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

Area of Science:

• Geochemistry
• Soil Science
• Analytical Chemistry

Background:

• Soil mineralogy is key to understanding soil properties and agricultural productivity.
• Traditional X-ray diffraction (XRD) analysis presents challenges in sample handling and interpretation.
• Objective and efficient soil characterization methods are needed for precision agriculture.

Purpose of the Study:

• To develop a simplified sample preparation and analysis methodology for soil mineralogy using XRD.
• To integrate principal component analysis (PCA) for objective interpretation of XRD data.
• To assess the efficiency of the proposed method in characterizing soil mineralogical composition.

Main Methods:

• A simplified sample preparation protocol for soil analysis by XRD was developed.
• Two principal component analysis (PCA) models were constructed: one based on mineral percentages and another on diffraction intensities.
• Ninety soil samples from nine *Coffea arabica* farms were analyzed.

Main Results:

• The integrated XRD-PCA methodology demonstrated high efficiency in identifying distinct clusters based on mineralogical composition.
• The approach provided a fast and objective method for soil characterization.
• PCA models effectively differentiated soil samples according to their mineralogical profiles.

Conclusions:

• The proposed simplified XRD methodology coupled with PCA offers a robust and efficient tool for soil mineralogical characterization.
• This method facilitates objective soil analysis, crucial for optimizing agricultural practices, particularly for crops like *Coffea arabica*.
• The study highlights the potential of PCA in overcoming subjective interpretation issues in XRD soil analysis.