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Acid soil effects on cereal crop
productivity in Ethiopia:
A prototype for enhancing crop management
James Warner, Office Head-ESAO, IFPRI, Addis Ababa
Michael Mann, Associate Prof, GWU, Washington D.C.
EEA conference, Addis Ababa | July 19, 2019
Overview
I. Objectives—purpose of presentation
II. Background—multidisciplinary (soil scientists and economists)
III. Data—AgSS, EthioSIS and remote sensed data
IV. Today’s research objective: focus on soil pH and productivity
V. Preliminary results
VI. Next steps/way forward
Objectives
 Introduce EthioSIS data in economic research:
oToday’s focus on pH (acid soil), crop productivity and lime
application for acid soil mitigation
oBegin to address (pH) crop productivity loss and relative
inefficiencies of fertilizers in acidic soils
oThe goal is to balance pH and use fertilizers more effectively
 The problem:
oAccording to EthioSIS, 28% of arable land in Ethiopia is acidic
oAt lower and higher pH levels, there are negative effects on crop
productivity (think quadratic function)
Objectives—Specific Research Objectives
Creating an effective national intervention strategy for acid soil reclamation (liming)
 Overview current pH and productivity and pH and fertilizer use
 Develop regression models estimating crop productivity
 Using econometric models:
o estimate productivity gains moving pH from 5.5 to 6.5
o Amount of fertilizer to achieve productivity at 6.5 pH (holding pH at 5.5)
 Create NPV of five years of estimated benefits of a single lime application versus
multi-year fertilizer application
 Create dashboard at kebele/woreda level indicating highest cost benefit ratios
(biggest productivity gains in productive areas at lowest costs)
Background
Small Holder
Farmers
Economist
Soil Scientist
• Farm
management
• Inputs
• Land area
• Soil health
• Soil quality
• Weather patterns
• Agro-ecology
• Remote sensing
data
Econometrics—
productivity
• Value of output
• Profitability
• Crop
models
• Field
studies
• Crop suitability
maps
• Crop yields
Existing Methodologies of Soil Scientists and Economists—
Develop Multi-disciplinary analysis
Background
Small Holder
Farmers
Economist
Soil Scientist
• Farm
management
• Inputs
• Land area
• Soil health
• Soil quality
• Weather patterns
• Agro-ecology
• Remote sensing
data
Econometrics—
Productivity
• Value of output
• Profitability
• Crop
models
• Field
studies
• Crop suitability
maps
• Crop yields
Existing Methodologies of Soil Scientists and Economists—
Develop Multi-disciplinary analysis
Background
Research is multifaceted
• Business models for lime
application for acid soil reclamation
(both demand/supply issues)
• Original work started with ATA
request about farmer lime
awareness (July 2016)
Creating an effective national intervention strategy for acid soil
reclamation (liming)
The Data
AgSS—Agriculture Sample Survey
o 1,750 sample areas over 7 Meher
seasons (2010/11 to 2016/17) for
approx. 12,250 observations
o 20 households per sample but
aggregated to the sub-kebele or
enumeration area (“super-farmer”)
o Area has median 23 sq. kms
o Variables include: extension,
improved seed, fertilizer, irrigation and
reported crop damage
Other data (remote sensed):
Elevation—meters above sea level
Palmer drought index (PDSI)-- is a
measurement of dryness based on recent
precipitation and temperature.
The Data
EthioSIS—Ethiopian Soil Information System
o Soil fertility mapping survey of Ethiopia.
o Twenty-two different soil properties
o Values are projected to EA area
o Variables include pH (mapped), Organic carbon
content (SOC), Sand content %, (SND), Cation
exchange capacity (CEC)
Organic carbon (+)--Soil organic carbon (SOC) is a strong
determinant of soil fertility through its positive effects
on soil structure and soil chemical and biological properties
which stimulate production
Sand Content (-) Sandy soil loses water at a high rate
leading to a low level of water retention that is unsuitable for
plant growth
CEC (+) Soils with low CEC will often suffer from a deficiency
in important nutrients like potassium and magnesium
Today’s research objective: Focus on pH
Assumptions:
pH below 6.5—acidic
pH below 5.5—highly acidic
pH above 7.3—alkaline
Optimal production pH 6.5 to 7 (neutral)
3 Mt of lime per ha to increase pH (5.5 to 6.5)
Unlike fertilizer, lime has strong carryover effects
and one application lasts 5 to 7 years
Preliminary Results—Basic Statistics
Simple graph relating OPH to pH
levels. Wheat/Barley match
quadratic and peak between 6 and
7. Maize is less sensitive to pH
and the results are not as robust.
