@Article{DottoDamGruCatPer:2017:TwPrTe,
author = "Dotto, Andre Carnieletto and Damolin, Ricardo Sim{\~a}o Diniz and
Grunwald, Sabine and Caten, Alexandre ten and Pereira Filho,
Waterloo",
affiliation = "{Universidade Federal de Santa Maria (UFSM)} and {Universidade
Federal de Santa Maria (UFSM)} and {University of Florid} and
{Universidade Federal de Santa Catarina (UFSC)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "Two preprocessing techniques to reduce model covariables in soil
property predictions by Vis-NIR spectroscopy",
journal = "Soil and Tillage Research",
year = "2017",
volume = "172",
pages = "59--68",
month = "Sept.",
keywords = "Visible-near infrared spectroscopy, Continuum removal, Detrend,
Band ratio.",
abstract = "Proximal sensing provides an alternative method to physical and
chemical laboratory soil analyses. The aim of this study is to
predict soil organic carbon (SOC), clay, sand, and silt content
using reduced spectral features as covariables selected by two
spectral preprocessing. A total of 299 soil samples were collected
in Santa Catarina state, Brazil. Two preprocessing techniques,
detrend transformation and continuum removal (CR), were applied to
isolate particular absorption features in the reflectance
spectrum. Two techniques were used to select the spectral features
in the spectrum: hand and mathematical selection. Partial least
squares regression (PLSR) and Support vector machines (SVM) were
applied to predict the soil properties. The reduction of predictor
covariables by hand selection technique contributed in developing
a high-level prediction model for SOC. PLSR and SVM presented no
statistical difference between the RMSE results, except for clay
content, where SVM presented superior performance. The
preprocessing techniques were statistically identical based on
RMSE results. Overall, the prediction of SOC, clay, sand and silt
presented suitable results using reduced spectral features as
covariables in modeling process.",
doi = "10.1016/j.still.2017.05.008",
url = "http://dx.doi.org/10.1016/j.still.2017.05.008",
issn = "0167-1987",
language = "en",
targetfile = "dotto_two.pdf",
urlaccessdate = "23 abr. 2024"
}