Search Results (142)

Against the backdrop of heightened global economic uncertainty and increasingly frequent risks in agricultural supply chains, enhancing agricultural supply chain resilience has become a critical issue for safeguarding national food security and promoting high-quality agricultural development. As key actors within agricultural supply chains, the impact of financialization—defined as the shift of resources to non-core financial assets—among agricultural listed firms on supply chain resilience warrants systematic examination. Using panel data from 165 Chinese agricultural listed firms (2010–2022), this study empirically investigates the impact of corporate financialization on agricultural supply chain resilience and its underlying mechanisms. An entropy-weighted composite index based on 16 parameters is used to assess agricultural supply chain resilience. It is composed of three dimensions: resistance capability, recovery capacity, and renewal capacity. The results show that: Financialization significantly undermines supply chain resilience, with the most substantial negative effect on recovery capacity, followed by renewal capacity, and the weakest on resistance capacity. Heterogeneity analyses show more pronounced negative effects among non-state-owned enterprises, non-primary sector firms, and capital-intensive enterprises. Financing constraints and capital expenditures partially mediate the negative relationship between financialization and resilience, while profitability persistence exacerbates the crowding-out effect. These findings suggest that policymakers should strike a compromise between reducing excessive financialization and strengthening agricultural supply chains. While prudently guiding agricultural firms’ financial asset allocation, greater emphasis should be placed on developing a diverse and coordinated industrial support system, thereby diverting financial capital away from crowding out core operations and toward effectively serving the real economy, ultimately contributing to national food security and agricultural modernization. Full article

Background/Objectives: Chrononutrition—the temporal organization of food intake relative to circadian rhythms—has emerged as an important factor in cardiometabolic health. While meal timing is typically analyzed as an isolated variable, limited research has examined integrated meal timing patterns, and no study has systematically compared clustering approaches for their identification. This cross-sectional study compared four clustering techniques—traditional (K-means, Hierarchical) and non-traditional (Gaussian Mixture Models (GMM), Spectral)—to identify meal timing patterns from habitual breakfast, lunch, and dinner times. Methods: The sample included 388 Mexican university students (72.8% female). Patterns were characterized using sociodemographic, anthropometric, food intake quality, and chronotype data. Clustering method concordance was assessed via Adjusted Rand Index (ARI). Results: We identified five patterns (Early, Early–Intermediate, Late–Intermediate, Late, and Late with early breakfast). No differences were observed in BMI, waist circumference, or age among clusters. Chronotype aligned with patterns (morning types overrepresented in early clusters). Food intake quality differed significantly, with more early eaters showing healthy intake than late eaters. Concordance across clustering methods was moderate (mean ARI = 0.376), with the highest agreement between the traditional and non-traditional techniques (Hierarchical–Spectral = 0.485 and K-means-GMM = 0.408). Conclusions: These findings suggest that, while traditional and non-traditional clustering techniques did not identify identical patterns, they identified similar core structures, supporting complementary pattern detection across algorithmic families. These results highlight the importance of comparing multiple methods and transparently reporting clustering approaches in chrononutrition research. Future studies should generate meal timing patterns in university students from other contexts and investigate whether these patterns are associated with eating patterns and cardiometabolic outcomes. Full article

This study investigates heavy metal pollution in agricultural soils and its associated health risks in Zhenjiang and Yangzhou in the core of the Yangtze River Delta, China, based on high-density sampling at 449 sites. Although the total concentrations of As and Cd remain below national Risk Intervention Values (GB 15618-2018), the Cd level significantly exceeds the national background, and the potential ecological risk index (PERI) indicates very high ecological risk (>320) at 88.2% of sites, driven primarily by Hg and Cd. The results show acceptable non-carcinogenic risks (HI < 1) for adults and children, but carcinogenic risks are elevated: arsenic alone exceeds the 1 × 10⁻⁶ threshold in 71.7% of adult and 92.1% of child scenarios, with the total carcinogenic risk averaging 1.89 × 10⁻⁶ (adults) and 3.05 × 10⁻⁶ (children). These probabilistic findings justify stricter local action thresholds for As and Cd in this densely populated rice-producing region and demonstrate the value of Monte Carlo simulation for delivering transparent, population-specific risk exceedance probabilities to support evidence-based regional soil management and food-safety policies. Full article

