COMBINAÇÃO DE FERRAMENTAS ESTATÍSTICAS E TÉCNICAS ESPECTROFOTOMÉTRICAS APLICADAS NA ESTIMATIVA DA CAPACIDADE ANTIOXIDANTE DE PRÓPOLIS

• Ano de defesa: 2022
• Autor(a) principal: NASCIMENTO, CAMILA LIMA DO
• Orientador(a): Torres, Yohandra Reyes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Centro-Oeste
• Programa de Pós-Graduação: Programa de Pós-Graduação em Química (Mestrado)
• Departamento: Unicentro::Departamento de Ciências Exatas e de Tecnologia
• País: Brasil
• Palavras-chave em Português: Própolis; Capacidade Antioxidante; Regressão PLS; Análise Multivariada
• Palavras-chave em Inglês: Propolis; Antioxidant Capacity; Partial Least Squares Regression; Multivariate Data Analysis
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::QUIMICA
• Link de acesso: http://tede.unicentro.br:8080/jspui/handle/jspui/1967

Propolis is an apicultural product of high scientific value. Its quality control includes the determination of its flavonoid and phenolic contents and antioxidant capacity. These properties are obtained by spectrophotometric methods which often comprise analytical protocols with several steps and uses organic solvents and toxic reagents. Then, these protocols are time consuming, especially when large number of samples are analyzed as it is routine in quality control laboratories. In this regard, the present work aimed to develop a faster and lower cost method for the determination of quality parameters of propolis, combining chemometric and spectroscopy tools. To this purpose, mid-IR and UV spectra of propolis extracts were recorded and the flavonoid and phenolic contents and the antioxidant capacity of propolis samples by DPPH and CUPRAC methods were used as references assays. Subsequently, Partial Least Squares Regression (PLS Regression) was applied to model the relationship between spectroscopic data and properties of propolis. All IR-based and UV-based PLS models were appropriate to estimate the antioxidant capacity and total flavonoids and phenolic contents of propolis samples. Determination coefficients for calibration were higher or equal than 0.65 (R² ≥ 0.65) and adequate values for RMSEC, RMSEP, RMSECV, and RPD were obtained. Consequently, simple IR and UV spectra combined with PLS models can be potentially used to predict the studied properties with acceptable accuracy. This approach might be employed in the quality control of propolis extracts with the advantages of being a fast, low cost and green methodology reducing laborious handling of sample, chemical reagents, solvents in addition to decreasing chemical waste and potential environment impact.