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PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗

PubMed2026

The combined and independent influence of food texture and a 'mindful eating' instruction on eating rate and food intake among Dutch primary schoolchildren.

Eating rate (ER), the amount of food consumed per unit of time, is a key determinant of food intake, with faster ER associated with larger meal size. Research in adults has shown that both sensory properties like texture, and instructions can influence ER and intake. However, their independent and combined effect on ER and intake in children remain poorly understood. This study examined the effects of food texture and a 'mindful eating' instruction on ER and food intake in children. Children (N = 73), 38 boys, aged 4-12 years, participated in a 4-week cluster-randomized incomplete cross-over study conducted during regular school lunches. Using a 2×3 factorial design, children were exposed to two levels of food texture (softer vs. harder whole-grain buns) and three types of instructions (none, control, 'mindful'). Linear mixed models with repeated measures were used, adjusting for sex and group. As the interaction between food-texture and type of instructions was non-significant, it was excluded from the final models. Results revealed a strong main effect of food texture on ER and food intake (all p < 0.001), where compared with softer buns, harder buns were associated with a slower eating rate (Δ = -6.67 g/min, SE = 0.59) and reduced food intake (Δ = -70 g, SE = 8). In contrast, type of instruction had no significant effect on ER or intake (p = 0.85). Our findings demonstrate that food texture exerts a dominant influence on children's eating rate and food intake, highlighting texture modification as a potential leverage point for influencing ER and intake in children.

Humans↗

PubMed2026

Innovations in microbial physical mutagenesis for food fermentation: An overview from traditional to emerging technologies.

Microbial strains serve as an important factor affecting fermentation efficiency and product quality. To obtain superior strains, mutation breeding is a classic strategy. Compared to chemical mutagenesis, physical mutagenesis directly induces genomic changes, providing notable advantages such as the elimination of chemical residues and environmental sustainability, hence rendering it a favored method for enhancing food-grade microorganisms. Conventional physical mutagenesis mostly depends on UV, rays, high pressure, or space radiation. As physical technologies advance, emerging methods such as ion implantation, plasma, microwave, ultrasound, and pulsed light are widely utilized for genetic modification. Mutagenesis technologies are progressively transitioning from single-effect to multi-effect synergy. Recent evaluations indicate that emerging technologies can enhance microbial mutation efficiency at the application level relative to established technologies. Nonetheless, the systematic clarification and comparative analysis at the mechanistic level remain inadequate, hindering intuitive comprehension of the qualities and distinctions across techniques. Furthermore, physical mutagenesis encounters several significant obstacles, such as cellular damage, limited rates of advantageous mutations, and laborious screening processes. This review carefully elucidates the mechanisms and properties of physical mutagenesis technology and delineates the distinctions among approaches through comparative analysis. Simultaneously, solutions for optimizing mutagenesis are presented to tackle the principal challenges mentioned above. This review aims to offer a theoretical foundation and practical guidance for the enhanced application of physical mutagenesis technologies in microbial breeding.

Mutagenesis↗

PubMed2026

Critical insights on the application of the theory of planned behaviour to food handlers' food safety practices.

