Coconut milk serves as an excellent plant-based substitute for animal milk in fermentation with kefir grains, producing a vegetarian-friendly and allergy-safe fermented beverage. This study examined how fermenting coconut milk with milk kefir grains affects its antioxidant capacity, tyrosinase inhibition, probiotic growth, total phenolic content, and protein profile. Results showed significant improvements in cellular antioxidant and anti-tyrosinase effects, along with enhanced growth of the probiotic Lactobacillus acidophilus during fermentation, especially at 120 h. Conversely, fermentation decreased the overall phenolic content and led to the breakdown of most proteins in the coconut milk. Nonetheless, the process promoted the formation of smaller proteins and peptides around 10 kDa, possibly contributing to the increased antioxidant, anti-tyrosinase, and probiotic growth-promoting effects. These findings offer valuable insights into how fermentation with kefir alters the biological activities and bioactive compounds of coconut milk, helping to identify the optimal fermentation duration for producing a health-enhancing, high-quality fermented beverage.
Konjac glucomannan (KGM), derived from konjac tubers, is a novel functional plant polysaccharide that plays a significant role in antioxidant activity, anti-tumour effects and blood glucose regulation. This study aimed to develop an optimal extraction method for KGM. The extraction yield of KGM was surveyed quantitatively analysed using a response surface central composite design (CCD) to maximise the yield. A quadratic regression model was created to illustrate the interactions between the factors influencing KGM extraction yield. The findings indicated that the effects of extraction temperature and the liquid-to-solid ratio had a greater impact on the extraction yield of KGM than the extraction time and extraction frequency. The optimal extraction conditions for KGM were determined to be an extraction temperature of 100 degrees C, an extraction time of 2 h, an extraction frequency of 2, and a liquid-to-solid ratio of 113 : 1. Under these optimal conditions, the extraction yield of KGM reached 15.31%.
Cocoa beans quality parameters are among other things biochemical properties such as moisture content, reducing sugars, fat, protein and total phenolic content (TPC) changed during postharvest processes. Current analytical approaches to these parameters are usually not only destructive and time-consuming but also laboratory-based analyses. This study aimed at assessing the potential of short-wave near infrared (SW-NIR) spectroscopy (954-1 700 nm) combined with partial least squares regression (PLSR) for the prediction of these quality parameters in both fresh, fermented, dried and roasted Forastero cocoa nibs. In total, a portable Flame-NIR+ spectrometer analysed 400 samples. Before developing the model, we have compared several spectral preprocessing methods like Savitzky-Golay derivatives, multiple scatter correction (MSC), standard normal variate (SNV), and normalisation. The spectra exhibited various absorption features linked to O-H, C-H, and N-H links reflective of evolving compositions across proximate processing stages. The prediction coefficients (R2P) obtained for moisture content (0.984), reducing sugars (0.958), protein (0.992), and total phenolic content (0.954) of the cocoa nibs was good, while fat prediction showed lower predictive performance than the other evaluated parameters. Savitzky-Golay derivative preprocessing consistently improved the performance of models across all evaluated parameters. These results show that SW-NIR spectroscopy with PLSR can be applied for fast, non-destructive and simultaneous estimations of multiple quality attributes in cocoa nibs during different stages of postharvest processing.
Nutritional strategies supporting healthy ageing and cognitive well-being have gained increasing attention as global populations age. Among dietary approaches, foods rich in bioactive compounds are of particular interest due to their potential involvement in biological pathways relevant to cognitive function. Soups represent versatile food matrices for incorporating and delivering a wide range of plant-derived ingredients, including vegetables, legumes, herbs, and mushrooms. These ingredients provide bioactive compounds such as polyphenols, carotenoids, terpenoids, dietary fibre, and other phytochemicals exhibiting antioxidant, anti-inflammatory, and enzyme-modulating properties. Evidence from nutritional, experimental, and mechanistic studies suggests that such compounds may influence processes associated with cognitive health, including oxidative balance, inflammatory responses, and gut-brain axis interactions. In addition, food-processing technologies such as pulsed electric fields and high hydrostatic pressure may improve the retention and bioaccessibility of selected bioactive compounds in soup-based foods. However, direct evidence linking soup consumption with cognitive outcomes remains limited, and much of the available literature is derived from studies on individual ingredients, isolated compounds, or experimental models. This review critically examines the role of soups as functional food matrices for the delivery of bioactive compounds associated with cognitive health, rather than as independently proven neuroprotective interventions. Particular attention is given to distinguishing direct soup-based evidence from ingredient-based and mechanistic studies, while also discussing the influence of technological processing on bioactive compound stability, bioaccessibility, and the potential nutritional value of functional soup formulations.
This model comparative study evaluated 16 monovarietal Blaufränkisch red wines from the Czech Republic, Hungary, Austria, and Slovakia focused on five parameters related to their antioxidant properties: total polyphenol content (TPC), total anthocyanin content (TAC), antioxidant activity assessed by the 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) radical scavenging assay and the ferric reducing antioxidant power (FRAP) assays, and wine colour intensity. Multivariate statistics were applied. The FRAP assay showed a very strong positive correlation with TPC (r = 0.968), supporting the central role of polyphenols in wine antioxidant activity. The highest TAC (285.6 mg.L-1) was observed in the Czech sample, while the lowest value (48.0 mg.L-1) was found in the Hungarian sample (overall mean 159.61 mg.L-1). FRAP results ranged from 13.6 to 21.53 mmol TE.L-1, with the highest value in the Austrian wine and the lowest in the Hungarian wine. DPPH activity showed a strong negative correlation with wine colour (r = -0.924) and a moderate negative correlation with TPC (r = -0.606). Statistically significant differences among countries were found for DPPH, FRAP and colour (Austria and Czech Republic for colour, P = 0.003 226). FRAP method, which aligns with TPC, appears to be better suited for characterising Blaufränkisch antioxidant activity than DPPH.
