Search Results (974)

The increasing demand for plant-based foods has led to significant growth in the availability, at a retail level, of plant-based cheese analogue products. This study presents the first comprehensive benchmarking of commercially available plant-based cheese analogue (PBCA) products in the Irish market, comparing them against conventional cheddar and processed dairy cheeses. A total of 16 cheese products were selected from Irish retail outlets, comprising five block-style plant-based analogues, seven slice-style analogues, two cheddar samples, and two processed cheese samples. Results showed that plant-based cheese analogues had significantly lower protein content (0.1–1.7 g/100 g) than cheddar (25 g/100 g) and processed cheese (12.9–18.2 g/100 g) and lacked a continuous protein matrix, being instead stabilized largely by solid fats, starch, and hydrocolloids. While cheddar showed the highest hardness, some plant-based cheeses achieved comparable hardness using texturizing agents but still demonstrated lower tan δ_max values, indicating inferior melting behaviour. Thermograms of differential scanning calorimetry presented a consistent single peak at ~20 °C across most vegan-based variants, unlike the dual-phase melting transitions observed in dairy cheeses. Sensory analysis further highlighted strong negative associations between PBCAs and consumer-relevant attributes such as flavour, texture, and overall acceptability. By integrating structural, functional, and sensory findings, this study identifies key formulation and performance deficits across cheese formats and provides direction for targeted improvements in next-generation PBCA product development. Full article

Antimicrobial Resistance (AMR), i.e., the evolution of microbes to become resistant to chemicals used to control them, is a global public health concern that can make bacterial diseases untreatable. Inputs including antibiotics, metals, and biocides can create an environment in the agrifood chain that selects for AMR. Consumption of food represents a potential exposure route to AMR microbes and AMR genes (ARGs), which may be present in viable bacteria or on free DNA. Ready-to-eat (RTE) foods are of particular interest because they are eaten without further cooking, so AMR bacteria or ARGs that are present may be consumed intact. They also represent varied production systems (fresh produce, cooked meat, dairy, etc.). An evidence gap exists regarding the diversity and consumption of ARGs in RTE food, which this study begins to address. We sampled 1001 RTE products at retail sale in the UK, in proportion to their consumption by the UK population, using National Diet and Nutrition Survey data. Bacterial DNA content of sample extracts was assessed by 16S metabarcoding, and 256 samples were selected for metagenomic sequencing for identification of ARGs based on consumption and likely bacterial DNA content. A total of 477 unique ARGs were identified in the samples, including ARGs that may be involved in resistance to important antibiotics, such as colistin, fluoroquinolones, and carbapenems, although phenotypic AMR was not measured. Based on the incidence of ARGs in food types, ARGs are estimated to be present in a high proportion of average diets. ARGs were detected on almost all RTE food types tested (48 of 52), and some efflux pump genes are consumed in 97% of UK diets. Full article

Objective: To explore the relationship between type of grocery store used (chain vs. independent), transportation access, food insecurity, and fruit and vegetable intake in Detroit, Michigan, USA, during the COVID-19 pandemic. Design: A cross-sectional online survey was conducted from December 2021 to May 2022. Setting: Detroit, Michigan. Participants: 656 Detroit residents aged 18 and older. Results: Bivariate analyses showed that chain grocery store shoppers reported significantly greater fruit and vegetable intake (2.42 vs. 2.14 times/day for independent grocery store shoppers, p < 0.001) and lower rates of food insecurity compared to independent store shoppers (45.9% vs. 65.3% for independent grocery store shoppers, p < 0.001). Fewer independent store shoppers used their own vehicle (52.9% vs. 76.2% for chain store shoppers, p < 0.001). After adjusting for socioeconomic and demographic variables transportation access was strongly associated with increased odds of shopping at chain stores (OR = 1.89, 95% CI [1.21,2.95], p = 0.005) but food insecurity was no longer associated with grocery store type. Shopping at chain grocery stores was associated with higher fruit and vegetable intake after adjusting for covariates (1.18 times more per day, p = 0.042). Qualitative responses highlighted systemic barriers, including poor food quality, high costs, and limited transportation options, exacerbating food access inequities. Conclusions: These disparities underscore the need for targeted interventions to improve transportation options and support food security in vulnerable populations, particularly in urban areas like Detroit. Addressing these structural challenges is essential for reducing food insecurity and promoting equitable access to nutritious foods. Full article

