Renata Vieira da Silva, Marcos Valério Vieira Lyrio, Roberta Quintino Frinhani, Lucas Louzada Pereira, Paulo Roberto Filgueiras, Marcos Antônio Ribeiro
{"title":"Application of Chemometric Methods in X-Ray Diffraction Data on Arabica Coffee Management Soils in Brazil","authors":"Renata Vieira da Silva, Marcos Valério Vieira Lyrio, Roberta Quintino Frinhani, Lucas Louzada Pereira, Paulo Roberto Filgueiras, Marcos Antônio Ribeiro","doi":"10.1002/ansa.70042","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"6 2","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://chemistry-europe.onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.70042","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical science advances","FirstCategoryId":"1085","ListUrlMain":"https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/ansa.70042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0
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 Coffea arabica, the results suggest greater efficiency in identifying clusters related to mineralogical composition, offering a fast and objective approach to soil characterization.