Preliminary Results—Basic Statistics
Simple graph relating fertilizer use to
pH levels in the soil.
From 5.5 to 7.0:
Oromia, SNNP and Tigray: Increase
fertilizer with higher pH. Tigray has a
few outliers at highly acidic areas.
Exception is Amhara which seems to
be increasing fertilizer with lower pH.
Farmers may be trying to counteract
declining yields with more fertilizer.
Preliminary Results—Basic Model
Models are crop specific on
productivity output per hectare
(wheat, barley, maize)
Most correct sign and statistically
significant
Splines are used to capture non-
linear effects (5 knots)
Preliminary Results—Basic Model
Output per ha gain changing pH from 5.5 to 6.5
Estimates from model, increasing
pH, holding all other variables at
their means. Ex. Barley increases
21.2% increasing pH from 5.5 to 6.5
(Obviously, trouble with est. at tails!)
Next Steps
 Complete dashboard for national
intervention (fertilizer impacts/balance
pH, NPV, cost benefit at kebele or
woreda)
 Experience sharing internationally
(e.g. Tanzania)
 Implement research at farm
household level to determine the
effects of liming at the smallholder
level
")Ambo
Dese
Gimbi
Fiche
Ab Ala
Woliso
Shambu
SekotaGonder
Kemise
Keliwan
Maychew
Nekemte
Weldiya
Injbara
Dalifagi
Adeb Tole
Debre Tabor
Debre Birhan
Finote Selam
Debre Markos
Mekele
Nazret
Bahir Dar
Guder
Dejen
Lime Transportation Model—Amhara
Thank you!
Dejen lime crushing facility Acid Soil Healthy Soil

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Acid soil effects on cereal crop productivity in Ethiopia:A prototype for enhancing crop management

  • 1. Acid soil effects on cereal crop productivity in Ethiopia: A prototype for enhancing crop management James Warner, Office Head-ESAO, IFPRI, Addis Ababa Michael Mann, Associate Prof, GWU, Washington D.C. EEA conference, Addis Ababa | July 19, 2019
  • 2. Overview I. Objectives—purpose of presentation II. Background—multidisciplinary (soil scientists and economists) III. Data—AgSS, EthioSIS and remote sensed data IV. Today’s research objective: focus on soil pH and productivity V. Preliminary results VI. Next steps/way forward
  • 3. Objectives  Introduce EthioSIS data in economic research: oToday’s focus on pH (acid soil), crop productivity and lime application for acid soil mitigation oBegin to address (pH) crop productivity loss and relative inefficiencies of fertilizers in acidic soils oThe goal is to balance pH and use fertilizers more effectively  The problem: oAccording to EthioSIS, 28% of arable land in Ethiopia is acidic oAt lower and higher pH levels, there are negative effects on crop productivity (think quadratic function)
  • 4. Objectives—Specific Research Objectives Creating an effective national intervention strategy for acid soil reclamation (liming)  Overview current pH and productivity and pH and fertilizer use  Develop regression models estimating crop productivity  Using econometric models: o estimate productivity gains moving pH from 5.5 to 6.5 o Amount of fertilizer to achieve productivity at 6.5 pH (holding pH at 5.5)  Create NPV of five years of estimated benefits of a single lime application versus multi-year fertilizer application  Create dashboard at kebele/woreda level indicating highest cost benefit ratios (biggest productivity gains in productive areas at lowest costs)
  • 5. Background Small Holder Farmers Economist Soil Scientist • Farm management • Inputs • Land area • Soil health • Soil quality • Weather patterns • Agro-ecology • Remote sensing data Econometrics— productivity • Value of output • Profitability • Crop models • Field studies • Crop suitability maps • Crop yields Existing Methodologies of Soil Scientists and Economists— Develop Multi-disciplinary analysis
