Use of Near-infrared Use of Near-infrared Spectroscopy for Spectroscopy for
Monitoring and Analysis of Monitoring and Analysis of Carbon Sequestration in Carbon Sequestration in
Soil Soil byby
P.D. Martin, and D.F. MalleyP.D. Martin, and D.F. MalleyPDK Projects, Inc.PDK Projects, Inc.
Winnipeg, Manitoba, CanadaWinnipeg, Manitoba, Canada
VisionVision
• 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
PurposePurpose
• Introduce Near-infrared Spectroscopy (NIRS)
• Describe:– Benefits to use of NIRS – How NIR can be used for soil carbon
assessment– Services available from PDK
NIR FactsNIR 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
Near-infrared Near-infrared SpectroscopySpectroscopy
• 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
The Work of Doing NIR The Work of Doing NIR AnalysisAnalysis
• Compositional information on samples (n ~>100) is correlated with the spectral information to develop statistical calibration models
• The calibrations “train” the instrument to analyze future unknown samples
FeaturesFeatures
• does not destroy the sample• is rapid, < 2 min/test• analyzes many constituents
simultaneously• analyzes compositional and
functional properties • field portable
Lab and Field Instrument: Lab and Field Instrument: Zeiss CoronaZeiss Corona
Organic Matter Organic Matter Compositional ParametersCompositional 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
Compositional Parameters Compositional Parameters cont’dcont’d
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 0.90.9 v.good v.good
Organic CarbonOrganic Carbon
• Miniota area• Newdale Soil
Assoc.• Dried, ground
samples (2mm)• N = 267• 1100 - 2500
nm• r2 = 0.78• SEP = 0.33 %
0
1
2
3
4
5
0 1 2 3 4 5
LECO-determined Org C (%)
NIR
-pre
dic
ted
Org
C (
%)
““Field-moist” applicationsField-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 36:1571-1582
Example of On-site Soil Example of On-site Soil Testing MethodTesting Method
• Soil cores - grid or stratified sampling
• Cores sliced on-site• Presentation of static, “as is”, field
moist samples• Multiple constituents
simultaneously
NIRS BenefitsNIRS 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
NIRS Benefits, cont.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
NIRS LimitationsNIRS 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
How can NIRS work for How can NIRS work for you?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. 159:109-114.
Objective Sample Selection, Objective Sample Selection, cont.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
Calibration and PredictionCalibration 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
Calibration and Prediction, Calibration and Prediction, cont.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
Monitoring and Long-term Monitoring and Long-term Soil Quality AssessmentSoil 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.
Monitoring and Long-term Monitoring and Long-term Soil Quality Assessment, Soil Quality Assessment,
cont.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
Sensing Soil QualitySensing Soil QualityLarge Area Surveillance of Soil Large Area Surveillance of Soil
Condition and TrendCondition and Trend
http://www.worldagroforestrycentre.org/sites/program1/specweb/home.htm
Services Available from Services Available from PDKPDK
Introductory PricingIntroductory Pricing• Objective Sample Selection
Samples submitted dried and ground (2mm) – $6.00 per sample
Services Available from PDK, Services Available from PDK, cont.cont.
• Compositional Analysis1. 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
Compositional Analysis, cont.Compositional Analysis, cont.
2. Prediction of future samplesPrediction 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
Services available from PDK, Services available from PDK, cont.cont.
• Consulting– Custom Quote for:
•Setup of personal NIR program•Setup of field portable instrument•Contract Research•Instrument selection/evaluation
ConclusionsConclusions
• 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
AcknowledgmentsAcknowledgments
• Foss NIRSystems Inc., USA• Carl Zeiss, Germany• Agriculture and Agri-Food Canada • Manitoba Rural Adaptation Council
(MRAC)• Industrial Research Assistance
Program (IRAP)
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