Exploring the spatiotemporal patterns of cultivated land conversion to non-agricultural uses and their evolutionary driving mechanisms is of significant importance for regional cultivated land protection and food security. This study utilizes time-series land use datasets, DEM, meteorological data, and statistical yearbook data to construct an assessment model for the rate of cultivated land conversion to non-agricultural uses. Based on this model, the study conducts spatial autocorrelation analysis and locational gradient analysis to systematically investigate the characteristics and driving mechanisms of cultivated land conversion to non-agricultural uses in Jiangsu Province from 2000 to 2023. The study revealed several key findings: (1). The total area of cultivated land in Jiangsu Province has demonstrated a trend of ‘initial continuous decline followed by a slight recovery after 2015.’ Spatially, it exhibits a distribution pattern characterized by ‘continuous reduction around urban areas, with relative stability in the northern core regions’. (2). The temporal pattern of cultivated land conversion to non-agricultural use in Jiangsu Province follows a trajectory of ‘rapid expansion (2000–2015) followed by a gradual slowdown (2015–2023),’ with significant gradient differences observed spatially (‘Southern Jiangsu > Central Jiangsu > Northern Jiangsu’). (3). The conversion of cultivated land to non-agricultural use in Jiangsu Province results from the combined effects of natural constraints, socio-economic driving factors, and agricultural policies. Topographical constraints and urban radiation have emerged as the primary spatial conditions promoting non-agriculturalization, with urban expansion identified as the most direct driving factor of cultivated land conversion in recent years. Conversely, agricultural factors have exerted a relatively weaker influence on non-agriculturalization. These research findings provide a significant scientific basis for formulating differentiated cultivated land protection policies across the province, thereby assisting in achieving a balance between food security and coordinated urban–rural development. Full article

Background/Objectives: Interest in alternatives to animal-derived products has gained momentum, driven by health, environmental, and ethical concerns. However, consumer interest in plant-based meat alternatives (PBMAs) remains highly heterogeneous. This study employs the core dimensions of the Food-Related Lifestyle (FRL) framework for consumer segmentation to deepen understanding of PBMA adoption in a meat-centric context such as Poland, and to derive segment-specific recommendations that support the transition toward plant-based diets. Methods: A cross-sectional survey was conducted among a representative sample of Polish adults (n = 1200). Consumer segmentation was performed using a two-step cluster analysis based on the three FRL dimensions—food involvement, innovativeness, and responsibility. Results: Four distinct consumer clusters emerged, differing significantly across all FRL dimensions (p < 0.001). Cluster 1, Traditionalists (18.5%), demonstrated high food involvement but the lowest innovativeness, showing the highest proportion of non-buyers and strong environmental scepticism. Cluster 2, Conscious Food Enthusiasts (24.6%), demonstrated the highest scores across all FRL dimensions, reported the most frequent PBMA purchases, and showed a strong sustainability orientation combined with a pronounced appreciation for sensory quality and eating enjoyment. Cluster 3, Moderates (38.8%) occupied intermediate positions exhibiting moderate PBMA purchasing frequency but expressing concern about food waste. Cluster 4, Careless Food Lovers (18.2%, n = 218), showed high food involvement and innovativeness, but the lowest responsibility, characterised by pronounced environmental scepticism. Conclusions: The study shows that consumer segments with similar levels of food involvement differ in their perceptions, beliefs, and willingness to adopt PBMAs, primarily according to their environmental orientation. These findings highlight that a strong interest in food alone does not translate into acceptance of plant-based alternatives unless accompanied by sustainability-oriented values. Overall, the results offer practical guidance for designing marketing, product development, and policy initiatives tailored to distinct consumer profiles, supporting the transition toward more plant-based dietary patterns. Full article

Social media has become a dominant channel for food marketing, particularly targeting youth through visually engaging and socially embedded content. This study investigates how young adults visually engage with food advertisements on social media and how specific visual and contextual features influence purchase intention. Using eye-tracking technology and survey analysis, data were collected from 35 participants aged 18 to 25. Participants viewed simulated Instagram posts incorporating elements such as food imagery, branding, influencer presence, and social cues. Visual attention was recorded using Tobii Pro Spectrum, and behavioral responses were assessed via post-surveys. A 2 × 2 design varying influencer presence and food type showed that both features significantly increased visual attention. Marketing cues and branding also attracted substantial visual attention. Linear regression revealed that core/non-core content and influencer features were among the strongest predictors of consumer response. The findings underscore the persuasive power of human and social features in digital food advertising. These insights have implications for commercial marketing practices and for understanding how visual and social elements influence youth engagement with food content on digital platforms. Full article

