Correlation of quantitative sensorial descriptors and chromatographic signals of beer using multivariate calibration strategies.

In this study, two important sensorial parameters of beer quality - bitterness and grain taste - were correlated with data obtained after headspace solid phase microextraction - gas chromatography with mass spectrometric detection (HS-SPME-GC-MS) analysis. Sensorial descriptors of 32 samples of Pilsner beers from different brands were previously estimated by conventional quantitative descriptive analyses (QDA). Areas of 54 compounds systematically found in the HS-SPME-GC-MS chromatograms were used as input data. Multivariate calibration models were established between the chromatographic areas and the sensorial parameters. The peaks (compounds) relevant to build each multivariate calibration model were determined by genetic algorithm (GA) and ordered predictors selection (OPS), tools for variable selection. GA selected 11 and 15 chromatographic peak areas, for bitterness and grain taste, respectively; while OPS selected 17 and 16 compounds for the same parameters. It could be noticed that seven variables were commonly pointed out by both variable selection methods to bitterness parameter and 10 variables were commonly selected to grain taste attribute. The peak areas most significant to the evaluation of the parameters found by both variable selection methods fed to the PLS algorithm to find the proper models. The obtained models estimated the sensorial descriptors with good accuracy and precision, showing that the utilised approaches were efficient in finding the evaluated correlations. Certainly, the combination of proper chemometric methodologies and instrumental data can be used as a potential tool for sensorial evaluation of foods and beverages, allowing for fast and secure replication of parameters usually measured by trained panellists.

Heat and phosphate starvation effects on the proteome, morphology and chemical composition of the biomining bacteria Acidithiobacillus ferrooxidans.

Acidithiobacillus ferrooxidans is a Gram negative, acidophilic, chemolithoautotrophic bacterium that plays an important role in metal bioleaching. During bioleaching, the cells are subjected to changes in the growth temperature and nutrients starvation. The aim of this study was to gather information about the response of the A.ferrooxidans Brazilian strain LR to K2HPO4 starvation and heat stress through investigation of cellular morphology, chemical composition and differential proteome. The scanning electron microscopic results showed that under the tested stress conditions, A. ferrooxidans cells became elongated while the Fourier transform infrared spectroscopy (FT-IR) analysis showed alterations in the wavenumbers between 850 and 1,275 cm(-1), which are related to carbohydrates, phospholipids and phosphoproteins. These findings indicate that the bacterial cell surface is affected by the tested stress conditions. A proteomic analysis, using 2-DE and tandem mass spectrometry, enabled the identification of 44 differentially expressed protein spots, being 30 due to heat stress (40°C) and 14 due to K2HPO4 starvation. The identified proteins belonged to 11 different functional categories, including protein fate, energy metabolism and cellular processes. The upregulated proteins were mainly from protein fate and energy metabolism categories. The obtained results provide evidences that A. ferrooxidans LR responds to heat stress and K2HPO4 starvation by inducing alterations in cellular morphology and chemical composition of the cell surface. Also, the identification of several proteins involved in protein fate suggests that the bacteria cellular homesostasis was affected. In addition, the identification of proteins from different functional categories indicates that the A. ferrooxidans response to higher than optimal temperatures and phosphate starvation involves global changes in its physiology.