| Autor: |
Kasemsumran S; Laboratory of Non-Destructive Quality Evaluation of Commodities, Kasetsart Agricultural and Agro-Industrial Product Improvement Institute (KAPI), Kasetsart University, Bangkok 10900, Thailand., Boondaeng A; Laboratory of Enzyme and Microbiology, KAPI, Kasetsart University, Bangkok 10900, Thailand., Ngowsuwan K; Laboratory of Non-Destructive Quality Evaluation of Commodities, Kasetsart Agricultural and Agro-Industrial Product Improvement Institute (KAPI), Kasetsart University, Bangkok 10900, Thailand., Jungtheerapanich S; Laboratory of Non-Destructive Quality Evaluation of Commodities, Kasetsart Agricultural and Agro-Industrial Product Improvement Institute (KAPI), Kasetsart University, Bangkok 10900, Thailand., Apiwatanapiwat W; Laboratory of Enzyme and Microbiology, KAPI, Kasetsart University, Bangkok 10900, Thailand., Janchai P; Laboratory of Enzyme and Microbiology, KAPI, Kasetsart University, Bangkok 10900, Thailand., Meelaksana J; Laboratory of Enzyme and Microbiology, KAPI, Kasetsart University, Bangkok 10900, Thailand., Vaithanomsat P; Laboratory of Enzyme and Microbiology, KAPI, Kasetsart University, Bangkok 10900, Thailand. |
| Abstrakt: |
This study used Fourier transform-near-infrared (FT-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. |
