Predicting soil clay content from NIR, gamma-ray and XRF curves.
Predicting soil clay content from NIR, gamma-ray and XRF curves.
Author(s): VASQUES, G. de M.; RODRIGUES, H. M.; TAVARES, S. R. de L.; COELHO, M. R.
Summary: In this study, data from NIR, gamma ray and XRF curves, and three multivariate methods (partial least squares regression - PLS, random forest - RF, and support vector machine - SVM) were used to predict soil clay content at 0-10-cm depth. Training and validation data included 103 and 25 samples, respectively. Gamma ray and XRF data were taken in situ at the soil surface, using portable sensors, whereas NIR reflectance curves (800-2500 nm) were measured from airdried fine earth samples in the laboratory.
Publication year: 2019
Types of publication: Abstract in annals or event proceedings
Unit: Embrapa Soils
Keywords: Sensoriamento Remoto
Observation
Some of Embrapa's publications are published as ePub files. To read them, use or download one of the following free software options to your computer or mobile device. Android: Google Play Books; IOS: iBooks; Windows and Linux: Calibre.
Access other publications
Access the Agricultural Research Database (BDPA) to consult Embrapa's full library collection and records.
Visit Embrapa Bookstore to purchase books and other publications sold by Embrapa.