, Ermias Gourlay, Sydney Shepherd, Keith |
| author_facet |
Carletto, Calogero Aynekulu, Ermias Gourlay, Sydney Shepherd, Keith |
| author_sort |
Carletto, Calogero |
| title |
Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics |
| title_short |
Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics |
| title_full |
Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics |
| title_fullStr |
Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics |
| title_full_unstemmed |
Collecting the Dirt on Soils : Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics |
| title_sort |
collecting the dirt on soils : advancements in plot-level soil testing and implications for agricultural statistics |
| publisher |
World Bank, Washington, DC |
| publishDate |
2017 |
| url |
http://documents.worldbank.org/curated/en/748621494523429244/Collecting-the-dirt-on-soils-advancements-in-plot-level-soil-testing-and-implications-for-agricultural-statistics http://hdl.handle.net/10986/26736 |
| _version_ |
1764462740653473792 |