Background: Obesity is a risk factor for several non-communicable diseases and premature death. The Western-type diet, rich in calories and diverse in tastes, smells, and textures, promotes the onset and progression of obesity. We compared the effects of two Western-style palatable obesogenic diets—the cafeteria (CAF) diet, which allows for self-selection of calorie-dense food items consumed by humans, and the fast-food diet (FFD)—composed of a fixed combination of cheeseburgers and fries—on the manifestation of obesity-related complications. Methods: 3-month-old female rats consumed either the control (CTRL), FFD, or CAF diet for 12 months. Body weight was monitored weekly. At the end of the experiment, rats underwent metabolic and behavioral testing. Cardiometabolic markers and those characterizing glycoxidative and carbonyl stress, inflammatory status, and tryptophan metabolism were determined. Results: The CAF rats gain most weight (CTRL: +111 ± 40 g; FFD: +211 ± 77 g; CAF: 316 ± 87 g). CAF feeding produced a classical metabolic syndrome–like profile with severe obesity, insulin resistance, dyslipidemia, and liver steatosis, whereas the FFD model led to moderate obesity with preserved insulin sensitivity but elevated blood pressure and hepatic cholesterol accumulation. Thus, the CAF group developed a severe metabolic syndrome-like pathology assessed as continuous metabolic syndrome z-core (CTRL: −2.3 ± 1.0; FFD: −0.4 ± 1.9; CAF: 3.0 ± 2.4). Despite these differences, both diets promoted neuroinflammation and social deficits, likely mediated through gut microbiota–derived metabolites such as 5-HIAA and indoxyl sulfate. Conclusions: In female rats, self-selected CAF diet drives more severe and distinct pattern of metabolic syndrome-like pathology than a fixed FFD. Full article

Objectives: Intolerance of uncertainty (IU) is a transdiagnostic factor implicated in emotional disorders and has recently been linked to maladaptive eating attitudes. Body dissatisfaction, a core risk factor for maladaptive eating, may represent a key pathway through which IU exerts its effects. This study examined whether body dissatisfaction has an indirect effect on the association between IU and disordered eating attitudes in female university students, controlling for body mass index (BMI) and trait anxiety. Methods: A cross-sectional study was conducted with 141 female psychology students aged 18–35 years (M = 21.23, SD = 2.31). Participants completed self-report measures of IU (Intolerance of Uncertainty Scale–Short Form), body dissatisfaction (Body Shape Questionnaire), disordered eating attitudes (Eating Attitudes Test-26), trait anxiety (State–Trait Anxiety Inventory), and reported weight and height to calculate BMI. Indirect effects were tested using bootstrapped mediation models. Results: IU was positively associated with body dissatisfaction (β = 1.139, p = 0.001), which in turn significantly predicted dieting (β = 0.126, p < 0.001) and bulimia/food preoccupation (β = 0.033, p < 0.001), but not oral control. Bootstrapped analyses showed significant indirect effects of IU on dieting (β = 0.144, 95% CI [0.047, 0.251]) and bulimia/food preoccupation (β = 0.037, 95% CI [0.010, 0.074]) via body dissatisfaction. Direct effects of IU on eating attitudes were not significant. Conclusions: IU to be associated with disordered eating attitudes primarily through body dissatisfaction, independently of BMI and anxiety. These findings extend evidence of IU as a cognitive vulnerability for eating-related psychopathology to non-clinical populations, highlighting the need for preventive interventions addressing both body image concerns and IU in female university students. Full article

Maintaining the freshness of shrimp is a critical issue in quality and safety control within the food processing industry. Traditional methods often rely on destructive techniques, which are difficult to apply in online real-time monitoring. To address this challenge, this study aims to propose a non-destructive approach for shrimp freshness assessment based on imaging and deep learning, enabling efficient and reliable freshness classification. The core innovation of the method lies in constructing an improved GoogLeNet architecture. By incorporating the ELU activation function, L2 regularization, and the RMSProp optimizer, combined with a transfer learning strategy, the model effectively enhances generalization capability and stability under limited sample conditions. Evaluated on a shrimp image dataset rigorously annotated based on TVB-N reference values, the proposed model achieved an accuracy of 93% with a test loss of only 0.2. Ablation studies further confirmed the contribution of architectural and training strategy modifications to performance improvement. The results demonstrate that the method enables rapid, non-contact freshness discrimination, making it suitable for real-time sorting and quality monitoring in shrimp processing lines, and providing a feasible pathway for deployment on edge computing devices. This study offers a practical solution for intelligent non-destructive detection in aquatic products, with strong potential for engineering applications. Full article

