Record Details

Comparison of data mining approaches for estimating soil nutrient contents using diffuse reflectance spectroscopy

OAR@ICRISAT

View Archive Info
 
 
Field Value
 
Relation http://oar.icrisat.org/9480/
http://www.currentscience.ac.in/Volumes/110/06/1031.pdf
 
Title Comparison of data mining approaches for estimating soil nutrient contents using diffuse reflectance spectroscopy
 
Creator Sarathjith, M C
Das, B S
Wani, S P
Sahrawat, K L
Gupta, A
 
Subject Soil Science
 
Description Diffuse reflectance spectroscopy (DRS) operating in
wavelength range of 350–2500 nm is emerging as a
rapid and non-invasive approach for estimating soil
nutrient content. The success of the DRS approach relies
on the ability of the data mining algorithms to extract
appropriate spectral features while accounting
for non-linearity and complexity of the reflectance
spectra. There is no comparative assessment of spectral
algorithms for estimating nutrient content of
Indian soils. We compare the performance of partialleast-squares
regression (PLSR), support vector regression
(SVR), discrete wavelet transformation
(DWT) and their combinations (DWT–PLSR and
DWT–SVR) to estimate soil nutrient content. The
DRS models were generated for extractable phosphorus
(P), potassium (K), sulphur (S), boron (B), zinc
(Zn), iron (Fe) and aluminium (Al) content in Vertisols
and Alfisols and were compared using residual
prediction deviation (RPD) of validation dataset. The
best DRS models yielded accurate predictions for P
(RPD = 2.27), Fe (RPD = 2.91) in Vertisols and Fe
(RPD = 2.43) in Alfisols, while B (RPD = 1.63), Zn
(RPD = 1.49) in Vertisols and K (RPD = 1.89), Zn
(RPD = 1.41) in Alfisols were predicted with moderate
accuracy. The DWT–SVR outperformed all other approaches
in case of P, K and Fe in Vertisols and P, K
and Zn in Alfisols; whereas the PLSR approach was
better for B, Zn and Al in Vertisols and B, Fe and Al
in Alfisols. The DWT–SVR approach yielded parsimonious
DRS models with similar or better prediction
accuracy than PLSR approach. Hence, the DWT–SVR
may be considered as a suitable data mining approach
for estimating soil nutrients in Alfisols and Vertisols
of India.
 
Publisher Current Science Association
 
Date 2016-03-25
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Rights —
 
Identifier http://oar.icrisat.org/9480/1/Sarathjith%20et%20al%202016_CS.pdf
Sarathjith, M C and Das, B S and Wani, S P and Sahrawat, K L and Gupta, A (2016) Comparison of data mining approaches for estimating soil nutrient contents using diffuse reflectance spectroscopy. Current Science, 110 (06). pp. 1031-1037. ISSN 0011-3891