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Xuejing Fan

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Open access Sep 2026

Effects of Lactic Acid Bacteria Fermentation on the Physicochemical Properties, Nutritional Value, and Sensory Characteristics of a White Kidney Bean-Based Beverage

The increasing demand for sustainable food systems, high-value resource utilization, and dietary diversification has promoted the development of plant-based beverages. This study aimed to develop a white kidney bean-based beverage (WKBB) through lactic acid bacteria fermentation and investigate the effects of different fermentation strategies on its physicochemical properties, nutritional characteristics, volatile compounds, and sensory quality. WKBB was fermented using Lactiplantibacillus plantarum, Limosilactobacillus fermentum, and a mixed culture of both strains. The results showed that fermentation significantly modified the quality characteristics of WKBB, including changes in its physicochemical properties and free amino acid composition. Furthermore, fermentation promoted the release of phenolic and flavonoid compounds during simulated gastrointestinal digestion. GC–MS analysis revealed that fermentation altered the volatile composition of WKBB and increased the diversity of volatile compounds, thereby contributing to a more complex flavor profile. Sensory evaluation indicated that fermented samples exhibited improved overall sensory characteristics, with mixed-strain fermentation resulting in a more balanced quality profile. These findings demonstrate that lactic acid bacteria fermentation, particularly mixed-strain fermentation, is a promising and sustainable strategy for the development of a white kidney bean-based beverage and for enhancing the utilization of plant-based resources.

Ye-Wen Xu, Li-Ping Sun, Ying Gu et al. · Foods · 0 citations

Open access Jul 2026

Machine learning–assisted surface-enhanced Raman spectroscopy for multiple and rapid screening of foodborne pathogenic bacteria

To address the challenge of mixed contamination of foodborne pathogenic bacteria in food, in this study, a machine learning (ML) assisted surface-enhanced Raman scattering (SERS) sensing platform was proposed for multiple and rapid screening of foodborne pathogenic bacteria. 4-Mercaptophenylboronic acid-functionalized gold nanoparticles (AuNPs@4-MPBA) was introduced as SERS substrate and the molecular recognition and electromagnetic enhancement mechanisms for target analytes were elucidated by theoretical simulation. The sensing platform achieved efficient identification and differentiation of single and mixed contaminations of Escherichia coli, Salmonella typhimurium, Shigella, Listeria monocytogenes, and Staphylococcus aureus in three tea samples. The ability of the model to generalize across varying conditions was evaluated using a mixed spectral dataset from different tea sample matrices. After spectral preprocessing, the Random Forest (RF) model was used to classify 31 samples, achieving a classification accuracy of 97.34% and an out-of-bag accuracy of 95.98%, demonstrating excellent stability and generalization capability. The proposed approach enabled the rapid and accurate classification of foodborne pathogenic bacteria in complex food matrices, offering a promising strategy for rapid food safety emergency screening.

Simin Dai, Ceping Yin, Xuejing Fan et al. · Food Quality and Safety · 0 citations