Measurement of biochar properties, including
aromatic carbon, and monitoring the
concentration of charred material in soil using
NIR spectroscopy
BAMBANG H. KUSUMO
With the collaboration of P. BISHOP,
R. CALVELO PEREIRA, M. CAMPS ARBESTAIN,
C.B. HEDLEY, M.J. HEDLEY, A.F. MAHMUD,
and T. WANG
Introduction
• Conversion of biomass to biochar increases the residence time of C
in soil relative to that of the original feedstock
• It is proposed as a strategy able to reduce the release of CO2 to the
atmosphere
• Techniques and protocols are required to monitor and confirm
biochar stability in soil over time
Biochar
Massey University Farm
Uniform Biochar ApplicationBiomass Biochar
Introduction
• Application rates of biochar to soil will reflect cost of production,
transport and application (≤10 t ha-1 ~ 1% topsoil)
• NIRS techniques have been successfully used to measure C in soil.
But not yet widely used to measure biochar properties
In situ NIRS Measurement
Landcare Research Palmerston North, NZ
1. Can NIRS be used to measure biochar stability
parameters, e.g., aromatic C and molar H/Corg
ratio?
2. Can NIRS be used to measure biochar
concentration in soil at low (narrow range) to high
(wide range) rates of application?
3. Can NIRS – discriminant analysis be used to detect
biochar in soil?
Questions ?
1. Can NIRS be used to measure
biochar stability parameters, e.g.,
aromatic C and molar H/Corg ratio?
1st Study
Eucalyptus Pine Willow Poplar Manure BiosolidEucalyptus
LeavesChickenmanure
Poultrylitter
Papersludge
Materials and Methods
(ParLes; Viscarra Rossel, 2008)
Pyrolysis 250, 350, 450, 550 °C
The biochar samples were scanned
Spectral pre-processing (ParLes)
PCA analysis (ParLes)
Discriminant Analysis (MINITAB 16)
PLSR was used to build calibration models
25 biochar samples were analysed
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
400 600 800 1000 1200 1400 1600 1800 2000 2200 2400
Ref
lect
ance
Wavelength (nm)
MAe250
MAe350
BSe550
MAe450
BSe250
BSe350
BSe450
EuW400A
EuW550A
EuW400
EuW550
EuL400A
EuL550A
PS550A
PL400
PL550A
CM400
CM550A
PI-400
PO-400
WI-400
PO-550
WI-550
M-C-1
M-C-2550oC
Water Absorption
OH Absorption
Vis-NIR Spectra of 25 Biochars
Higher maximum pyrolysis temperatures reduced NIR reflectance
- Pyrolysis removes water and alcohols from feedstock
0.00060.00040.00020.0000-0.0002-0.0004
0.0002
0.0001
0.0000
-0.0001
-0.0002
-0.0003
PC1 (37.2%)
PC
2 (
8.9
%)
Biosolid+Wood
Leaves
Manure
Manure+Wood
Paper sludge
Wood
Feedstock
Manure or may contain decomposed plant tissue
May contain wood/plant tissue
Unknown
PCA Score Plot of Biochar Spectral data based on:
Feedstock
0.00060.00040.00020.0000-0.0002-0.0004
0.0002
0.0001
0.0000
-0.0001
-0.0002
-0.0003
PC1 (37.2%)
PC
2 (
8.9
%)
Unknown
250
350
400
450
550
Temperature
250-350oC
400-450oC
550oC
Unknown
Temperature of Pyrolysis
0.00060.00040.00020.0000-0.0002-0.0004
0.0002
0.0001
0.0000
-0.0001
-0.0002
-0.0003
PC1 (37.2%)
PC
2 (
8.9
%)
< 35%
> 65%
35-65%
Aromatic C
< 35%
> 65%
35-65%
Aromatic C
0.00060.00040.00020.0000-0.0002-0.0004
0.0002
0.0001
0.0000
-0.0001
-0.0002
-0.0003
PC1 (37.2%)
PC
2 (
8.9
%)
< 0.7
> 0.7
Ratio
H/Corg
H/Corg
Observation Predicted group From group Square distance Proba
bility
Archaeological charcoal 1
(M-C-1)350oC
250oC 394.291 0.000
350oC 378.434 1.000
400oC 439.338 0.000
450oC 536.841 0.000
550oC 569.557 0.000
Archaeological charcoal 2
(M-C-2)250oC
250oC 1018.365 1.000
350oC 1279.314 0.000
400oC 1299.436 0.000
450oC 1469.148 0.000
550oC 1499.017 0.000
Put into groupTrue Group All Groups
250oC 350oC 400oC 450oC 550oC
250oC 3 0 0 0 0
350oC 0 3 0 0 0
400oC 0 0 6 0 0
450oC 0 0 2 2 1
550oC 0 0 0 0 8
Total number 3 3 8 2 9 25
Correct number 3 3 6 2 8 22
