Spectral data of tropical soils using dry-chemistry techniques (VNIR, XRF, and LIBS): A dataset for soil fertility prediction

Autor(es)

Tavares, Tiago Rodrigues ; Molin, Jose Paulo ; Nunes, Lidiane Cristina ; Alves, Elton Eduardo Novais ; Krug, Francisco Jose ; de Carvalho, Hudson Wallace Pereira

• Tipo de documento: Artigo Científico
• Fonte: DATA IN BRIEF; v. 41, p. 7-pg., 2022-04-01.

Resumo

Proximal soil sensing technologies, such as visible and near infrared diffuse reflectance spectroscopy (VNIR), X-ray fluorescence spectroscopy (XRF), and laser-induced breakdown spectroscopy (LIBS), are dry-chemistry techniques that enable rapid and environmentally friendly soil fertility analyses. The application of XRF and LIBS sensors in an individual or combined manner for soil fertility prediction is quite recent, especially in tropical soils. The shared dataset presents spectral data of VNIR, XRF, and LIBS sensors, even as the characterization of key soil fertility attributes (clay, organic matter, cation exchange capacity, pH, base saturation, and exchangeable P, K, Ca, and Mg) of 102 soil samples. The samples were obtained from two Brazilian agricultural areas and have a wide variation of chemical and textural attributes. This is a pioneer dataset of tropical soils, with potential to be reused for comparative studies with other datasets, e.g., comparing the performance of sensors, instrumental conditions, and/or predictive models on different soil types, soil origin, concentration range, and agricultural practices. Moreover, it can also be applied to compose soil spectral libraries that use spectral data collected under similar instrumental conditions. (C) 2022 The Author(s). Published by Elsevier Inc. (AU)

• Processo FAPESP: 20/16670-9 - Modelagem de dados espectrais para análise da fertilidade de solos tropicais: associação das técnicas vis-NIR e XRF para a modernização dos métodos tradicionais de análise
• Beneficiário: Tiago Rodrigues Tavares
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado