Use of Near-infrared Spectroscopy for Monitoring and Analysis of Carbon Sequestration in Soil

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Use of Near-infrared Spectroscopy for Monitoring
and Analysis of Carbon Sequestration in Soil
by P.D. Martin, and D.F. Malley PDK Projects,
Inc. Winnipeg, Manitoba, Canada
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Vision

• Soil and plant analyses are available when and
  where they are needed
• Need for information, rather than analytical
  cost, to dictate the number and kinds of analyses
• Analyses promote sound, sustainable environmental
  and agricultural management

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Purpose

• Introduce Near-infrared Spectroscopy (NIRS)
• Describe
• Benefits to use of NIRS
• How NIR can be used for soil carbon assessment
• Services available from PDK

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NIR Facts

• NIRS provides rapid, chemical-free, flexible
  analysis
• NIRS is used globally for food and feed analysis
• NIRS has enormous potential for
  agro-environmental applications, including soil
  carbon assessment

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Near-infrared Spectroscopy

• Utilizes the absorbance of NIR light (780 - 2500
  nm) by vibrating bonds between atoms in molecules
• O-H, C-H, C-N, C-O, P-O, S-O
• Molecular spectroscopy - analyzes intact samples
• NIR absorbances obey the Beer/Lambert law

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The Work of Doing NIR Analysis

• Compositional information on samples (n gt100) is
  correlated with the spectral information to
  develop statistical calibration models
• The calibrations train the instrument to
  analyze future unknown samples

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Features

• does not destroy the sample
• is rapid, lt 2 min/test
• analyzes many constituents simultaneously
• analyzes compositional and functional properties
• field portable

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Lab and Field Instrument Zeiss Corona
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Organic Matter Compositional Parameters

• Organic matter/organic C
• OM, OC
• Total C (LECO)
• C HUMUS
• Humic acid fractions
• Humic and Fulvic
• Fulvic acid fractions
• Lignin content
• Cellulose content

r2 0.81-0.97 0.93-0.96 0.94 0.95 0.91 0.63 0.77-0.
83 0.81
Performance good exc. v.good -
exc. v.good v.good v.good poor good good
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Compositional Parameters contd

• r2 performance
• Clay 0.81-0.87 good
• Total N 0.86-0.96 good - v.good
• moisture 0.93-0.98 v.good exc.
• CEC 0.9 v.good

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Organic Carbon

• Miniota area
• Newdale Soil Assoc.
• Dried, ground samples (2mm)
• N 267
• 1100 - 2500 nm
• r2 0.78
• SEP 0.33

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Field-moist applications

• Moisture corrected calibration
• 0.033 and 1.5 MPa moisture tension
• r2 0.89
• SEP 0.23
• Range 0.45 3.16 OC

Sudduth, K.A. and J.W. Hummel (1993). Soil
organic matter, CEC and moisture sensing with a
portable NIR spectrophotometer. Trans of the
ASAE 361571-1582
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Example of On-site Soil Testing Method

• Soil cores - grid or stratified sampling
• Cores sliced on-site
• Presentation of static, as is, field moist
  samples
• Multiple constituents simultaneously

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NIRS Benefits

• COST !
• LECO OC 27/sample
• NIR OC 6/sample
• Minimal sample preparation
• Dried and ground (2mm mesh)
• Potential for as is or field moist
  determinations
• Timeliness
• Potential for immediate analysis

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NIRS Benefits, cont.

• Precision
• Precision of NIR equal or better than reference
• Does not destroy the sample
• The same sample can be analyzed many times over
• Positive implications for long term and/or
  incubative studies

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NIRS Limitations

• Site to Site Bias
• Potential for bias in predictions of samples from
  one site using calibrations derived from samples
  from another site.
• Affects absolute accuracy
• Does not affect precision
• This can be corrected by incorporating a small
  number of samples from the new site into the
  calibration.
• At present, this means that NIRS is not practical
  for small sample groups

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How can NIRS work for you?

• Objective sample selection1
• NIRS can be used to select sample sets from a
  large group of samples which
• Retain a maximum representation of overall sample
  population variability
• Samples selected better than random because
• Greater recovery of range
• Higher variance
• Better Kurtosis (more even distribution)

1Stenberg, B. et al. (1995) Use of near infrared
reflectance spectra of soils for objective
selection of samples. Soil Science. 159109-114.
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Objective Sample Selection, cont.

• Using NIR for selecting analytical samples
  reduces cost directly by lowering the number of
  samples that need to be analyzed to encompass
  soil variability.
• Stenberg, et al. estimated a 70 reduction in
  cost for their study using this method
• For their study, the overall n 144 samples,
  selected n 20 samples

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Calibration and Prediction

• Calibrations are developed on a selected set of
  samples (ie. using the NIR selection method)
• These calibrations can be used to predict the
  remaining samples.
• Requires large sample sets
• ncalibration 100 samples recommended

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Calibration and Prediction, cont.

• Extra cost of calibration and accompanying wet
  chemistry is offset by a large economy of scale
• Once a calibration is developed, it only requires
  updating with a much smaller number of QA/QC
  samples
• Calibrations will eventually exist for various
  soils, bringing initial costs down

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Monitoring and Long-term Soil Quality Assessment

• NIR spectra contain information for both carbon
  quantity, and carbon quality in soil
• High precision plus lower cost of NIR results
  make large scale assessments of soil carbon flux
  much more feasible, both
• Over time
• Under varying management practices.

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Monitoring and Long-term Soil Quality Assessment,
cont.

• Non destructive nature of NIR, coupled with
  as-is and/or on-site assessment potential
  mean that
• The same sample could be analyzed indefinitely
  over time.
• Could reduce potential subsampling error
• Could increase relevance of results

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Sensing Soil QualityLarge Area Surveillance of
Soil Condition and Trend
http//www.worldagroforestrycentre.org/sites/progr
am1/specweb/home.htm
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Services Available from PDKIntroductory Pricing

• Objective Sample Selection
• Samples submitted dried and ground (2mm)
• 6.00 per sample

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Services Available from PDK, cont.

• Compositional Analysis
• Calibration
• Samples (100 samples, 5 g/sample min) submitted
  dried and ground in borosilicate vials or bags
• Reference values submitted for constituents of
  interest, including QA/QC data from the
  analytical laboratory. (Reference chemistry can
  be arranged at a Lab of your choice, at
  commercial rates -extra)
• First calibration 6.00/sample plus 150
• Each additional calibration 250

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Compositional Analysis, cont.

• 2. Prediction of future samples
• Prediction of future unknown samples of the same
  type as in the calibrations, submitted dried and
  ground
• First constituent 6.00/sample
• Each additional constituent 1.00/sample

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Services available from PDK, cont.

• Consulting
• Custom Quote for
• Setup of personal NIR program
• Setup of field portable instrument
• Contract Research
• Instrument selection/evaluation

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Conclusions

• NIR is the only practical method for analyzing
  large numbers of samples for measurement of C
  stores
• NIR has potential to determine quality/persistence
  of organic C in soil

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Acknowledgments

• Foss NIRSystems Inc., USA
• Carl Zeiss, Germany
• Agriculture and Agri-Food Canada
• Manitoba Rural Adaptation Council (MRAC)
• Industrial Research Assistance Program (IRAP)