Title: Use of Near-infrared Spectroscopy for Monitoring and Analysis of Carbon Sequestration in Soil
1Use 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
2Vision
- 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
3Purpose
- Introduce Near-infrared Spectroscopy (NIRS)
- Describe
- Benefits to use of NIRS
- How NIR can be used for soil carbon assessment
- Services available from PDK
4NIR 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
5Near-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
6The 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
7Features
- does not destroy the sample
- is rapid, lt 2 min/test
- analyzes many constituents simultaneously
- analyzes compositional and functional properties
- field portable
8Lab and Field Instrument Zeiss Corona
9Organic 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
10Compositional 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
11Organic Carbon
- Miniota area
- Newdale Soil Assoc.
- Dried, ground samples (2mm)
- N 267
- 1100 - 2500 nm
- r2 0.78
- SEP 0.33
12Field-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
13Example 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
14NIRS 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
15NIRS 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
16NIRS 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
17How 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.
18Objective 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
19Calibration 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
20Calibration 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
21Monitoring 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.
22Monitoring 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
23Sensing Soil QualityLarge Area Surveillance of
Soil Condition and Trend
http//www.worldagroforestrycentre.org/sites/progr
am1/specweb/home.htm
24Services Available from PDKIntroductory Pricing
- Objective Sample Selection
- Samples submitted dried and ground (2mm)
- 6.00 per sample
25Services 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
26Compositional 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
27Services available from PDK, cont.
- Consulting
- Custom Quote for
- Setup of personal NIR program
- Setup of field portable instrument
- Contract Research
- Instrument selection/evaluation
28Conclusions
- 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
29Acknowledgments
- Foss NIRSystems Inc., USA
- Carl Zeiss, Germany
- Agriculture and Agri-Food Canada
- Manitoba Rural Adaptation Council (MRAC)
- Industrial Research Assistance Program (IRAP)