Foodborne diseases remain a significant public health concern, often linked to unsafe food-handling practices. The Theory of Planned Behaviour (TPB) is widely used to predict and explain food safety behaviours, yet its application in this field has not been systematically and in-depth evaluated. This review evaluated how the TPB has been applied to study food handlers' behaviour, focusing on methodological approaches, use of the TACT (Target, Action, Context, and Time) framework, validity, elicitation studies, and reliability. Seventeen studies were included following a systematic search of four databases (Scopus, Web of Science, Wiley Online Library, and Taylor & Francis Online). Data were extracted on behaviour definition, aim of study, main findings, use of indirect and direct TPB measures, use of elicitation studies, internal consistency, content validation, analytical methods used, and any extensions to the original TPB framework. Key elements related to adherence to core TPB principles and measurement practices were extracted using a Checklist. Most studies used direct measures of TPB constructs, and only a few reported procedures for content validation. Considerable variability was found in the reporting of key measurement and psychometric practices. Five studies fully applied the TACT framework, while nine incorporated additional factors such as knowledge and moral norms. Elicitation studies were conducted in five cases where indirect measures were employed. Analytical approaches were mainly based on multiple linear regression, with limited use of more advanced techniques such as structural equation modeling. Twelve studies reported internal consistency results. Overall, the review highlights opportunities to strengthen methodological practices in future TPB research on food safety. Greater attention to conducting and reporting content validation, full application of the TACT framework, reporting of internal consistency, and consistent inclusion of elicitation studies when using indirect measures may enhance transparency, reinforcing the credibility and trustworthiness of research findings. A major methodological limitation of this review was that screening and data extraction were conducted by a single reviewer and no formal quality or risk-of-bias assessment of the included studies was performed. Despite these limitations, the findings provide practical guidance for the development and validation of TPB-based questionnaires and may support more robust food safety research, interventions, and policy initiatives aimed at improving food handlers' practices.

Humans↗

PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Applications of metal-organic frameworks in smart packaging for food freshness indication: a comprehensive review.

Smart packaging is extensively studied for its multifunctional capabilities in antimicrobial activity, preservation, and atmosphere modification. Recently emerged metal-organic frameworks (MOFs) freshness-indicating packaging becomes a key research direction in smart packaging owing to its distinctive functions and physicochemical properties. As multifunctional materials, the unique porous structure and tunable properties of MOFs provide a distinctive approach for developing food packaging applications dedicated to food freshness indication. Existing MOFs-based smart packaging still faces potential safety risks and technical challenges in practical applications, and there remains a lack of integrated discussion that combines synthesis strategies, packaging design, optimization, and safety assessment. This review elaborates on the application of MOFs in freshness-indicating smart packaging, focusing on diverse MOFs synthesis strategies, the formats of smart packaging, types of indicator signals, and qualitative/quantitative analytical methods. It also delves into the methodology concepts of MOFs-based smart packaging and evaluates MOFs safety in food packaging by addressing potential risks. Studies show that MOFs-based smart packaging achieves qualitative and semi-quantitative analysis of food freshness through multiple signal modalities such as visible color change, fluorescence, and photothermal effects. This review emphasizes that safe MOFs design is critically important and should comply with the overall migration limit of <10 mg/dm2 specified in Regulation (EC) No 1935/2004, lanthanide element limit of <0.05 mg/kg, and FDA threshold of 1.5 μg/person/day. Comprehensive safety assessment and intelligent sensing platforms will constitute pivotal directions for advancing MOFs-based smart packaging toward practical application.

Food Packaging↗

PubMed2026

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU·mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays↗

PubMed2026

Herbicolin A, an antifungal lipopeptide produced by Pantoea agglomerans APC 4211 is a promising biocontrol agent against food spoilage fungi.

Fungal contamination of food with yeast and molds is associated with major economic losses due to spoilage and also poses health risks in the form of mycotoxin production. The strain Pantoea agglomerans APC 4211 isolated from leaves of Ilex aquifolium (holly tree) has broad spectrum antifungal activity against a variety of food spoilage fungi. Genomic analysis of the strain confirmed the presence of biosynthetic gene clusters potentially encoding for the enzymatic machinery required for the production of the antifungal lipopeptide herbicolin A. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of the cell-free supernatant (CFS) confirmed the presence of molecular masses corresponding to herbicolin A (1300.8 Da), and herbicolin B (1138 Da). Purified herbicolin A has desirable properties for biotechnological applications, including potent antifungal activity against a range of spoilage fungi, thermal stability and resistance to proteases. The lipopeptide has low cytotoxicity against epithelial cell lines and has minimum inhibitory concentrations (MICs) lower than those of some commercial antifungal drugs (0.2-2.5 mg/L). In a model dairy system (10% skim milk), herbicolin A demonstrated excellent solubility and stability, effectively eliminating Aspergillus niger and Penicillium notatum at a concentration of 5 mg/L. Overall, the study determines herbicolin's A spectrum against food spoilage organisms and examines potential applications in food. In conclusion, herbicolin A is a potent, naturally occurring antifungal agent with the potential to be applied as a biopreservative in food systems, providing a safe, clean-label, and efficient compound for synthetic preservatives replacement.

