Potentiometric characterization and recognition of humic acid patterns extracted from altitude soils

Authors

• Efraim Lázaro Reis Departamento de Química Universidade Federal de Viçosa 36.570-900, Viçosa, MG http://orcid.org/0000-0003-4285-8892
• Rita Aparecida Dutra Departamento de Química Universidade Federal de Viçosa 36.570-900, Viçosa, MG
• Vinícius de Mello Benites Embrapa Solos Jardim Botânico 22.460-000 – Rio de Janeiro - RJ
• César Reis Departamento de Química Universidade Federal de Viçosa 36.570-900, Viçosa, MG
• Clausius Duque Gonçalves Reis Instituto de Ciências Exatas Universidade Federal de Viçosa 38.810-000, Rio Paranaíba, MG
• Eduardo de Sá Mendonça Departamento de Agronomia Universidade Federal do Espírito Santo 29.500-000, Alegre, ES
• Paulo Henrique Fidêncio Departamento de Química Universidade Federal dos Vales do Jequitinhonha e Mucurí 39.100-000, Diamantina, MG

DOI:

https://doi.org/10.17058/tecnolog.v24i2.15121

Keywords:

Solos de altitude, Ácidos húmicos, Titulação potenciométrtica, Análise das componentes principais.

Abstract

High altitude rock-vegetation is found at the top of highest mountains in Brazil such as Espinhaço and Mantiqueiracomplexesat Minas Gerais and Bahia states consisting in ecosystems with outstanding characteristics in diversity of flora and fauna.The soil in these areas is generally shallow, poor in nutrients, but rich in exchangeable iron and aluminum.The characterization of humic acids from such ecosystems among other chemical components is very useful to understand the fundamental properties of the organic composition of the soil.A total of 72 soil samples from 10 different locations in the Espinhaço and Mantiqueira complexes were potentiometrically characterized.The data of the potentiometric titrations were processed in a software based on the Delphi language, in order to obtain the ionization constants and the percentages of the titrated groups. This software proved to be efficient in the reproduction of the titration curves with a notable agreement with the experimental ones.After processing the potentiometric data, the values of the ionization constants and percentages of the carboxylic and phenolic groups were subjected to the principal components analysis in the MatLab environment, using a matrix of 72 samples and 10 variables, obtaining a model in which it was found that the first four principal components explained 91.23% of the total variation of the original data.The characteristics of humic acids evidenced by the potentiometric titration reflect the conditions in which these acids were formed, although not allowing a more effective separation between the groups evidenced by the principal components analysis.