Journal of the Brazilian Chemical Society
URI permanente para esta coleçãohttps://thoth.dti.ufv.br/handle/123456789/13322
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Item Chemometric analysis of UV characteristic profile and infrared fingerprint variations of Coffea arabica green beans under different space management treatments(Sociedade Brasileira de Química, 2016) Terrile, Amélia E.; Marcheafave, Gustavo G.; Oliveira, Guilherme S.; Rakocevic, Miroslava; Bruns, Roy E.; Scarminio, Ieda S.Ultraviolet characteristic profiles and infrared spectroscopic (FTIR) fingerprints of green bean extracts of Coffea arabica L., cv. IAPAR 59, cultivated in two planting patterns, rectangular and square, and at two different densities, 10,000 and 6,000 plants ha-1, identified as R10,R6,S10, and S6 were analyzed with principal component and hierarchical cluster analyses. A simplex centroid design for four solvents (ethanol, acetone, dichloromethane, hexane) was used for sample extraction. The largest chlorogenic acid (CGA) contents were found at the lower planting density. The dichloromethane extracts of the S10 treatment showed the highest levels of unsaponifiable lipids (cafestol and kahweol). The R6 treatment showed a slightly higher content of cafestol and kahweol. Cluster analysis of FTIR fingerprints confirmed that the CGA and caffeine levels differentiate the spatial arrangements. The FTIR fingerprints suggest that green beans from S6 and R10 were richer in lipids and the other two treatments had more sugars and proteins.Item Irrigation and light acess effects on Coffea arabica L. leaves by FTIR-chemometric analysis(Sociedade Brasileira de Química, 2018) Sanchez, Patrícia M.; Pauli, Elis D.; Scheel, Guilherme L.; Rakocevic, Miroslava; Brunsc, Roy E.; Scarminio, Ieda S.Coffee bean chemical compositions has been extensively studied. However, there is a small amount of research on other parts of the coffee plant, including leaves. Fourier transform infrared (FTIR) spectral profiles of Coffea arabica L. cv. IAPAR 59 leaf extracts from a simplex-centroid design were studied by principal component analysis (PCA) to evaluate the effect of solvente extractor on its metabolites. PCA indicated that the extractor solvents containing ethanol were the most suitable for this study. FTIR spectra in conjunction with orthogonal signal correction and partial least squares-discrimination analysis (OSC-PLS-DA) were used to classify and discriminate the leaves of irrigated and non-irrigated plants by bands related to carbohydrates, amino acids and lipids. Leaves receiving different intensities of solar radiation were also discriminated by bands corresponding to caffeine, carbohydrates and lipids. FTIR spectral profile analyzed with chemometric tools showed to be a useful, powerful and simple procedure to discriminate coffee leaves collected from different microclimate conditions.Item Differential scanning calorimetry and infrared spectroscopy combined with chemometric analysis to the determination of coffee adulteration by corn(Sociedade Brasileira de Química, 2017) Brondi, Ariadne M.; Torres, Claudia; Garcia, Jerusa S.; Trevisan, Marcello G.Roasted and ground coffee is targeted by fraudulent addiction of products. In this way the determination of contaminants in coffee has economic and nutritional importance. In this study, the coffee adulteration by corn were detected using DSC (differential scanning calorimetry) and FTIR (Fourier transform infrared spectroscopy) coupled to PCA (principal component analysis), and PLS (partial least squares) models. Three different levels of roasted and ground Coffea arabica L. were used to prepare mixtures with roasted and ground corn. The level of adulteration used was between 0.5 to 40% (m/m). It was observed that both DSC and FTIR coupled with PCA are able to discriminate adulterated from unadulterated samples of coffee by corn at levels below 1%. PLS models were built with DSC and FTIR data reaching good correlation between the values of estimated and reference concentrations, with RMSECV (root mean square error of cross-validation) lower than 3.5% for DSC data and 2.7% for FTIR data.