FT-MIR-ATR Associated with Chemometrics Methods: A Preliminary Analysis of Deterioration State of Brazil Nut Oil.

Brazil nut oil is highly valued in the food, cosmetic, chemical, and pharmaceutical industries, as well as other sectors of the economy. This work aims to use the Fourier transform infrared (FTIR) technique associated with partial least squares regression (PLSR) and principal component analysis (PCA) to demonstrate that these methods can be used in a prior and rapid analysis in quality control. Natural oils were extracted and stored for chemical analysis. PCA presented two groups regarding the state of degradation, subdivided into super-degraded and partially degraded groups in 99.88% of the explained variance. The applied PLS reported an acidity index (AI) prediction model with root mean square error of calibration (RMSEC) = 1.8564, root mean square error of cross-validation (REMSECV) = 4.2641, root mean square error of prediction (RMSEP) = 2.1491, R2cal (calibration correlation coefficient) equal to 0.9679, R2val (validation correlation coefficient) equal to 0.8474, and R2pred (prediction correlation coefficient) equal to 0, 8468. The peroxide index (PI) prediction model showed RMSEC = 0.0005, REMSECV = 0.0016, RMSEP = 0.00079, calibration R2 equal to 0.9670, cross-validation R2 equal to 0.7149, and R2 of prediction equal to 0.9099. The physical-chemical analyses identified that five samples fit in the food sector and the others fit in other sectors of the economy. In this way, the preliminary monitoring of the state of degradation was reported, and the prediction models of the peroxide and acidity indexes in Brazil nut oil for quality control were determined.

First report of phenolic compounds isolated from Inga stipularis DC. (fabaceae) leaves.

Several species of the Inga genus are used by Amazonian indigenous communities to treat injuries, pain and inflammations, which is directly related to the presence of phenolic compounds in these species. Many studies have addressed the phytochemical relevance of this genus, but they are still few considering the large number of species. Therefore, this study aimed to investigate the chemical composition of Inga stipularis leaves in order to find compounds with potential pharmacological application and economic interest. The developed method allowed the isolation and identification of 8 compounds in the ethanol extract of I. stipularis: eucryphin, neoastilbin, astilbin, neoisoastilbin, isoastilbin, quercitrin, engeletin and isoengeletin. Astilbin stands out for having been isolated directly from the fractionation of the extract by SPE with high yield. This study was a pioneer for I. stipularis and revealed the potential of the species as an abundant source of compounds of pharmacological and economic interest.