Portable x-ray fluorescence (pXRF) spectrometry applied to the prediction of chemical attributes in inceptisols under different land use

Anita Fernanda dos Santos Teixeira, David C. Weindorf, Sérgio Henrique Godinho Silva, Luiz Roberto Guimarães Guilherme, Nilton Curi

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

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 (regressions) and validation of soil fertility attributes and necessity of lime (NL) application, with or without distinction between managed and unmanaged areas. Management practices on coffee crops increased the levels of Sr, CaO, P 2 O 5 , Cu, and Zn. CaO content was efficient for prediction of exchangeable Ca 2+ contents (R 2 = 0.91), pH (R 2 = 0.88), base saturation (R 2 = 0.89) in managed areas. General models presented adequate results to predict exchangeable Ca 2+ (R 2 = 0.92), pH (R 2 = 0.85), and base saturation (R 2 = 0.90). Models for unmanaged areas were less effective. PXRF detected modifications in elemental contents caused by management practices and provided reliable predictions of soil fertility attributes.

Original languageEnglish
Pages (from-to)501-512
Number of pages12
JournalCiencia e Agrotecnologia
Volume42
Issue number5
DOIs
StatePublished - Sep 1 2018

Scopus Subject Areas

  • Food Science
  • Animal Science and Zoology
  • Agronomy and Crop Science
  • General Veterinary
  • Soil Science

Keywords

  • Brazilian Cerrado
  • Proximal sensor
  • Soil fertility
  • Soil management
  • Soil property modeling

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