Regatieri Lueji, Vitalis Flora, Bujna Erika, Nguyen Quang Duc, Kovacs Zoltan
Department of Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), 1118 Budapest, Hungary.
Department of Bioengineering and Alcoholic Drink Technology, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), 1118 Budapest, Hungary.
Foods. 2025 Apr 5;14(7):1274. doi: 10.3390/foods14071274.
The nutritional effects of fruit juices, combined with the added value of a probiotic, provide a plant-based fortified functional food. Some process-related drawbacks are caused by the pH parameter, which will affect the survival of probiotics during their industrial processing and storage. By means of developing a monitoring method for probiotic activity, the present study aims to investigate the application of near-infrared spectroscopy (NIR) as a correlative analytical method for fermentation process tracking, in association with the different absorption patterns of bound water, explained by aquaphotomics. The data evaluated in the wavelength range of 1300-1600 nm indicate classification accuracies of 99-100% and 99-93% during calibration and validation, respectively, when applying PCA-LDA for discriminating the fermentation times, for each one of the single and mixed bacterial groups. During PLSR prediction, according to the fermentation times, the validation models developed for pH show coefficients of determination in the range of 0.96 to nearly 1 and root mean square errors of 0.05 and 0.19. On the other hand, for the PLSR prediction of log cell count (CFU/mL), validation modeling shows a coefficient of determination of 0.85 and a root mean square error of 0.23. All things considered, the results support the applicability of combining NIR and aquaphotomics as a bioprocess monitoring tool, which can be further implemented in different studies and industrial contexts.
果汁的营养功效，再加上益生菌的附加值，构成了一种基于植物的强化功能性食品。一些与加工过程相关的缺点是由pH参数引起的，这会影响益生菌在工业加工和储存过程中的存活。通过开发一种益生菌活性监测方法，本研究旨在探讨近红外光谱（NIR）作为一种相关分析方法在发酵过程跟踪中的应用，并结合水光谱学解释的结合水的不同吸收模式。在1300 - 1600 nm波长范围内评估的数据表明，当应用主成分分析-线性判别分析（PCA-LDA）来区分单一和混合细菌组中每一组的发酵时间时，在校准和验证期间的分类准确率分别为99 - 100%和99 - 93%。在偏最小二乘回归（PLSR）预测过程中，根据发酵时间，为pH值建立的验证模型的决定系数在0.96至接近1的范围内，均方根误差分别为0.05和0.19。另一方面，对于对数细胞计数（CFU/mL）的PLSR预测，验证模型的决定系数为0.85，均方根误差为0.23。综合考虑，结果支持将近红外光谱和水光谱学结合作为生物过程监测工具的适用性，这可以在不同的研究和工业环境中进一步实施。