  • 6. Background Small Holder Farmers Economist Soil Scientist • Farm management • Inputs • Land area • Soil health • Soil quality • Weather patterns • Agro-ecology • Remote sensing data Econometrics— Productivity • Value of output • Profitability • Crop models • Field studies • Crop suitability maps • Crop yields Existing Methodologies of Soil Scientists and Economists— Develop Multi-disciplinary analysis
  • 7. Background Research is multifaceted • Business models for lime application for acid soil reclamation (both demand/supply issues) • Original work started with ATA request about farmer lime awareness (July 2016) Creating an effective national intervention strategy for acid soil reclamation (liming)
  • 8. The Data AgSS—Agriculture Sample Survey o 1,750 sample areas over 7 Meher seasons (2010/11 to 2016/17) for approx. 12,250 observations o 20 households per sample but aggregated to the sub-kebele or enumeration area (“super-farmer”) o Area has median 23 sq. kms o Variables include: extension, improved seed, fertilizer, irrigation and reported crop damage Other data (remote sensed): Elevation—meters above sea level Palmer drought index (PDSI)-- is a measurement of dryness based on recent precipitation and temperature.
  • 9. The Data EthioSIS—Ethiopian Soil Information System o Soil fertility mapping survey of Ethiopia. o Twenty-two different soil properties o Values are projected to EA area o Variables include pH (mapped), Organic carbon content (SOC), Sand content %, (SND), Cation exchange capacity (CEC) Organic carbon (+)--Soil organic carbon (SOC) is a strong determinant of soil fertility through its positive effects on soil structure and soil chemical and biological properties which stimulate production Sand Content (-) Sandy soil loses water at a high rate leading to a low level of water retention that is unsuitable for plant growth CEC (+) Soils with low CEC will often suffer from a deficiency in important nutrients like potassium and magnesium
  • 10. Today’s research objective: Focus on pH Assumptions: pH below 6.5—acidic pH below 5.5—highly acidic pH above 7.3—alkaline Optimal production pH 6.5 to 7 (neutral) 3 Mt of lime per ha to increase pH (5.5 to 6.5) Unlike fertilizer, lime has strong carryover effects and one application lasts 5 to 7 years
  • 11. Preliminary Results—Basic Statistics Simple graph relating OPH to pH levels. Wheat/Barley match quadratic and peak between 6 and 7. Maize is less sensitive to pH and the results are not as robust.
  • 12. Preliminary Results—Basic Statistics Simple graph relating fertilizer use to pH levels in the soil. From 5.5 to 7.0: Oromia, SNNP and Tigray: Increase fertilizer with higher pH. Tigray has a few outliers at highly acidic areas. Exception is Amhara which seems to be increasing fertilizer with lower pH. Farmers may be trying to counteract declining yields with more fertilizer.
  • 13. Preliminary Results—Basic Model Models are crop specific on productivity output per hectare (wheat, barley, maize) Most correct sign and statistically significant Splines are used to capture non- linear effects (5 knots)
  • 14. Preliminary Results—Basic Model Output per ha gain changing pH from 5.5 to 6.5 Estimates from model, increasing pH, holding all other variables at their means. Ex. Barley increases 21.2% increasing pH from 5.5 to 6.5 (Obviously, trouble with est. at tails!)
  • 15. Next Steps  Complete dashboard for national intervention (fertilizer impacts/balance pH, NPV, cost benefit at kebele or woreda)  Experience sharing internationally (e.g. Tanzania)  Implement research at farm household level to determine the effects of liming at the smallholder level ")Ambo Dese Gimbi Fiche Ab Ala Woliso Shambu SekotaGonder Kemise Keliwan Maychew Nekemte Weldiya Injbara Dalifagi Adeb Tole Debre Tabor Debre Birhan Finote Selam Debre Markos Mekele Nazret Bahir Dar Guder Dejen Lime Transportation Model—Amhara
  • 16. Thank you! Dejen lime crushing facility Acid Soil Healthy Soil