ABSTRACT
Beer is one of the oldest and most known alcoholic beverages whose organoleptic characteristics are the attributes that the consumer seeks, which is why it is essential to ensure proper quality control of the final product. Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with multivariate analysis can be an alternative to traditional methods to predict quality parameters in craft beer. This study aims to develop prediction models based on FT-MIR spectroscopy to simultaneously quantify quality parameters (color, specific gravity, alcohol volume, bitterness, turbidity, pH, and total acidity) in craft beer. Additionally, principal component analysis (PCA) was applied, and it was possible to classify craft beer samples according to their style. Partial least squares (PLS1) developed the best predictive model by obtaining higher R2c (0.9999) values and lower standard error of calibration (SEC: 0.01-0.11) and standard error of prediction (SEP: 0.01-0.14) values in comparison to the models developed with the other algorithms. Specific gravity could not be predicted due to the low variability in the values. Validation and prediction with external samples confirmed the predictive capacity of the developed model. By making a comparison to traditional techniques, FT-MIR coupled with multivariate analysis has a higher advantage, since it is rapid (approximately 6 min), efficient, cheap, and eco-friendly because it does not require the use of solvents or reagents, representing an alternative to simultaneously analyzing quality parameters in craft beer.
ABSTRACT
The microbial corrosion of oil and gas pipes is one of the problems occurring in the oil industry. Various mechanisms explaining microbial corrosion have been demonstrated. Commonly, biocorrosion is attributed to sulfate-reducing bacteria. Also, it has recently been reported that microbial species can connect their electron transport system to metal electrodes. In this research, two spore-forming bacteria isolated in different years from a gas pipeline were identified by biochemical techniques and by 16S rDNA amplification, sequencing, and comparison with the NCBI database. Isolates were also compared between them using molecular techniques as the restriction patterns, unique for 16S rDNA (ARDRA), and the profile of the amplified bit from the genomic DNA, using an unspecific primer (RAPD). The results obtained showed that both isolates corresponded to Clostridium celerecrescens with a 99% similarity according to the sequence reported on the NCBI database. Also, the ARDRA and RAPD electrophoretic profiles of both strains were identical, and no plasmids were found in the strains. Thus, it can be settled that this bacterium is persistent in the environment prevailing in gas pipelines. Also, it was demonstrated that the bacterial secretion of organic acids contributes to the pitting and general biocorrosion of API XL 52 steel. The rates of corrosion obtained, approximately after 40 days, were correlated with the presence and metabolic activity of C. celerecrescens on the metallic surfaces.