Japan’s 8.5 million vacant homes (Akiyas) represent a paradox of scarcity amid surplus: while rural depopulation leaves properties abandoned, housing shortages and bureaucratic inefficiencies hinder their reuse. This study proposes AKI2ALL, an AI-blockchain framework designed to automate the circular repurposing of Akiyas into ten high-value community assets—guesthouses, co-working spaces, pop-up retail and logistics hubs, urban farming hubs, disaster relief housing, parking lots, elderly daycare centers, exhibition spaces, places for food and beverages, and company offices—through smart contracts and data-driven workflows. By integrating circular economy principles with decentralized technology, AKI2ALL streamlines property transitions, tax validation, and administrative processes, reducing operational costs while preserving embodied carbon in existing structures. Municipalities list properties, owners select uses, and AI optimizes assignments based on real-time demand. This work bridges gaps in digital construction governance, proving that automating trust and accountability can transform systemic inefficiencies into opportunities for community-led, low-carbon regeneration, highlighting its potential as a scalable model for global vacant property reuse. Full article

Biogenic amines (BA) are simple organic bases of low molecular weight, formed during decarboxylation of amino acids. Ripened cheeses provide suitable conditions for the development of bacteria and production of BAs. The aim of the present study was to investigate the presence of eight BAs in ripened cheese samples (n = 125) using a high-performance liquid chromatography with diode array detector (HPLC-DAD). Furthermore, microbiological analyses towards identification of bacteria using matrix-assisted laser desorption ionisation—time of flight mass spectrometry (MALDI-TOF MS) were performed. Cadaverine and putrescine were detected in 28.0% and 20.8% of cheese samples at concentrations ranging from 6.12 to 2871 mg/kg and 5.74 to 441 mg/kg, respectively. High amounts of putrescine and cadaverine in cheeses were associated with the presence of Hafnia alvei. Tyramine was identified in 28.0% of samples in the concentration range of 5.62–646 mg/kg. High concentrations of this amine was found in cheeses containing Enterococcus faecium and Enterococcus faecalis. Histamine content, the only BA restricted in food according to Regulation 2073/2005, was observed above 100 mg/kg in 11.2% of the cheeses. Ripened cheeses available on the local retail market may contain significant levels of biogenic amines and may pose a potential health hazard to consumers. Full article

Food not only fulfills basic human survival needs but also significantly impacts health and culture. Research on food-related topics holds substantial theoretical and practical significance, with food image recognition being a core task in fine-grained image recognition. This field has broad applications and promising prospects in smart dining, intelligent healthcare, and smart retail. With the rapid advancement of artificial intelligence, deep learning has emerged as a key technology that enhances recognition efficiency and accuracy, enabling more practical applications. This paper comprehensively reviews the techniques and challenges of deep learning in food image recognition. First, we outline the historical development of food image recognition technologies, categorizing the primary methods into manual feature extraction-based and deep learning-based approaches. Next, we systematically organize existing food image datasets and summarize the characteristics of several representative datasets. Additionally, we analyze typical deep learning models and their performance on different datasets. Finally, we discuss the practical applications of food image recognition in calorie estimation and food safety, identify current research challenges, and propose future research directions. Full article

The COVID-19 pandemic had significant global impacts. In Japan, consumers refrained from going out, and dining out decreased significantly, which strongly affected the restaurant industry and resulted in a shift in food demand from eating out to home consumption. The seafood industry is no exception to this trend. This study surveyed 300 individuals with experience in seafood transactions across wholesalers, restaurants, and retailers to examine how the pandemic influenced supply and demand patterns from a distribution perspective. Results indicated that while the volume of luxury seafood handled by restaurants and wholesalers decreased, the volume handled by retailers increased. Conversely, the volume of inexpensive popular seafood declined across all three sectors. The findings suggest that some of the luxury seafood previously sold to restaurants was redirected to retailers as consumer demand shifted from dining out to home consumption during the pandemic. Full article

Escherichia coli (E. coli) remains a major concern in poultry production due to its ability to incite foodborne illness and public health crisis, zoonotic potential, and the increasing prevalence of antibiotic-resistant strains. The contamination of poultry products with pathogenic E. coli, including avian pathogenic E. coli (APEC) and Shiga toxin-producing E. coli (STEC), presents risks at multiple stages of the poultry production cycle. The stages affected by E. coli range from, but are not limited to, the hatcheries to grow-out operations, slaughterhouses, and retail markets. While traditional detection methods such as culture-based assays and polymerase chain reaction (PCR) are well-established for E. coli detection in the food supply chain, their time, cost, and high infrastructure demands limit their suitability for rapid and field-based surveillance—hindering the ability for effective cessation and handling of outbreaks. Biosensors have emerged as powerful diagnostic tools that offer rapid, sensitive, and cost-effective alternatives for E. coli detection across various stages of poultry development and processing where detection is needed. This review examines current biosensor technologies designed to detect bacterial biomarkers, toxins, antibiotic resistance genes, and host immune response indicators for E. coli. Emphasis is placed on field-deployable and point-of-care (POC) platforms capable of integrating into poultry production environments. In addition to enhancing early pathogen detection, biosensors support antimicrobial resistance monitoring, facilitate integration into Hazard Analysis Critical Control Points (HACCP) systems, and align with the One Health framework by improving both animal and public health outcomes. Their strategic implementation in slaughterhouse quality control and marketplace testing can significantly reduce contamination risk and strengthen traceability in the poultry value chain. As biosensor technology continues to evolve, its application in E. coli surveillance is poised to play a transformative role in sustainable poultry production and global food safety. Full article

