Multivariate Analysis with XRD Data as a Fingerprinting Technique to Study Burned Soils

Abstract

Fire is a natural process with recognized recurrence. However, ongoing climate change and human activities are causing some disturbances in their natural regimes in most ecosystems. It is important to improve the methodologies used to evaluate the fire-induced changes in soils. This study aims at investigating the potential of the X-ray diffraction (XRD) technique to be used as a fingerprinting technique for burned soils. Multivariate analysis was employed to analyze the XRD data. Hierarchical Cluster Analysis (HCA) and local Partial Least Squares (PLS-2) models were performed. The soil samples are classified as Ferralsols and were collected from an Amazon region, Brazil, from forests, pastures and a slash-and-burn area. The studied temperatures ranged between 25 and 800 °C. Major differences were found for gibbsite, goethite and kaolinite contents due to dehydration. PLS-2 analysis presented better results than HCA as it provided information concerning the two features of the investigated soils, the collection site and the temperature. Therefore, it was possible to characterize soils from different sites and soils heated at different temperatures by using XRD data with multivariate analysis. Such methodology provided important information that may be used in areas with these environmental and soil conditions.

Keywords

• X-ray diffraction
• multivariate analysis
• burning simulation
• ferralsol