Dissertação
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR
Fecha
2022-09-30Autor
Kunz, Karine Mariele
Institución
Resumen
The chemical analysis of soil components is a tool that allows good practices for correctives
and fertilizers recommendation and managing soil fertility. Traditional methods of analysis
usually consume a high number of reagents and require a lot of time for sample preparation and
extractions. An alternative has been spectroscopy in the visible and near infrared (Vis-NIR)
region. However, this tool needs validation and calibration of models for reliable estimates for
different soil parameters. The objective of this work was to evaluate the reliability of Vis-NIR
spectroscopy to estimate the potential acidity of tropical soils compared with values obtained
by traditional methods used in routine soil analysis laboratories. We used 240 soil samples from
agricultural areas and analyzed in the UFSM routine laboratory, 60 samples of each clay class
(class 1: clay content ≤ 20; class 2: 21-40; class 3: 41-60; class 4: >60), which are subdivided
by organic matter (OM) content into 20 samples of low content class (low ≤ 2.5), 20 samples
of the medium class (medium 2.6 - 5.0), 20 samples of the high OM content class (high >5.0).
For the validation of the models, 51 unknown samples were used, which were not part of the
initial sample bank. The determination of the potential acidity of the samples was made by
estimating with the SMP index and by the calcium acetate method. Five spectra pretreatments
were used: smoothed (SMO), Savitzky-Golay Derivate (SGD), Multiplicative Scatter
Correction (MSC), Continuum Removal (CRR) and Standard normalization variate (SNV).
Prediction models for the potential acidity content were developed from raw and pre-processed
spectral data. The models tested were Cubist, Multiple Linear Regression (MLR) and Partial
Least Squares Regression (PLSR). The evaluation of the precision of the calibration curves was
performed using the coefficient of determination (R²
) and the deviations from the root mean
square error (RMSE). Curve validation was performed with the model that presented the best
calibration performance. Soil spectra showed features related to soil constituents, mainly in
SNV, MSC, SGD and CRR techniques. The pre-processing that obtained the best performance
in both the calibration and validation stages was the CRR, regardless of the model used. There
was a wide variation in the accuracy of the same multivariate method when different preprocesses were applied. The Cubist model presented the best performance, both for validation
of samples analyzed by calcium acetate (R²=0.86; r=0.93) and for the SMP index (R²=0.91;
r=0.95). Both the calcium acetate method and the SMP index method showed good fit with the
model (R²=0.55 and R²=0.53, respectively). Vis-NIR spectroscopy has the potential to estimate
the potential acidity, however, other studies and tests are needed to better elucidate the
technique until the use of curves in soil analysis laboratories.