This research investigated the impact of the concentration of pineapple juice on the characteristics of pineapple wine during fermentation with Saccharomyces cerevisiae var. burgundy. Three ratios of fresh pineapple juice to water were mixed to obtain three treatments, which were T1—2:1, T2—1:1, and T3—1:2. The °Brix and pH of all pineapple juice and water ratios were adjusted to 25 and 4, respectively. The results showed that changes in alcohol, pH, Total Soluble Solids (TSS), Total Titratable Acidity (TAA, as citric acid), and Volatile Acidity (VA, as acetic acid) during the 10-day fermentation among three treatments were significantly different. The highest alcohol content was obtained from the 2:1 with values of 10.71% (v/v). The mixed ratio at 1:1 and 1:2 obtained the alcohol value of 9.61 and 8.35% (v/v), respectively. After ten days of fermentation, TSS, pH values, TAA, and VA were in the range of 9.7–13 °Brix, 3.56–3.82, 0.384–0.448, and 0.0013–0.0016, respectively. However, the appearance, aroma, and taste of all ratios were not significantly different. Sweetness and overall liking, wine with pineapple juice/water ratio at 2:1 had the highest score (p ≤ 0.05). The total antioxidant activities determined by DPPH and total phenolic content were 0.91 mmol/L TE and 365.80 mg/L GAE, respectively, as confirmed by FTIR spectral analyses.

Near infrared spectroscopy is a non-destructive technique used for measuring and analyzing chemical compositions in an organic sample. The calibration equation and spectrum are used for calculating the prediction result. In this case, the spectrum provides very important data; therefore, the accuracy of the near infrared prediction system depends on the sample preparation because the spectrum is sensitive to physical property conditions such as sample temperature. When the sample temperature has changed, the absorption peak will be shifted nonlinearly in both the absorption value and wavelengths around 840 nm and 940 nm (in the short regions). Consequently, if applying a calibration model developed from spectra of a constant sample temperature by using a linear multivariate data analysis to predict the samples with different temperature conditions, the average of difference between actual values and predicted values (bias) will occur. Therefore, the objective of this research was to develop a spectra temperature compensation method namely the temperature compensation coefficient method by applying direct standardization algorithm. By the use of temperature compensation coefficient, the temperature effect can be solved and the accurate prediction results can be obtained. Moreover, the performance of temperature compensation coefficient was investigated and compared with the fixed temperature and three compensation methods, such as generalized least squares weighting, external parameter orthogonalization, and global calibration. The results indicated that temperature compensation coefficient method and the global calibration gave the best result with high accuracy of the lowest bias at 95% confident level.

This study used Fourier transform-near-infrared (NIR) spectroscopy equipped with the liquid probe in combination with an efficient wavelength selection method named searching combination moving window partial least squares (SCMWPLS) for the determination of ethanol, total soluble solids, total acidity, and total volatile acid contents in pineapple fruit wine fermentation using Saccharomyces cerevisiae var. Burgundy. Two fermentation batches were produced, and the NIR spectral data of the calibration samples in the wavenumber range of 11,536–3952 cm−1 were obtained over ten days of the fermentation period. SCMWPLS coupled with second derivatives searched and optimized spectral intervals containing useful information for building calibration models of four parameters. All models were validated by test samples obtained from an independent fermentation batch. The SCMWPLS models showed better predictions (the lowest value of prediction error and the highest value of residual predictive deviation) with acceptable statistical results (under confidence limits) among the results achieved by using the whole region. The results of this study demonstrated that FT-NIR spectroscopy using a liquid probe coupled with SCMWPLS could select the optimized wavelength regions while reducing spectral points and increasing accuracy for simultaneously monitoring the evolution of four chemical parameters in pineapple fruit wine fermentation.

Pineapples are a tropical fruit with high nutritional value and high vitamin and sugar contents. In this study, low-grade pineapples were fermented to produce vinegar using surface culture fermentation (SCF), which involved the addition of dragon fruit juice, to compare the quality and antioxidant activity of different preparations of vinegar. The highest acetic acid concentration (7.35%) was obtained from pineapple vinegar after 20 days of incubation. Vinegar made from mixed pineapple and dragon fruit juice without peel and vinegar with pineapple and dragon fruit juice with peel had acetic acid concentrations of up to 6.20% and 4.50%, respectively. The mixed-fruit vinegar of pineapple and dragon fruit juice with peel displayed the highest antioxidant activity at 210.74 µg/g TE, while no significant difference was found between the other two vinegars (189.52 vs. 187.91 µg/L TE). Notably, the volatile compounds detected in the vinegars were alcohols and esters, which may contribute to the distinct aroma. Overall, the addition of dragon fruit juice with peel to pineapple vinegar increased the phenolic content and antioxidant activity; however, fermentation was slightly slower than that of the other two test materials.

No abstract