Pantoea↗

PubMed2026

Health bill beneath the plastic feast: A phthalate contamination alert from takeout food containers.

The rapid growth of takeout food consumption in China has raised concerns regarding exposure to phthalic acid esters (PAEs) from food packaging. This study investigated the presence, source, contribution, and health risk of PAEs in commonly used takeout containers. Widespread contamination was observed, with total PAE concentrations ranging from below the limit of detection to 222,000 ng/g. Diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), and bis(2-ethylhexyl) phthalate (DEHP) were identified as the predominant compounds, accounting for 7.50 %, 14.7 %, and 18.7 % of the total concentration, respectively. These PAEs may originated from additives during manufacturing and potential contamination of raw materials. Human exposure assessment showed that daily exposure doses of DIBP, DBP, and DEHP via container ranged from 0.00 to 2340 ng/(kg·day) among frequent takeout consumers, contributing substantially to overall PAE body burdens. To further assess exposure and associated risks, a nationwide online questionnaire survey was conducted across China. Based on this national-scale behavioral dataset, the health risks among Chinese residents were evaluated. Although the modeled non-carcinogenic risks of DIBP, DBP, and DEHP remained within acceptable limits, the simulation suggested that approximately 70 % of participants may experience potential exceedance of the carcinogenic risk threshold for DEHP. The frequency of takeout food consumption was identified as the most important factor affecting PAE exposure. These findings underscore the importance of limiting takeout frequency and reducing reliance on plastic containers to mitigate health risks. This study provides scientific evidence to support the development of safer packaging materials and informs public health strategies.

Phthalic Acids↗

PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

Water intake, switching between bites and sips, and drinking behavior are associated with food intake across meals varying in spiciness: A secondary analysis of two randomized crossover studies.

Widespread nutrition advice instructs consumers to drink water with meals to increase fullness and reduce energy intake. However, recent data indicates greater water intake is associated with more food intake at a meal, not less. Switching between meal components (e.g., alternating between food and water), has also been associated with increased food intake at a pasta meal, but it remains unclear whether this applies to other foods. In a secondary analysis, we pooled existing data from 2 crossover experiments (total n = 86) where adults ate an ad libitum lunch consisting of 650 g of beef chili (n = 52) or chicken tikka masala (n = 34) with 450 g of water twice in the laboratory while being video-recorded. For both experiments, the spiciness of the lunch was varied by adding different ratios of hot:sweet paprika. Videos were coded to measure sip number, sip size (g/sip), drinking rate (g/min), and number of switches between bites of food and sips of water. As we previously reported, increasing spiciness slowed eating rate and reduced food intake; in secondary analyses described here, the reduction in food intake was not moderated by water intake, switching, or drinking behaviors (all p > 0.73). Notably, across all meals, greater water intake (p < 0.001) and switching (p = 0.02) associated with greater food intake. Overall, individuals ate more when they drank more and switched between bites and sips more often, highlighting the potential influence of water and drinking behaviors on food consumption. This finding challenges the widespread dietary advice to drink water with meals to reduce food intake.

Humans↗

PubMed2026

Ecological momentary assessment studies on food craving among healthy adults: A systematic review.