Proportion (%) 100 100 75.0 100 88.9 88.0
Linear Discriminant Analysis of Spectral Biochar Data based on
Temperature
NIRS can predict biochar Aromatic C(using band region: 780-2500 nm)
y = 0.8544x + 6.3034R² = 0.9261
RMSE = 5.336RPD = 3.62
0
10
20
30
40
50
60
70
80
90
0 10 20 30 40 50 60 70 80 90
NIR
S-P
red
icte
d A
rom
ati
c C
(%
)
13C NMR-Measured Aromatic C (%)
Vis-NIR Spectroscopy
13C NMR Spectroscopy
NIRS (780-2500 nm bands)
can predict Fixed C, H/Corg
Atomic Ratio, and
Fraction of Aromaticity (fa)
y = 0.8033x + 8.2847R² = 0.9155
RMSE = 6.009RPD = 3.26
0
10
20
30
40
50
60
70
80
90
0 10 20 30 40 50 60 70 80 90
NIR
S-P
red
icte
d F
ixe
d C
(%
)
Measured Fixed C (%)
y = 0.8694x + 0.0995R² = 0.921
RMSE = 0.041RPD = 3.56
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1
NIR
S-P
red
icte
d f
a
Measured fa
y = 0.8843x + 0.0913R² = 0.9332
RMSE = 0.072RPD = 3.87
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
NIR
S-P
red
icte
d H
/Co
rgA
tom
ic R
ati
o
Measured H/Corg Atomic Ratio
H/Corg
Fixed C
Fraction of Aromaticity
NIRS (780-2500 nm bands) can predict
Corg, H O & Ash content, Volatile Matter
content, O/Corg atomic ratio, and pH
r pH Corg (%) N (%) H (%) Ash (%) O (%) VM (%) FC (%) H /Corg O/Corg fa Aromatic C (%)
pH 1 0.128 0.237 -0.619* 0.144 -0.628* -0.579 0.287 -0.699* -0.457 0.683* 0.364
Corg (%) 0.128 1 -0.270 0.437 -0.916* -0.051 0.202 0.942* -0.579 -0.659* 0.123 0.916*
N (%) 0.237 -0.270 1 -0.078 0.317 -0.298 -0.103 -0.223 0.157 -0.167 -0.075 -0.265
H (%) -0.619* 0.437 -0.078 1 -0.618* 0.427 0.746* 0.208 0.439 -0.086 -0.760* 0.089
Ash (%) 0.144 -0.916* 0.317 -0.618* 1 -0.349 -0.451 -0.826* 0.348 0.347 0.115 -0.755*
O (%)1 -0.628* -0.051 -0.298 0.427 -0.349 1 0.594 -0.121 0.410 0.711* -0.479 -0.218
VM (%)2 -0.579 0.202 -0.103 0.746* -0.451 0.594 1 -0.083 0.424 0.215 -0.781* -0.140
FC (%)3 0.287 0.942* -0.223 0.208 -0.826* -0.121 -0.083 1 -0.715* -0.659* 0.373 0.971*
H /Corg -0.699* -0.579 0.157 0.439 0.348 0.410 0.424 -0.715* 1 0.593 -0.804* -0.783*
O/Corg -0.457 -0.659* -0.167 -0.086 0.347 0.711* 0.215 -0.659* 0.593 1 -0.352 -0.694*
fa4 0.683* 0.123 -0.075 -0.760* 0.115 -0.479 -0.781* 0.373 -0.804* -0.352 1 0.489
Aromatic C (%) 0.364 0.916* -0.265 0.089 -0.755* -0.218 -0.140 0.971* -0.783* -0.694* 0.489 1
Correlation matrix among the reference data
of biochar properties
VM = volatile matter, FC = fixed carbon, fa = fraction of aromaticity
Independent NIRS prediction between
Aromatic C and fraction of aromaticity (fa)
Aromatic C & fa; r = 0.489 Aromatic C prediction; R2 = 0.926 fa prediction; R2 = 0.921
Fraction of aromaticity
Aromatic C
2nd Study
2. Can NIRS be used to measure
biochar concentration in soil at low
(narrow range) to high (wide range)
rates of application?
Pine-350
Biosolids-
550
pH 7.2 8.2
C % 75.9 35.6
N % 0.3 1.4
Ash % 2.6 51.2
Vol Matter % 30.2 13.4
Fixed C % 63.2 30.6
Materials and Methods
Wide range;
0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 75, 100% Biochar
Narrow range;0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5% Biochar
Soils/substrate:
- Alfisol (silt-loam
Tokomaru)
- Entisol (sandy soil
Motuiti)
- Quartz
Fraction of Aromaticity(BS-550) = 87%(PI-350) = 73%
Total of Aromatic C(BS-550) = 309.7 g kg-1
(PI-350) = 554.1 g kg-1
Biochar
SpectraUV-Vis-NIR
NMR
** *
*
Aromatic C
Predicting Wide Range (0-100%)
Biochar Concentration in Soil using NIRS
Better prediction when soil + biochar types
were separated
Using NIR (780-2500 nm)
Using NIR (780-2500 nm)
Sandy Soil
Using NIR (780-2500 nm)
Silt Loam Soil
Using Vis-NIR Bands
780-1200 & 2100-2500 nm
Can biochar, with low concentration (0-2.5%) in soil, be predicted well using NIRS (780-1200 & 2100-2500 nm) ?