By 2030, the world population is projected to reach approximately 9.7 billion. One of the core objectives of the global sustainable development goals (SDGs), adopted from the 1996 World Food Summit, is to eradicate hunger by that time, meaning ensuring food security for all. The Food and Agriculture Organization (FAO) defines food security as follows: “Food security exists when all people, at all times, have physical and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life.” Conceptually, it is posited that food security can be understood as a nexus of four elements: Food security = Availability + Access + Utilization + Stability of a food system. This study focused specifically on the food availability component of food security. It addresses a critical gap in the existing literature: the limited understanding of the role farmworkers and their families play in sustaining food systems. Specifically, it explores how the children of Haitian farmworkers in the United States perceive agricultural labor through the lens of their family’s experiences, including their personal willingness to engage in it and their advocacy for others to pursue such work. Although qualitative in nature, this study employed the Political Economy of the Food System, also referred to as Agrifood Systems Theory or the Political Ecology of Food Systems, as its guiding theoretical framework, as it aligns closely with the study’s objectives. The data were collected between December 2022 and June 2023. The sample consisted of eight young adults (ages 18 to 29), all of Haitian descent. Overall, the findings indicated that participants commonly reported feeling a sense of inferiority and a lack of interest in and respect for farmwork as a profession during their upbringing, particularly in comparison to peers from non-farmworker households and those outside of their immediate communities. This sense of inferiority was attributed to several factors, including their upbringing, the inherent vulnerability associated with farm work, and the long-term physical toll agricultural work had on both themselves and their parents. The study’s findings carry important implications for practitioners, scholars, policymakers, and all stakeholders involved in achieving food security. They underscore the urgent need to reform labor policies and improve the conditions surrounding farm work, making it a more appealing, dignified, desirable, and sustainable occupation in the face of a growing world population. Full article

With the growing emphasis on healthy eating and nutrition management in modern society, food image recognition has become increasingly important. However, it faces challenges such as large intra-class differences and high inter-class similarities. To tackle these issues, we present a Food Feature Fusion Network (FFFNet), which leverages a multi-head cross-attention mechanism to integrate the local detail-capturing capability of Convolutional Neural Networks with the global modeling capacity of Vision Transformers. This enables the model to capture key discriminative features when addressing such challenging food recognition tasks. FFFNet also introduces self-supervised clustering, generating pseudo-labels from the feature space distribution and employing a clustering objective derived from Kullback–Leibler divergence to optimize the feature space distribution. By maximizing similarity between features and their corresponding cluster centers, and minimizing similarity with non-corresponding centers, it promotes intra-class compactness and inter-class separability, thereby addressing the core challenges. We evaluated FFFNet across the ISIA Food-500, ETHZ Food-101, and UEC Food256 datasets, attaining Top-1/Top-5 accuracies of 65.31%/88.94%, 89.98%/98.37%, and 80.91%/94.92%, respectively, outperforming existing approaches. Full article

Although mulberry leaf (Morus alba L., ML) and Siraitia grosvenorii (SG) individually demonstrate anti-diabetic properties, their combined efficacy against type 2 diabetes mellitus (T2DM) remains unexplored. This study systematically explored the multi-target mechanisms and synergistic potential of the MLSG combination (MLSG) for T2DM intervention. We evaluated the in vitro inhibitory activities of MLSG, ML, and SG on α-amylase and α-glucosidase, alongside antioxidant capacity assessments through DPPH/ABTS radical scavenging, reducing power, and FRAP assays. Bioactive metabolites were identified using non-targeted metabolomics, while core targets and pathways were predicted using network pharmacology and validated through molecular docking. The results reveal MLSG’s significantly enhanced inhibition of α-amylase (IC₅₀ = 14.06 mg/mL) and α-glucosidase (IC₅₀ = 0.02 mg/mL) compared to individual extracts, exhibiting 1.3–15.5-fold higher potency with synergistic effects (combination index < 1). MLSG also showed improved antioxidant capacity, outperforming SG in DPPH/ABTS⁺ scavenging and reducing power (p < 0.05), and surpassing ML in ABTS⁺ scavenging, reducing power, and FRAP values (p < 0.05). Metabolomics identified 26 MLSG-derived metabolites with anti-T2DM potential, and network analysis pinpointed 26 active components primarily targeting STAT3, AKT1, PIK3CA, EGFR, and MAPK1 to regulate T2DM pathways. Molecular docking confirmed strong binding affinities between these components and core targets. Collectively, MLSG exerts potent synergistic anti-T2DM effects through dual-enzyme inhibition, elevated antioxidant activity, and multi-target pathway regulation, providing a solid foundation for developing MLSG as functional food ingredients. Full article

