Chromatographic Profiling of Artisanal Chocolates: Volatile Composition and Methylxanthines as Markers of Cocoa Content March 14, 2026

The increasing demand for artisanal chocolates highlights the importance of reliable analytical strategies for quality assurance and product authentication. In this study, 45 Brazilian artisanal chocolates (36%–100% cocoa) were characterized by integrated chromatographic and chemometric analyses. Seventeen representative samples were evaluated for volatile compounds using HS-SPME/GC-MS, and methylxanthines were quantified by HPLC-DAD after optimization of an ultrasound-assisted liquid–liquid extraction method. The procedure achieved recoveries of 92% ± 10% for theobromine and 95% ± 3% for caffeine, meeting international validation criteria. In total, 72 volatile compounds were identified, mainly acids, esters, pyrazines, and aldehydes, associated with descriptors such as roasted, nutty, floral, and fruity. Theobromine (1.158–21.033 g kg⁻¹) and caffeine (0.058–1.997 g kg⁻¹) concentrations showed strong positive correlations with declared cocoa content. Principal component analysis revealed clear separation between low- and high-cocoa chocolates, with theobromine as the main discriminating variable. The results demonstrate that methylxanthines are robust chemical markers for chocolate authentication and classification, and that the combined use of GC-MS, HPLC, and multivariate analysis provides a reliable workflow for quality control, traceability, and prevention of commercial fraud in the chocolate industry.

Unveiling the Complexity of Pu‐Erh Tea Flavor: Integrating Chemistry, Processing, and Sensory Neuroscience March 14, 2026

Pu-erh tea, a geographically indicated tea product from Yunnan, China, is renowned for its unique flavor profile shaped by intricate chemical compositions and complex processing techniques. This review systematically summarizes the material basis of Pu-erh tea flavor, focusing on key taste, sensation and aroma compounds such as tea polyphenols, alkaloids, amino acids, and volatiles. A major highlight of this review is its integration of molecular sensory science, detailing taste, sensation, and odor perception mechanisms mediated by key receptors. The interplay between flavor compounds is explored to decode the complexity of Pu-erh tea's flavor profile. The transformation pathways of these components during critical processing steps are elucidated, highlighting microbial succession and enzymatic reactions that drive the evolution of sensory attributes like bitterness, sweetness, and aged aroma. Advanced analytical methods, including quantitative descriptive analysis, electronic nose/tongue, and computational approaches like molecular docking, are discussed for their roles in bridging chemical data with flavor perception. Despite advancements, challenges remain, such as clarifying the molecular basis of sweet aftertaste and optimizing numerically controlled fermentation. This review provides a multidisciplinary framework for future research, emphasizing the convergence of metabolomics, sensory neuroscience, and artificial intelligence to advance Pu-erh tea flavor science.

From Sustainable Protein to Advanced Biomaterials: Structural and Functional Innovations of Filamentous Fungi in Food Systems March 14, 2026

Global food systems are increasingly challenged by food loss, waste, and the underutilization of nutrient-rich processing byproducts. Filamentous fungi, owing to their metabolic versatility, can efficiently convert complex substrates into protein-rich biomass while developing branched mycelial networks that provide natural structural frameworks with great potential for food and material functionalization. This review systematically summarizes the biological characteristics and taxonomy of filamentous fungi, their nutritional value as sustainable protein sources, and their applications in food structuring and functional material development. Special emphasis is placed on the integration of 3D printing with fungal growth, which enhances the formation and functionality of mycelial networks. By coupling fungal growth with advanced manufacturing technologies, new opportunities emerge for constructing circular and sustainable food systems that maximize resource utilization. Filamentous fungi thus serve not only as renewable protein sources but also as natural scaffolds for fabricating structured foods and biofunctional materials. These strategies collectively promote innovation in food design and material science while addressing global challenges in nutrition, resource efficiency, and environmental sustainability.