Minced lamb remains one of the most produced meat products in the meat industry, across both the food service and retail sectors. Tea polyphenols (TPs), renowned for their diverse biological activities, are increasingly being employed as natural food additives in research and development. Tea polyphenols at concentrations of 0.00% (CG), 0.01% (TP1), 0.10% (TP2), and 0.30% (TP3) were added to lamb which had undergone a series of freeze–thaw cycles. The presence of tea polyphenols led to a significant decrease in the number of disulfide bonds, resulting in a slower oxidation rate. In addition, the surface hydrophobicity and juice loss of the minced lamb supplemented with tea polyphenols were 91.23 ± 0.22 and 20.00 ± 0.46, respectively, representing a reduction of 1.5% and 7.59% compared to the group without the addition of tea polyphenols. However, the addition of high-dose tea polyphenols also led to a reduction in emulsification stability, alterations in protein conformation, and changes in water migration. Furthermore, the incorporation of a minimal quantity of tea polyphenols (0.01%) resulted in enhanced emulsification stability, water retention, textural properties, and microstructures in minced lamb. This suggests that tea polyphenols have the potential to improve the quality of minced lamb following freezing and thawing processes. Full article

Carsharing has long supported trip purposes typically made by private vehicles, with grocery shopping especially benefiting from the carrying capacity of a personal vehicle. BlueLA is a one-way, station-based electric vehicle (EV) carsharing service in Los Angeles aimed at improving access in low-income neighborhoods. We hypothesize that BlueLA improves grocery access for underserved households by increasing their spatial-temporal reach to diverse grocery store types. We test two hypotheses: (1) accessibility from BlueLA stations to grocery stores varies by store type, traffic conditions, and departure times; and (2) Standard (general population) and Community (low-income) members differ in perceived grocery access and station usage. Using a mixed-methods approach, we integrate walking and driving isochrones, store data (n = 5888), trip activity data (n = 59,112), and survey responses (n = 215). Grocery shopping was a key trip purpose, with 69% of Community and 61% of Standard members reporting this use. Late-night grocery access is mostly limited to convenience stores, while roundtrips to full-service stores range from 55 to 100 min and cost USD 12 to USD 20. Survey data show that 84% of Community and 71% of Standard members reported improved grocery access. The findings highlight the importance of trip timing and the potential for carsharing and retail strategies to improve food access. Full article

Staphylococcus aureus is an important cause of food intoxication, which has the potential to induce diverse infections, toxinoses and life-threatening diseases among humans and animals. This study investigated the prevalence, antimicrobial resistance, and genetic diversity of S. aureus and methicillin-resistant S. aureus (MRSA) in retail raw meat from Shandong (March 2021–October 2022). The distribution of virulence genes, antimicrobial susceptibility, and genetic diversity of these isolates were analyzed. From a total of 442 samples, 87 (19.7%) S. aureus and 11 (2.5%) MRSA were isolated. According to the antimicrobial susceptibility testing, it was found that all the S. aureus isolates were resistant to at least one antimicrobial. Most isolates (95.9%) were resistant to penicillin, with high resistance to ampicillin (82.7%) and multidrug resistance in 76.5% of cases. One isolate could simultaneously resist eleven antimicrobials (ERY-CLI-GEN-SMZ-FFC-PEN-PRL-AMC-CIP-TET-AMP). In contrast, all the isolates showed sensitivity to vancomycin. The most prevalent virulence gene was sed, accounting for 10.2%, followed by sec (8.2%). Regarding genetic polymorphism, these isolates were divided into 21 different sequence types (STs) using multilocus sequence typing (MLST) and 33 staphylococcal protein A (spa) types using spaTyper 1.0 tool. The most prevalent sequence types were ST398 (22.4%), followed by ST7 (20.4%), while ST59, ST1, ST188, ST9, ST398, and ST7 were observed in MRSA isolates. The most prevalent spa types were t034 (15.3%), followed by t899 (10.2%), while t441, t127, t184, t899, t034, and t091 were observed in MRSA isolates. In conclusion, our study highlights the high prevalence of S. aureus and MRSA in different retail raw meats in Shandong. This poses a potential threat to food safety and underscores the need for enhanced surveillance and stricter antibiotic control measures. Full article