Ecological Momentary Assessment (EMA) can capture the dynamic nature of food craving in free-living conditions, addressing limitations of laboratory and retrospective reporting methods. This systematic review synthesized findings from EMA studies to characterize 1) methodological features, 2) the temporal dynamics of food craving, and 3) the relationship between craving and eating behaviors. A systematic search of PubMed and PsycINFO databases was conducted following PRISMA guidelines. The review included 23 studies that utilized EMA designs to assess food craving repeatedly in daily life among healthy adults. Most studies employed EMA protocols that prompted participants to respond at pre-specified time points and utilized single-item craving measures. Most craving measures (71%) lacked specificity regarding the type of food craved. Results revealed a consistent positive within-person association between hunger and food craving. Conversely, associations between stress/negative affect and craving were inconsistent, varying by individual traits and context. Momentary food craving appeared to predict subsequent eating outcomes. Evidence suggested food craving may be a dynamic, transient state that co-fluctuates with hunger, functioning as a proximal antecedent to food intake. However, reliance on non-specific food craving measures and EMA protocols prompting at fixed schedules limits the granular understanding of craving mechanisms. Future research requires refining food craving measurement and incorporating randomized prompting within predefined windows, or participant-initiated sampling triggered by specific events (e.g., eating occasion), to better characterize food craving dynamics in relation to eating behaviors.

Humans↗

PubMed2026

Microbial diversity, functional activities, and safety risks in fermented tea: a comprehensive review.

Microbial fermented teas are gaining global popularity due to their unique sensory profiles and health benefits. The quality and safety of these products are governed by complex microbial ecosystems that orchestrate the biotransformation of tea leaf components. This review addresses a critical paradox in the field: the same microbial activities that generate desirable bioactive metabolites, such as theabrownins and organic acids, also create ecological niches for mycotoxigenic fungi, posing significant health risks from contaminants like ochratoxin A, citrinin, and aflatoxins. While extensive research has cataloged the microbial diversity in these systems, a comprehensive framework linking processing environments to microbial community assembly, functional outcomes, and quantifiable safety risks remains elusive. This review systematically bridges this gap by synthesizing current knowledge on the microbial consortia-dominated by Aspergillus, Penicillium, Bacillus, and Lactiplantibacillus species-that drive tea fermentation. We critically analyze their functional roles in enhancing flavor, bioactivity, and potential probiotic activity while simultaneously evaluating the mechanisms of mycotoxin production and accumulation. By integrating microbial ecology, biochemistry, and food safety, we propose a forward-looking perspective focused on transitioning the industry from traditional, spontaneous fermentation to modern, controlled biotechnological processes. This approach, centered on the use of defined starter cultures, predictive modeling, and active biocontrol strategies, provides a roadmap for ensuring the consistent quality and safety of fermented tea products, ultimately unlocking their full potential as high-quality functional foods.

Tea↗

PubMed2026

Elucidation of microbial community structure, small-molecule metabolic and flavor profile characteristics in Xuanwei ham under different processing techniques.

This study systematically compared the impacts of traditional (TH) and modern (MH) processing techniques on the physicochemical properties, microbial community structure, metabolome, and volatile aroma compounds of Xuanwei ham. The results showed that the TH group had higher moisture content and water activity, along with a more tender texture, whereas the MH group exhibited greater hardness and chewiness. Microbiological analysis revealed that the interior of the MH group had higher species richness of both fungi and bacteria, while the TH group maintained higher fungal diversity. Metabolomic analysis identified 112 differential metabolites, with sweet amino acids and certain lipids being more enriched in modern ham, whereas traditional ham contained higher levels of umami amino acids, polyunsaturated fatty acids, and flavor compounds such as carnosine. KEGG pathway enrichment indicated that the differences were primarily concentrated in amino acid biosynthesis and metabolism-related pathways. Volatile flavoromics analysis identified 45 odor-active compounds and screened 15 key aroma-active substances. Among them, modern processed ham was significantly enriched in fatty aldehydes such as (E)-2-nonenal, hexanal, nonanal, and octanal, whereas traditional processed ham was characterized by 1-octen-3-ol, (E,E)-2,4-decadienal, methional, acetoin, and benzeneacetaldehyde. Correlation analysis confirmed that dominant microbes in Xuanwei ham were significantly associated with differential metabolites and characteristic aroma compounds, respectively. This study provides a scientific basis for standardizing production processes, enabling precise quality control, and promoting high-quality industrial development of Xuanwei ham.

