Application of Chemometric Methods in X‐Ray Diffraction Data on Arabica Coffee Management Soils in Brazil

Soil mineralogy, analysed by x-ray diffraction (XRD), is crucial to understanding its variability and influence on physical and chemical properties. However, soil analysis by XRD faces challenges, especially with large sample volumes and subjective interpretation. This study proposes a simplified methodology for sample preparation and soil analysis by XRD, which is associated with the principal component analysis (PCA). Two PCA models were built: one using semiquantitative percentages of minerals and another based on diffraction intensities. After analysing 90 samples from nine farms producing <i>Coffea arabica</i>, the results suggest greater efficiency in identifying clusters related to mineralogical composition, offering a fast and objective approach to soil characterization.

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Publication Details

Journal
Analytical Science Advances
Published
2025-10-17
DOI
https://doi.org/10.1002/ansa.70042
Citations
1
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
0.75
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article

Application of Chemometric Methods in X‐Ray Diffraction Data on Arabica Coffee Management Soils in Brazil

Paulo R. Filgueiras, Marcos Valério Vieira Lyrio, Marcos A. Ribeiro, Lucas Louzada Pereira et al.
1 citations
Analytical Science Advances
Spectroscopy and Chemometric Analyses
0.75
article

Application of Chemometric Methods in X‐Ray Diffraction Data on Arabica Coffee Management Soils in Brazil

Paulo R. Filgueiras, Marcos Valério Vieira Lyrio, Marcos A. Ribeiro, Lucas Louzada Pereira, Roberta Quintino Frinhani, Renata Silva
article en
1 citations

Abstract

Soil mineralogy, analysed by x-ray diffraction (XRD), is crucial to understanding its variability and influence on physical and chemical properties. However, soil analysis by XRD faces challenges, especially with large sample volumes and subjective interpretation. This study proposes a simplified methodology for sample preparation and soil analysis by XRD, which is associated with the principal component analysis (PCA). Two PCA models were built: one using semiquantitative percentages of minerals and another based on diffraction intensities. After analysing 90 samples from nine farms producing <i>Coffea arabica</i>, the results suggest greater efficiency in identifying clusters related to mineralogical composition, offering a fast and objective approach to soil characterization.

Analytical Science AdvancesVol. 6(2)
Instituto Federal do Espírito Santo (BR), Universidade Federal do Espírito Santo (BR)
Openalex Percentile: Top 25%
Spectroscopy and Chemometric Analyses
0.75
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