This presentation was presented during the 3 Parallel session on Theme 1, Monitoring, mapping, measuring, reporting and verification (MRV) of SOC, of the Global Symposium on Soil Organic Carbon that took place in Rome 21-23 March 2017. The presentation was made by Ms. Caroline Ouko, from CETRAD - Kenya, in FAO Hq, Rome

1. USING INFRARED SPECTROSCOPY
FOR DETECTION OF CHANGE IN SOIL
PROPERTIES IN SELECTED
LANDUSES IN MT. MARSABIT
ECOSYSTEM, NORTHERN KENYA
Caroline Achieng Ouko
Research Scientist
CETRAD | P.O Box 144-10400 | Nanyuki | Kenya

2.  Independence: 12th
December 1963
 Ethnic groups: 43
 Area: 592000 km2
 Location: 5o north & 5o south
& between longitudes 34o &
42o east
 Altitude: variable from 0 to
5000m above sea level
 Climate (equator, topography,
Indian ocean, ITCZ, habitat &
ecology)
 Economy: heavily rely on
natural resources: forests
Introduction

3. Forests provide essential ecosystems services
but have been depleted. The change from
natural forest cover to agricultural and pastoral
activities is rampant
Introduction Contd..

4. Study Area

5. Mt. Marsabit Forest depletion.
Study Introduction

6. Study Introduction Contd.
 The conventional assessment methods to
determine soil degradation are expensive, time
consuming and very specific.
 The assessment of diverse effects of land use and
land use change on soil productivity requires
methods that can provide rapid and integrated
assessments
 Developments in laboratory and field based
reflectance spectrometry present a unique
capability for rapid, cheap, integrated assessments
and routine monitoring of soil productivity status

7. Objective
To evaluate the use of near infrared
spectroscopy for non-destructive
characterization
And prediction of management sensitive soil
properties under different land use systems.

8. Methodology
 Three transects cutting across the chosen
land use patterns namely forest, cropped
and pastureland (GPS).
 Soil sampling for physical and chemical
analysis.
 Above ground carbon stocks estimated in the
different LUS according to Woomer et al
1998.
 222 augured soil samples from 0 – 20 and
20 – 50 cm.
 Calibration set was a third of the total
(74 samples)

9. Study Area

10. Methodology cont.
 The air dried soil passed through a 2-mm
sieve was packed in 12 mm deep and 55
mm diameter Duran Petri dishes.
 The samples were scanned through the
bottom of the Petri dishes using a high
intensity source probe
 The probe illuminated the sample giving a
correlated color temperature of 3000 K.
 Reflectance spectra were recorded at two
positions, successively rotating the sample
dish through 90o between readings to
sample within dish variation.

11. Methodology cont.
 X-ray fluorescence (XRF) is used to detect and measure the
concentration of elements in substances. Fluorescence -
phenomena of absorbing incoming radiation and reradiating it
as lower-energy radiation.

12. Methodology cont.
 Reflectance readings of each wavelength band
were expressed relative to the average of the
white reference readings.
 Spectroscopic transformation was applied to
convert spectral reflectance to absorbance
 Principle component analysis was implemented
in Unscrambler version 7.5
 Individual soil variables were calibrated against
214 (0.36-2.49 µm) reflectance bands using
Partial Least Squares (PLS) regression

13. Results and Discussion
 Mean relative reflectance varied among
the three LUS
 The mean soil spectral reflectance from
the three LUS exhibited similar pattern
indicating similar mineralogy.

14. Results and Discussion
Relative reflectance averaged across the
entire spectrum (albedo) of all the soils ranged
from 0.025 to 0.28.
0
0.0
5
0.
1
0.1
5
0.
2
0.2
5
0.
3
0 0.
5
1 1.
5
2 2.
5
3
Wavelength (µm)
Relativereflectance
F
C
R
Near Infrared Reflectance Spectroscopy of forest (F), cropland
(C) and pastureland (R) soil samples.

15. Regression of soil properties measured by standard laboratory
procedures and predicted by NIRS – PLS techniques.
pH
y = 0.9504x + 0.3598
R2 = 0.9465
6.5
7
7.5
8
8.5
6.5 7 7.5 8
Measured values
Predictedvalues
1
Total Carbon
y = 0.97x + 0.0847
R2
= 0.973
0
2
4
6
8
10
12
0 2 4 6 8 10 12
Measured values (%)
PredictedValues
1
Magnesium
y = 0.954x + 0.3733
R2
= 0.9435
5
7
9
11
13
15
5 7 9 11 13
Measured values (ppm/100g)
Predictedvalues
(ppm/100g)
1
Potassium
y = 0.3329x + 7.6048
R2
= 0.3516
0
5
10
15
20
0 5 10 15 20 25
Measured values (meq/100g)
Predictedvalues
(meq/100g)
1
CEC
y = 0.7072x + 8.9154
R2
= 0.7629
20
25
30
35
40
45
50
20 30 40 50
Measured values (Cmol/g)
Predictedvalues
(Cmol/g
)
1
Total Nitrogen
y = 0.9884x + 0.0077
R2
= 0.9537
0
1
2
0 1 2
Measured values
Predictedvalues
(%)
1
Calcium
y = 0.8309x + 1.5033
R2
= 0.7626
5
10
15
20
5 10 15 20
Measured values
Predictedvalues
(ppm)
Measured N
Linear (PredN)

16. NIRS Prediction of Soil Properties using
Partial Least Square Regression
 Carbon, nitrogen, pH, exchangeable magnesium & calcium, and
CEC were reliably predicted (r2 > 0.76) by NIRS-PLS.
 Cross validation models with high regression (r2) values such as
those obtained with N, CEC and exchangeable Ca also yielded large
validation r2 values (r2 > 0.76).
 These properties are highly correlated with carbon (r2 = 0.97).
 pH (r2 = 0.95) and exchangeable Mg (r2 = 0.94) were more
accurately predicted by NIRS-PLS than would be expected based on
their correlations with carbon.
 Correlation coefficients of extractable K was very low (r2 = 0.35)
probably due to its luxury consumption and leaching as weathering
advances.

17. Estimated total A&BG carbon stocks (ton/ha)
under different land use systems
Carbon
stocks
Forest Cultivated Rangeland
Above C 4.3x109 1.5x109 1.7x109
Below 1.4x109 1.2x109 0.9x109
Total 5.7x109 2.7x109 2.6x109
Mean SE 24.5 20.3 19.2

18. Conclusion and
Recommendations
 Soil carbon content is useful to assess rate and
extent of land degradation.
 This study has shown that conversion of forests
to agricultural use affects the soil properties.
 The carbon stocks were especially affected in
that the carbon sinks were reduced in the
converted land use systems and a decline in
carbon stocks of 45.6% and 47.4% in the
pasture and cropped land was observed.

19. Conclusion and
Recommendations
 NIRS was sensitive to changes in soil properties caused
by forest conversion and gave good estimates of
management induced changes in soil properties
including total C and total N, CEC, exchangeable Ca
and Mg, and particle size distribution.
 Significantly, these are primary soil constituents for
which a theoretical basis for reliable NIRS prediction
exists.
 NIRS spectroscopy offers great potential for estimating
and monitoring variations in these constituents under
different land use land management scenarios.

20. Conclusion and
Recommendations
 Future direction for research is to develop a spectral library of
referent or benchmark sites at a landscape scale. The spectral
separability of managed systems relative to an undisturbed
benchmark offers a new research vision
 Future studies should explore approaches that combine
Discriminant analysis and strategic spectral libraries of pre-
agriculture (benchmark) soil conditions with information on
physical, chemical and biological properties.
 The reliable methods will accelerate the development of risk-
based approaches that explicitly account for site history and
land use management.

21. Future Outlook
Looks rocky and steep
Look for opportunities
Divine intervention

22. Acknowledgment
Research funds were provided by AGREF
Thank you for your attention

23. References
 Analytical Spectral Devices Inc. (1997). FieldSpecTM User’s guide.
Analytical Spectral Devices Inc., Boulder CO.
 Food and agriculture organization (FAO), Forest Resources Assessment
(1990). Global Synthesis, FAO Forestry Paper 124, FAO, Rome, Italy, 1995.
 McCarty, G.W., Reeves, J.B., Follett, R.F., and. Kimble, J.M., (2002). Mid-
infrared and near-infrared diffuse reflectance spectroscopy for soil carbon
measurement, Soil Sci. Soc. Am. J. 66 (2), pp. 640–646).
 Naes, T., Isacksson, T., Fearn, T. and Davies, T. (2002). A user-friendly
guide to Multivariate Calibration and Classification. NIR Publications
Chichester, UK.
 Shepherd, K.D. and Walsh, M.G., (2007). Review: Infrared spectroscopy-
Enabling an evidence-based diagnostic surveillance approach to agricultural
and environmental management in developing countries. Journal of Infrared
Spectroscopy 15, 1-19.