780-1200 & 2100-2500 nm
Finely Ground
the Sandy Soil
780-1200 & 2100-2500 nm
Finely Ground
the Sandy Soil
780-1200 & 2100-2500 nm
780-1200 & 2100-2500 nm
Sandy Soil
780-1200 & 2100-2500 nm
Silt Loam Soil
*) UV-Vis-NIR bands = 350-2500; **) Vis-NIR bands = 400-2500 nm; ***) NIR bands = 780-2500 nm
# Finely ground Motuiti soil = passed through 0.180 mm sieve
Sample Bands UsedNumber of
Samples
Number of
Factors
For PLSR model
Leave-one-out cross-validation
R2 RMSECV RPD
Motuiti (fine) # + BS-550 UV-Vis-NIR*) 26 5 0.455 0.585 1.31
Motuiti (fine)# + BS-550 Vis-NIR**) 26 5 0.428 0.624 1.23
Motuiti (fine)# + BS-550 NIR***) 26 5 0.767 0.378 2.02
Motuiti (fine)# + BS-550 780-1200 &
2100-2500 nm
26 5 0.964 0.143 5.37
Effect of band region selection and grinding on prediction accuracyfor one soil and biochar type
Sample Bands Used
Number
of
Samples
Number of
Factors
For PLSR
model
Leave-one-out cross-validation
R2 RMSECV RPD
Motuiti (coarse) + BS-550 UV-Vis-NIR*) 26 5 0.414 0.612 1.25
Motuiti (coarse) + BS-550 Vis-NIR**) 26 5 0.687 0.426 1.79
Motuiti (coarse) + BS-550 NIR***) 26 5 0.463 0.559 1.37
Motuiti (coarse) + BS-550 780-1200 &
2100-2500 nm
26 5 0.961 0.149 5.14
Sample Bands UsedNumber of
Samples
Number of
Factors
for PLSR
model
Leave-one-out cross-validation
R2 RMSECV RPD
Tokomaru (fine)+PI-350 and
Motuiti (fine) # +BS-550 UV-Vis-NIR*) 52 4 0.213 0.677 1.12
Tokomaru (fine) +PI-350
and Motuiti (fine) # +BS-550 Vis-NIR**) 52 4 0.232 0.686 1.10
Tokomaru (fine)+PI-350 and
Motuiti (fine) # +BS-550 NIR***) 52 4 0.858 0.228 2.63
Tokomaru (fine) +PI-350
and Motuiti (fine) # +BS-550780-1200 &
2100-2500 nm52 4 0.954 0.168 4.55
*) UV-Vis-NIR bands = 350-2500; **) Vis-NIR bands = 400-2500 nm; ***) NIR bands = 780-2500 nm
# Finely ground Motuiti soil = passed through 0.180 mm sieve
Effect of band region selection and grinding on prediction
accuracy of two soils and biochars
0.030.020.010.00-0.01
0.002
0.001
0.000
-0.001
-0.002
PC1 (65.3% variance)
PC
2 (
5.5
% v
ari
an
ce
)
BC
NIL
Group
BC (Biochar)NIL
Marked influence of biochar in soil spectral reflectance
PCA Score Plot of 1690 Pre-Processed Spectral Data
(780-1200 & 2100-2500 nm) with and without Biochar
Put into groupTrue Group All
groupsBiochar NIL
Biochar 26 1
NIL 1 1662
Total number 27 1663 1690
Correct number 26 1662 1688
Correct
proportion (%)
96.3 99.9 99.9
•R to Log(1/R)•Wavelet detrending• Smoothing
(Savitzky-Golay•1st Derivative•Mean Centre
Raw Spectral Data
Pre-Processed
PCA
Scores of Principal
Components
Discriminant Analysis
Response Variables (e.g. NIL, biochar)
Result of Classification
Summary of Classification
Summary of Classification; Separate Calibration and validation set
Put into group
Calibration set (1000 spectra) Validation set (690 spectra)
True Group True Group
Biochar NIL All Biochar NIL All
Biochar 19 0 5 1
NIL 2 979 1 683
Total number 21 979 1000 6 684 690
Correct number 19 979 998 5 683 688
Correct proportion (%) 90.5 100 99.8 83.3 99.9 99.7
Measured vs. Predicted Total C from the Soil Cores
(using selected band region: 780-1200 & 2100-2500 nm)
NIRS prediction on cores without biochar
NIRS prediction on cores with biochar
Effect of added biochar on soil C (elemental analysis data)
Biochar
Effect of added biochar on soil C (NIRS-
predicted data)
CONCLUSIONS
• NIR reflectance spectroscopy has a potential use for
predicting biochar C aromaticity and other biochar properties
• Successful prediction of molar H/Corg indicates that NIRS can
be used as a quick assessment for C stability
• NIRS was able to predict biochar at low (narrow range, 0–2.5%
BC) and high (wide range, 0–100% BC) application rates
• Grinding the coarse soil and selecting the important bands
(780-1200 & 2100-2500 nm) improved the prediction accuracy
• NIRS – Discriminant Analysis can be used to detect biochar in
field soil