2025 9+10

Researcher outlines vision for implants that could help patients reclaim vital connection with their surroundings.

Wine quality is closely linked to sensory attributes such as aroma, taste, and mouthfeel, all of which are influenced by grape variety, “terroir”, and vinification practices. Among these, aroma is particularly important for consumer preference, and it results from a complex interplay of numerous volatile compounds. Conventional sensory methods, such as descriptive analysis (DA) performed by trained panels, offer valuable insights but are often time-consuming, resource-intensive, and subject to individual variability. Recent advances in sensor technologies—including electronic nose (E-nose) and electronic tongue (E-tongue)—combined with chemometric techniques and machine learning algorithms, offer more efficient, objective, and predictive approaches to wine aroma profiling. These tools integrate analytical and sensory data to predict aromatic characteristics and quality traits across diverse wine styles. Complementary techniques, including gas chromatography (GC), near-infrared (NIR) spectroscopy, and quantitative structure–odor relationship (QSOR) modeling, when integrated with multivariate statistical methods such as partial least squares regression (PLSR) and neural networks, have shown high predictive accuracy in assessing wine aroma and quality. Such approaches facilitate real-time monitoring, strengthen quality control, and support informed decision-making in enology. However, aligning instrumental outputs with human sensory perception remains a challenge, highlighting the need for further refinement of hybrid models. This review highlights the emerging role of predictive modeling and sensor-based technologies in advancing wine aroma evaluation and quality management.

Researchers have designed an algorithm that can predict how good a white wine tastes by analysing its chemical components. The tool could help winemakers craft better wines – including...

Looking at the fundamental terminology and data analysis principles in benchtop GC–MS

Artificial intelligence (AI) is increasingly being integrated into sensory evaluation in food science to overcome limitations of traditional methods s…

Food flavor represents a complex, multisensory experience shaped by the interplay of volatile and non-volatile components, texture, and consumer perce…

Citrus fruit peels constitute an abundant yet underutilized source of agricultural waste, despite being rich in bioactive compounds with potential app…

The author, an obsessive plant hunter, has created a botanical resource for Britain like no other.

Lemon is widely valued for its bioactive components and unique flavor, which are influenced by diverse volatile organic compounds (VOCs). This study i…

Researchers say low- and no-calorie sweeteners appear to affect thinking and memory in middle age

The diversity of odor and flavor sensory attributes present in common beans, along with their variability (i.e., sensory diversity) and the chemical c…

From tea and dark chocolate to apples and grapes, everyday foods rich in flavan-3-ols could help lower blood pressure and improve vascular health, according to new research.

During chocolate production, thermal processes such as roasting and conching promote nonenzymatic browning reactions such as the Maillard reaction and caramelization. In the present work, the MRPs furosine, 3-deoxyglucosone (3-DG), 3-deoxygalactosone (3-DGal), 5-hydroxymethylfurfural (HMF), N-ε-fructosyllysine, N-ε-lactulosyllysine, N-ε-carboxymethyllysine (CML), N-ε-carboxyethyllysine (CEL), pyrraline, methylglyoxal-derived hydroimidazolone 1 (MG-H1), formyline, maltosine, and rhamnolysine were quantitated in 4 filled, 12 dark, 11 milk, and 4 white chocolate samples. The predominant MRP in filled chocolates was N-ε-fructosyllysine (up to 2662 mg/kg of chocolate), whereas in milk chocolates, it was N-ε-lactulosyllysine (up to 883 mg/kg of chocolate). Filled and milk chocolates contain higher levels of furosine and CML. Dark and white chocolates exhibit lower levels of MRPs such as furosine, CML, CEL, and formyline. The consumption of milk chocolates and filled chocolates can contribute significantly to the dietary intake of pyrraline, N-ε-fructosyllysine, N-ε-lactulosyllysine, and CML.