|
|
|
|
|
| Teixeira,Anita Fernanda dos Santos; Weindorf,David C.; Silva,Sérgio Henrique Godinho; Guilherme,Luiz Roberto Guimarães; Curi,Nilton. |
| ABSTRACT Portable X-ray fluorescence (pXRF) spectrometry has been increasingly adopted for varying studies worldwide. This work aimed at characterizing effects of soil management on the content of chemical elements detected by pXRF in managed and unmanaged areas of Inceptisols, and evaluating the potential of using pXRF data to generate prediction models for soil fertility attributes, evaluating the effect of land uses on such models. Samples were collected in A, B, and C horizons of soils under native forest, native Cerrado, coffee crops with 1 and 5 years of implantation and eucalyptus. Soil fertility attributes were determined through laboratory analyses, whereas, elemental contents were obtained through pXRF analysis. PXRF data were used for modeling... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil property modeling; Soil management; Soil fertility; Brazilian Cerrado; Proximal sensor.. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000500501 |
| |
|
|
| Silva,Sérgio Henrique Godinho; Teixeira,Anita Fernanda dos Santos; Menezes,Michele Duarte de; Guilherme,Luiz Roberto Guimarães; Moreira,Fatima Maria de Souza; Curi,Nilton. |
| ABSTRACT Determination of soil properties helps in the correct management of soil fertility. The portable X-ray fluorescence spectrometer (pXRF) has been recently adopted to determine total chemical element contents in soils, allowing soil property inferences. However, these studies are still scarce in Brazil and other countries. The objectives of this work were to predict soil properties using pXRF data, comparing stepwise multiple linear regression (SMLR) and random forest (RF) methods, as well as mapping and validating soil properties. 120 soil samples were collected at three depths and submitted to laboratory analyses. pXRF was used in the samples and total element contents were determined. From pXRF data, SMLR and RF were used to predict soil... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil analyses; Spatial prediction; Proximal sensor.. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542017000600648 |
| |
|
|
|