Gastrodiae Rhizoma (tianma, TM), a traditional medicine that has food and medicine homology, faces controversy over retaining its epidermis (tianma pi, TP) during processing due to unclear phytochemical value. This study presents the first integrated approach combining GC–IMS, UHPLC–MS, and Caenorhabditis elegans (C. elegans) aging models to compare TP with the tuber core (tianma xin, TX). The results include the following: (1) A total of forty-seven volatile compounds were identified by GC–IMS, including 12 key aroma substances via relative odor activity value (ROAV ≥ 1), of which seven ((Z)-4-heptenal, β-citronellol, hexanal, 1-pentanol, 1-octen-3-one, 2-methylpropanol, and 2-butanone) were enriched in TP. (2) Non-targeted metabolomics revealed 1025 metabolites via UHPLC–MS, highlighting phenylpropanoid biosynthesis as the primary differential pathway (p < 0.05). Phenylpropanoids and polyketides exhibited predominant enrichment in TP (|log2FC| > 2, VIP > 1, p < 0.01). (3) In C. elegans models, TP outperformed TX in pharyngeal pumping (4.16%, p < 0.05), while both extended stress-resistant lifespan (p < 0.01). In conclusion, TP plays an essential role in establishing the characteristic odor profile of TM and retaining bioactive components, particularly phenylpropanoids. Preserving TP during processing optimally maintains the distinctive aroma profile and pharmacological value of TM, which provides valuable guidance for industrial utilization. Full article

Edible insect farming represents a promising sector focused on producing sustainable and nutritional food and feed. Compared to conventionally farmed animals, insects are more sustainable, thanks to lower greenhouse gas emissions, efficient bioconversion, and minimal space requirements. These characteristics make edible insect farming remarkably eco-friendly: this concept aligns with the core principles of the organic supply chain. However, current organic regulations do not yet include insects. This review investigates various aspects of edible insect rearing to better understand how an “organic edible insect farm” could be established. Nine insect species that have been authorized as ingredients for the production of either food or feed were included, such as Hermetia illucens, Musca domestica, Tenebrio molitor, Alphitobius diaperinus, Locusta migratoria, Gryllodes sigillatus, Gryllus assimilis, Acheta domesticus, and Bombyx mori. Among the evaluated features of insect farming, insect welfare and the use of chemical substances (such as veterinary drugs and pesticides) are thoroughly examined in the literature review. These represent the most significant challenges given the scarce knowledge both on the well-being of insects, currently identified as non-sentient beings, and on the degradation and metabolism of drugs or pesticides that could harm the animals but also undermine consumer safety. Full article

As Generation Z gradually becomes the dominant consumer group, the catering industry, as a critical sector affecting people’s livelihood, warrants an in-depth investigation into its consumption decision mechanisms. This study, grounded in the online–merge–offline (OMO) context, empirically examines the impact mechanism of frontline employee service competence on the repurchase decisions of Generation Z consumers in the foodservice sector, while testing the mediating roles of customer satisfaction and brand trust, as well as the moderating effect of the OMO scenario. Data were collected via a survey of 326 Generation Z customers who consumed in integrated OMO dining environments. Partial least squares structural equation modeling (PLS-SEM) was employed for the data analysis. The findings reveal that frontline employee service competence significantly and positively influences consumer repurchase intention and customer satisfaction, but does not have a significant effect on brand trust. Customer satisfaction fully mediates the relationship between employee service competence and repurchase decisions, whereas brand trust, despite having the strongest direct effect on repurchase intention, is predominantly shaped by systemic factors such as food safety and supply chain transparency, rendering its mediating pathway non-significant. Furthermore, the OMO context does not exhibit a significant moderating effect between employee service competence and customer satisfaction, nor between employee service competence and brand trust, reflecting that the current digital integration has yet to effectively address Generation Z’s core needs for privacy protection and emotional resonance. This study elucidates the “contact–cognition–behavior” pathway by which service competence influences consumer decision-making through satisfaction, while clarifying the systemic formation mechanism of brand trust. Based on these results, it is recommended that enterprises prioritize emotional service training for frontline employees to enhance satisfaction, build brand trust through ingredient traceability systems, and optimize OMO scenario design to better align with Generation Z’s expectations for emotional interaction. Full article