Wine production is an important sector of the food industry in Bulgaria, contributing to both economic development and cultural heritage. The present study aims to show how natural language processing (NLP) and machine learning methods can be applied to analyze expert-written Bulgarian wine descriptions and to extract patterns related to wine quality and style. Based on a bilingual dataset of reviews (in Bulgarian and English), semantic analysis, classification, regression and clustering models were used, which combine textual and structured data. The descriptions were transformed into numerical representations using a pre-trained language model (BERT), after which algorithms were used to predict style categories and ratings. Additional sentiment and segmentation analyses revealed differences between wine types, and clustering identified thematic structures in the expert language. The comparison between predefined styles and automatically derived clusters was evaluated using metrics such as Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI). The resulting analysis shows that text descriptions contain valuable information that allows for automated wine profiling. These findings can be applied by a wide range of stakeholders—researchers, producers, retailers, and marketing specialists. Full article

Objective: The objective of this article was to perform a comparative analysis of the changes in the availability of commercial food establishments around the schools in a Brazilian capital city. Methods: This is a comparative analysis between two cross-sectional panels performed in 2012 and 2019 in Florianópolis, Santa Catarina, Brazil. Secondary data from different sources were used. The location data of schools and establishments were georeferenced. For the analysis of the surroundings of schools, a network buffer of 800 m was considered. The establishments were classified based on the foods they primarily sold: fresh, mixed and ultra-processed foods. The chi-square and Wilcoxon tests were applied for the analyses, considering a significance level of 95% (p < 0.05). Results: The number of food establishments around schools increased by 63%. There was a statistically significant growth in mixed (p = 0.008) and ultra-processed (p = 0.024) food- selling establishments. Conclusion: We conclude that the increase in establishments selling ultra-processed foods around schools at the expense of establishments selling fresh food deserves attention. This condition requires public policies that help promote healthier environments, thus contributing to the health of schoolchildren. Full article

Food contact polymers require thermochromic pigments to provide temperature-sensitive visual cues for consumer safety and product integrity. However, their susceptibility to ultraviolet (UV) degradation limits long-term application. This study investigates the UV resistance of food-grade thermochromic polypropylene blends under simulated indoor and outdoor UV exposure for 500 and 1000 h. Visual properties, colorimetric (CIE L*a*b*) measurements, mechanical testing (tensile and impact), and mass variation analysis were performed to assess photostability and material integrity. Exposure to UV led to progressive discoloration (ΔE*_ab up to 34.07) and significant mechanical deterioration. Tensile strain at break decreased by 48.67%, and notched impact strength dropped by 44.15% after 1000 h of UV exposure. No measurable mass loss occurred, indicating degradation was confined to surface-level oxidation rather than bulk material erosion or leaching. These findings highlight the need for optimal pigment loading and UV stabilization to extend the shelf life of thermochromic food packaging materials in light-exposed storage and retail environments. The study offers a framework for improving the long-term reliability of smart packaging in the food industry. This work uniquely integrates optical, mechanical, and mass loss analyses to evaluate thermochromic packaging degradation under extended UVA exposure. Full article

With the improvement of living standards, consumer demand for fresh produce has witnessed a remarkable upsurge. Fresh products present significant preservation challenges, as their freshness directly correlates with sales performance and ultimately impacts the sustainable development of the fresh supply chain. Enhancing freshness preservation standards, boosting market demand, strengthening brand reputation, and promoting the development of a fresh supply chain are urgent problems that need to be solved. This paper delves into the dynamic optimal decision-making processes within a fresh food supply chain, which is composed of a supplier and a retailer, under different government subsidy scenarios: centralized decision-making, decentralized decision-making under supplier myopia, and decentralized decision-making under supplier’s foresight. Herein, a differential game model is constructed, and through the utilization of dynamic optimization and backward induction techniques, feedback strategies for various decision-making paradigms are derived. A comparative evaluation of decision-making models is conducted, grounded in theoretical frameworks and substantiated through numerical simulations, to assess critical parameter impacts. The results indicate the following: (1) the effect coefficients of consumer preference and preservation efforts show significant positive correlations with suppliers’ preservation strategies and retailers’ promotional tactics, respectively; (2) supply chain profitability reaches its Pareto-optimal state under centralized decision-making structures, while myopic supplier behavior leads to systematically lower profits than foresighted supplier strategies; (3) retailers demonstrate stronger collaboration preferences toward foresighted suppliers, as such partnerships ensure enhanced quality consistency and supply continuity; and (4) government agencies should implement dynamically adjusted subsidy schemes during preservation initiatives to facilitate sustainable operational frameworks in fresh produce supply chains. Full article