Kinetic Evaluation of the Production of Mead from a Non-Saccharomyces Strain.

There is a growing market for craft beverages with unique flavors. This study aimed to obtain a palate-pleasing mead derived from Pichia kudriavzevii 4A as a monoculture. Different culture media were evaluated to compare the fermentation kinetics and final products. The crucial factors in the medium were ~200 mg L-1 of yeast assimilable nitrogen and a pH of 3.5-5.0. A panel of judges favored the mead derived from Pichia kudriavzevii 4A (fermented in a medium with honey initially at 23 °Bx) over a commercial sample produced from Saccharomyces cerevisiae, considering its appearance, fruity and floral flavors (provided by esters, aldehydes, and higher alcohols), and balance between sweetness (given by the 82.91 g L-1 of residual sugars) and alcohol. The present mead had an 8.57% v/v ethanol concentration, was elaborated in 28 days, and reached a maximum biomass growth (2.40 g L-1) on the same fermentation day (6) that the minimum level of pH was reached. The biomass growth yield peaked at 24 and 48 h (~0.049 g g-1), while the ethanol yield peaked at 24 h (1.525 ± 0.332 g g-1), in both cases declining thereafter. The Gompertz model adequately describes the kinetics of sugar consumption and the generation of yeast biomass and ethanol. Pathogenic microorganisms, methanol, lead, and arsenic were absent in the mead. Thus, Pichia kudriavzevii 4A produced a safe and quality mead with probable consumer acceptance.

Prediction of coumarin and ethyl vanillin in pure vanilla extracts using MID-FTIR spectroscopy and chemometrics.

Fourier transform mid-infrared (MID-FTIR) spectroscopy coupled with chemometric analysis was used to identify and quantify coumarin (CMR) and ethyl vanillin (EVA) adulterations in pure vanilla extracts. Forty samples adulterated with CMR (0.25-10 ppm) and forty with EVA (0.25-10%) were prepared from pure vanilla extracts and characterized by MID-FTIR spectroscopy to develop chemometric models. Additionally, six commercial vanilla samples were analyzed. A soft independent modeling of class analogy (SIMCA) model was developed to identify and classify the purity from EVA-adulterated or CMR-adulterated samples. Prediction models for CMR or EVA content were developed using the principal component regression (PCR), partial least squares with single y-variables (PLS1), and with multiple y-variables (PLS2) algorithms. Moreover, the predictions of the best quantification chemometric model were compared with the results of a high-performance liquid chromatography-diode array detector (HPLC-DAD) method to evaluate the accuracy of the prediction. The PLS1 algorithm had better performance using 3 and 8 factors for EVA and CMR, respectively. The SIMCA model showed 100% recognition and rejections rates. The results demonstrate that adulteration of pure vanilla with EVA and CMR could be successfully predicted by the developed technique.