Application of Peracetic Acid in Poultry Processing: Effects of Treatment Dynamics and Emerging Risk of Resistance Development in Salmonella spp. March 14, 2026

Nontyphoidal Salmonella is a leading cause of foodborne illness, with poultry representing a major source. Peracetic acid (PAA), a widely adopted antimicrobial in poultry processing, offers advantages over traditional disinfectants but has sparked interest in its combined use with other antimicrobials and potential resistance. This review evaluates the efficacy of PAA in mitigating Salmonella in combination with other food-grade antimicrobials, explores possible synergism, efficacy under varying treatment parameters, resistance development against PAA, and its role in resistance evolution. While PAA demonstrates broad-spectrum efficacy, its performance varies with environmental parameters; higher temperatures generally enhance antimicrobial action but also accelerate PAA degradation. Organic matter diminishes PAA efficacy by reactive quenching. Variability in concentration and contact time further influences outcomes. Despite its oxidative mode of action and presumed low risk for resistance, emerging studies indicate that Salmonella can develop adaptive tolerance and potential cross/coresistance following repeated or sublethal exposure to PAA. These adaptations may involve genetic upregulation of oxidative stress response pathways, efflux systems, and modifications in cell membrane integrity, raising concerns about the long-term sustainability of PAA use. Additionally, combinatorial treatments (e.g., PAA with UV-C, enzymes, or organic acids) show promise in enhancing efficacy while mitigating resistance risks. Despite recognition of PAA's safety and effectiveness, knowledge gaps remain regarding standardized resistance definitions, serotype-specific tolerance, and optimal intervention strategies in commercial settings. Therefore, there is a need for standardized testing protocols, robust studies on potential resistance, and further exploration of synergistic PAA applications to ensure sustained poultry product safety and public health protection.

Artificial Intelligence in Food Safety: A Tertiary Study March 14, 2026

Food safety remains a critical factor in preventing contaminated and hazardous products from reaching consumers. The integration of artificial intelligence (AI) and its capacity to deal with vast datasets has significantly enhanced food safety protocols, and a substantial number of primary and secondary studies have emerged at the intersection of these two domains. Although several studies have addressed AI applications in food safety, no tertiary study has yet synthesized the collective insights from existing systematic reviews. To address this gap, this paper provides a comprehensive overview of the current state of AI applications in food safety through a systematic tertiary analysis of secondary studies. By systematically analyzing secondary studies, this research identifies key trends such as the food categories most frequently investigated, the data sources utilized, prevalent food safety hazards, the commonly adopted AI algorithms, and the challenges associated with their implementation within the field. The analysis revealed that dairy products received the greatest research attention, with sensing data serving as the primary data source. Neural networks emerged as the predominant AI approach. Furthermore, most applications focused on the detection of chemical food safety hazards rather than biological, physical, or general predictive modeling. Notably, this study highlights a lack of AI algorithms utilizing unstructured data, despite its growing relevance in the era of generative AI. Accordingly, future research directions are discussed, particularly the transformative potential of large language models (LLMs) in food safety monitoring and regulatory compliance.

EP 76: Deconstructing America’s New Dietary Guidance, Unlocking Sustainable Fat Innovation February 23, 2026

Experts unpack the new U.S. Dietary Guidelines and explore how animal-free fats are advancing next-generation plant-based food innovation.

SciDish February 2026: What post-GLP-1 eating means for food innovation February 16, 2026

In this SciDish episode, experts explore how GLP-1 use is changing appetite and eating patterns—and what it means for food innovation and nutrition design.

EP 75: GLP-1 Trend Gets Hotter, Rethinking UPF Myths and Mechanisms January 27, 2026

Learn how GLP-1 medications are transforming consumer food choices and what the latest science on ultra-processed foods means for CPG innovation.

Omnivore Presents: SciDish | January 2026: Consumer Trends Sparking Food Innovation January 19, 2026

Consumer trend trackers Jenny Zegler of Mintel and Michael Howard of Nichefire set the stage for the year ahead, sharing their takes on the trends that will have the greatest impact on product development and food innovation.

EP 74: Riding the AI Wave, Legacy Brands Product Innovation, MAHA at IFT FIRST December 15, 2025

Get the latest insights from the food science and technology community in the December 2025 episodes of the Omnivore podcast.