Visible and near infrared spectroscopy coupled to random forest to quantify some soil quality parameters.
Spectrochim Acta A Mol Biomol Spectrosc
; 191: 454-462, 2018 Feb 15.
Article
em En
| MEDLINE
| ID: mdl-29080499
This study evaluates the use of visible and near infrared spectroscopy (Vis-NIRS) combined with multivariate regression based on random forest to quantify some quality soil parameters. The parameters analyzed were soil cation exchange capacity (CEC), sum of exchange bases (SB), organic matter (OM), clay and sand present in the soils of several regions of Brazil. Current methods for evaluating these parameters are laborious, timely and require various wet analytical methods that are not adequate for use in precision agriculture, where faster and automatic responses are required. The random forest regression models were statistically better than PLS regression models for CEC, OM, clay and sand, demonstrating resistance to overfitting, attenuating the effect of outlier samples and indicating the most important variables for the model. The methodology demonstrates the potential of the Vis-NIR as an alternative for determination of CEC, SB, OM, sand and clay, making possible to develop a fast and automatic analytical procedure.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Clinical_trials
/
Prognostic_studies
Idioma:
En
Revista:
Spectrochim Acta A Mol Biomol Spectrosc
Assunto da revista:
BIOLOGIA MOLECULAR
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Reino Unido