Animals↗

PubMed2026

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide↗

PubMed2026

Alginate-based edible coating incorporating green tea extract for preserving postharvest quality and safety of white mushrooms (Agaricus bisporus).

This study aimed to evaluate the effects of a sodium alginate based edible coating incorporated with green tea extract (GTE) (Camellia sinensis) on the postharvest quality attributes and antimicrobial activity against Listeria monocytogenes in white mushrooms during refrigerated storage. The phenolic profile of GTE was characterized, and its minimum inhibitory concentration (MIC) against L. monocytogenes (1.6 mg/mL) was determined. Sodium alginate coatings, with (ALG-GTE) or without GTE (ALG) at MIC (1.6 mg/mL), were characterized (functional groups, solubility in water, moisture, thickness, water contact angle and color) for their chemical and physical properties. The effects of ALG-GTE coatings on quality parameters (firmness, weight loss, color, pH, sugars and organic acids), enzymatic activity [polyphenol oxidase (PPO), peroxidase (POD) and pectin methylesterase (PME)], antimicrobial activity against L. monocytogenes (5 log CFU/g), and surface characteristics (3D optical profilometry) were assessed in white mushrooms (Agaricus bisporus) during refrigerated storage (8 days, 4 ± 1 °C, 90-95% RH). The ALG-GTE coatings preserved sugar composition, particularly rhamnose, reduced organic acids accumulation and delayed weight and firmness loss, reduced color changes, and decreased PME activity in coated white mushrooms. L. monocytogenes counts decreased by 1.4 log CFU/g after 1 day, and no viable cells were detected after 2 days (< 1.5 log CFU/g) in ALG-GTE coated white mushrooms. In addition, ALG-GTE coated white mushrooms exhibited smoother surfaces than uncoated samples. These findings highlight the potential of ALG-GTE coatings as a sustainable alternative capable of improving the microbiological safety and delaying the postharvest changes in fresh mushrooms.

Agaricus↗

PubMed2026

Innovation-related perception as a key driver of alternative protein acceptance: evidence from an early-stage model for cultivated meat and algae-/microalgae-based alternative protein products in Italy.

Alternative proteins are increasingly considered part of the transition toward more sustainable food systems, yet their diffusion depends critically on consumer acceptance. This study investigates the early-stage acceptance of two alternative protein categories in Italy-cultivated meat and algae-/microalgae-based alternative protein products. Focusing on the first three phases of acceptance, the analysis examines how innovation-related perception (IRP) shapes consumer perceived value (CPV), consumer perceived risk (CPR), and subsequent affective (AFF), cognitive (COG), and conative (CON) responses. Data were collected through an online survey administered to 238 Italian respondents and analysed using partial least squares structural equation modelling (PLS-SEM). The results show that IRP is the main upstream driver of early-stage acceptance in both product domains: more favourable perceptions strongly increase perceived value and reduce perceived risk. In turn, CPV exerts a much stronger influence than CPR on both affective and cognitive attitudes. A tentative cross-model comparison suggests only a descriptive variation in the final transition toward conative acceptance: affective and cognitive responses were both significant in the two models, with a relatively larger affective coefficient for cultivated meat and more balanced coefficients for algae-/microalgae-based products. Overall, the findings support a process-based interpretation of alternative protein acceptance and highlight the central role of innovation-related perception in shaping early consumer responses. These results provide relevant implications for communication strategies, product positioning, and policy actions aimed at improving the acceptability of alternative proteins in food cultures characterised by strong culinary traditions.

Italy↗