collecting the dirt on soils: advancements in plot-level soil testing and implications for...
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Collecting the Dirt on Soils:Advancements in Plot-Level Soil Testing and Implications for Agricultural Statistics
http://www.worldagroforestry.org/research/land-health
Ermias Betemariam (e.betemariam@cgiar.org)
Sydney Gourlay Keith Shepherd
Context
2Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Innovations in Agricultural Statistics
• Administrative data is often seen as methodologically flawed and
lacks credibility
• Lack of consistent, good quality data on soil health
• Data collection methods
• The role of technology
• What works in developing countries?
Context (2)
3Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Methodological improvements in smallholder agricultural statistics for decision making
http://www.csa.gov.et/index.php/component/content/article/14-survey-reports/123-latest-national-statistics-abstract
Objectives
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Improving measurements of agricultural productivity by combining household level and soil fertility data
• Develop soil-plant spectral analytical methods and diagnostic tools for rapid, low cost and reliable assessment of soil samples using light (Technology)
• Demonstrate applicability of integrating scientific method of soil quality assessment along with the socio-economic panel data
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Field data
5Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
3661 soil samples collected from three agro-ecologica zones
• Household socio-economic data• Subjective assessment of soil quality
• Soil sampling• Objective assessment of soil quality
Lab analyses
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015| 6
Laser Diffraction Particle Size Analysis(LDPSA)
Total X-ray Fluorescence spectroscopy (TXRF) for elemental analysis
FT Diffuse reflectance MIR Alpha MIR spectrometer
Instrumentation Dispersive VNIRFT-NIR FT-MIR
Handheld NIR/MIR
•Portable•Repeatability?•External service•No validation
•Benchtop•Repeatability•Self serviceable•Validation in-built•ISO compliant•Industry proven•Multipurpose
•Benchtop•Repeatability•No gas purging•Some servicing•Robotic•Validation in-built•ISO compliant•Outperforms NIR
•Handheld•Sample
homogeneity?•Variable
moisture?•Repeatability?•Still expensive•Rapidly
developing•Need to prepare
by developing soil reference libraries
Working on Rural labs
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015| 7
Lab analyses (2)
Why infrared spectroscopy?
Rapid Low cost Reproducible Predicts many soil functional properties
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015| 8
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Land Health applicationsAfrica Soil Spectroscopy Lab Network
EthioSIS 97 Sentinel sites
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
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Mid-infrared spectroscopy strongly predicts soil properties
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
MIR- reflectance
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Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Objective vs subjective soil quality measurements
Farmers use soil texture and color to describe soil qualities
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Soil carbon and pH values
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Objective vs subjective soil quality measurements
SOC (95% CI): 3.18 - 3.30%
pH(95% CI): 6.28 - 6.34
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Objective vs subjective soil quality measurements
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Soil quality indicators
USDA: http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/health/assessment/?cid=stelprdb1237387
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Subjective soil quality assessment poorly correlated to the scientific output
Science: about 17% of the soils have SOC < 2% but only 5%= poor soils
Local respondents identified only 5% of the as poor soils
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Objective vs subjective soil quality measurements
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Age Sex Literacy
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Objective vs subjective soil quality measurements
Age class, sex, and literacy did not significantly influence the subjectiveGrading of soil quality
Farmers better identify poor and not-poor soils but not “Fair soils” that future Questions should consider
10 50 100 150 200 2500
2000
4000
6000NIR spectroscopyThermal oxidationSample preparation
Number of samples
Ca
rbo
n m
ea
surm
en
t co
st (
US
D)
Pers...
Oth
ers0
3
6
9
12
15 NIR spectroscopyThermal oxidationSample preparation
Ca
rbo
n m
ea
sure
me
nt
cost
pe
r sa
mp
le (
US
D)
Cost –error analysis
0 500 1000 15000
2000
4000
6000
8000Thermal oxidation
Number of samples
Carb
on m
easu
rem
ent
cost
(USD
)Comparisons of costs of measuring SOC using a commercial lab and NIR
CostIR is cheaper (<~ 56%) than combustion method for large number of samples
ThroughputCombustion ~ 30-60 samples/dayNIR ~ 350 samples/dayMIR ~ 1000/day
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015| 17
Surveillance science Land health metrics
Consistent field protocol
Soil spectroscopyCoupling with remote sensing
Sentinel sites Randomized sampling schemes
Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015| 18
AfSIS: Soil functional propertiesFrom polygon-based to probabilistic mapping
+
Probability of observingcultivation
Current lime requirement ? ~ min [prob(pH < 5.5), prob(cult)]
Probability topsoil pH < 5.5 ... very acid soils
Grid-based probabilistic maps increases the reliability of the map and its power to be combined with other data sources (remote sensing & terrain data)
(Walsh, 2013)
=
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Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
• More research on cost-effective measurement tools- the future is bright• Subjective and objective measurement results do not much well• It was possible to integrate soil health measurement into the panel
household survey• Enhancing our understanding of household attributes, land management
practices and soil health management• Enable decision makers have clear understanding of soil status and trends
Finally…
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Ermias Betemariam| ISI2005 2015, | Rio de Janeiro| July 2015|
Smart data - Smart decisions
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