Traditional computer vision-based quality perception lacks depth information, limiting its application to reliable food quality management in the post-harvest supply chain. Three-dimensional (3D) reconstruction technology captures detailed surface geometry and internal structural information for reliable non-destructive quality inspection. Combined with emerging artificial intelligence (AI) technologies, 3D data-driven adaptive management brings potential for next-generation post-harvest quality management. This review analyzed 90 major related studies during 2015–2025, covering high-throughput 3D in-line inspection, high-resolution tomography, portable 3D sensing, and AI-driven 3D reconstruction technologies. Post-harvest supply chain application scenarios are mainly distributed in post-harvest processing (33 studies), manufacturing (29 studies), distribution (15 studies), and consumption (13 studies). Among them, fruit and vegetable products are the most intensively researched, highlighting the suitability and potential benefits of 3D reconstruction for these types of products. Besides, multiple 3D reconstruction technologies have been validated for postharvest evaluation, with X-ray CT dominating postharvest processing, manufacturing, and distribution, and portable RGB imaging devices dominating application in consumption. Besides, relevant 3D reconstruction analysis is evolving from geometry-driven to AI-enhanced analysis and management, highlighting the growing role of 3D reconstruction technology in intelligent, traceable, and sustainable post-harvest supply chain quality management. In the future, by integrating digital twins, IoT, and blockchain technologies, it is expected to build a transparent, tamper-proof quality traceability and control system across the global food supply chain. • 3D reconstruction significantly improves non-destructive food quality inspection. • AI integration expands 3D reconstruction applications in food supply chains. • Applications span post-harvest, processing, logistics, and consumer evaluation. • Enables automation in grading, manufacturing, cold chain, and dietary assessment. • Future trends include sensor fusion, XR, and digital twin for food quality control.

The divergence between the nutritional efficacy and the adverse sensory profile of Brassica vegetables constrains consumer acceptance and industrial utilization. This review systematically evaluated the formation, transformation, stability, and sensory consequences of glucosinolate-derived flavor compounds throughout the food supply chain. The molecular mechanisms regulating glucosinolate hydrolysis into isothiocyanates and nitriles were critically analyzed. Special emphasis was placed on the regulatory roles of endogenous specifier proteins and external processing conditions. Across Brassica systems, flavor quality is governed not simply by total glucosinolate abundance, but by precursor heterogeneity, hydrolysis-product partitioning, and matrix-dependent sensory thresholds. Furthermore, this review assessed the synergistic effects of thermal degradation, the Maillard reaction, and microbial biotransformation on flavor development during thermal processing and microbial fermentation. Although non-thermal processing and modified atmosphere packaging enhance flavor stability, balancing bioactive compound retention with desirable sensory quality remains a critical challenge. To address this gap, this review proposed a three-tier "farm-to-fork flavor regulation model." It linked precursor availability, reaction pathway selection, and matrix-dependent stability to flavor formation and perception across the production-to-consumption continuum. By integrating these regulatory layers, the framework provided a mechanistic basis for addressing the nutrition-sensory dilemma. It identified where interventions could retain health-promoting compounds while limiting excessive bitterness or pungency, thereby improving consumer acceptability. Overall, predictive flavor control in Brassica foods will require coordinated intervention across precursor regulation, pathway steering, and matrix-dependent sensory expression.

Microplastic biofilms enhance environmental stress, disinfectant, and antibiotic tolerance of Salmonella enterica serovar typhimurium in simulated fresh vegetable processing systems.

Antibiofilm Mechanisms and Applications of Natural Compounds.

A functionalized photocrosslinked organic-inorganic hybrid hydrogel for strawberry preservation and multimodal sensing.

Addressing post-harvest potato losses and advancing value addition through agro-processing for sustainable food supply chain: A review

Purpose The local food sector is embracing digital platforms as one of the supply chain (SC) configurations to hone SC efficiency. However, factors determining the successful development of digital platform-based local food supply chains (LFSCs) remain underexplored. This study aims to propose a framework of critical success factors (CSFs) for digital platform-based LFSCs. Design/methodology/approach The authors have adopted a multiple-case study approach where cases are both successful (active) and failure (inactive) initiatives and represent diverse business models. Findings Drawing on a digital platform lens, the authors have explored 12 CSFs, grouped under 4 overarching factors (value-oriented, organizational, user-related and contextual). The former two are micro-level factors, whereas the latter two are meso- and macro-level factors, respectively. This research infers that these factors are interdependent. Practical implications By identifying micro-level factors as fundamental enablers, this research informs platform managers that they should give utmost attention in designing and securing these factors. Furthermore, recognition of meso-level CSFs as a functional enabler informs managers that they should strategically cultivate the network size and exert effort to encourage users’ behavioral change. Alongside, by establishing macro-level CSFs as a structural enabler, this study informs policymakers on the necesity of creating a supportive regulatory framework and enhancing budget provisions for financial grants directed towards digital local food platforms. Social implications By leveraging the identified CSFs, practitioners can increasingly develop effective and viable digital platforms for local food, thereby broadening market reach for small- and medium-sized producers. Increased market access for these producers can, in turn promote rural development and SC equity. Simultaneously, the rise in viable platforms for local foods can enhance consumers’ (specifically urban consumers’) access to fresh local produce, thereby improving food security and their dietary quality. Moreover, the arrangement of hybrid communication by platform orchestrators can lessen information asymmetries and strengthen relationships between producers and consumers, hence fostering social capital within the SC. All these corroborate the societal contribution of this study. Originality/value This study extends SC literature by demonstrating that the digital platform-based LFSCs cannot be successfully developed by simply replicating CSFs pertinent to the traditional LFSCs; instead, platform-specific CSFs are required. Furthermore, this research shows that CSFs span multiple levels and are interdependent. This study also contributes to platform literature by adding a relational aspect to platform theory.

Type 2 diabetes mellitus (T2DM) is rising rapidly in Iran, where climate-related hazards such as heatwaves, sand and dust storms, and disruptions to food and medicine supply chains challenge continuity and quality of care. We sought to validate a climate-sensitive, health system-oriented management model for T2DM using a Delphi consensus process. Eighteen experts in diabetes, noncommunicable diseases and health systems rated 51 statements derived from the preliminary Integrated Iranian Climate-Sensitive Diabetes Management Model (ICDMM), mapped onto six domains aligned with WHO health system building blocks. Items were scored on a binary agree/disagree scale, with a ≥ 70% agreement threshold for consensus. In round 1, agreement ranged from 61.1% to 100.0%; 46 statements met the threshold and five were revised. In round 2 all revised items achieved ≥ 80% agreement, and ultimately all 51 statements reached consensus. The validated ICDMM comprises six domains and 51 components spanning climate-informed governance, resilient and equitable service delivery, workforce preparedness, digital and early-warning information systems, climate-resilient supply chains, and equity-oriented climate-sensitive financing. The ICDMM offers a disease-specific framework for operationalising climate-resilient health system principles for T2DM in a climate-vulnerable middle-income setting and now requires implementation and evaluation in real-world practice.

A framework for the recursive risk-ranking of foodborne zoonotic threats along food supply chains.

Critical factors for sustainable perishable food supply chains: Insights from Malawi banana supply chain

Embodied artificial intelligence in the food supply chain: Innovations, challenges, and future perspectives

Interventions in the food system to improve sustainability are emerging research areas reflecting complex relations between consumption, production, and environmental impact. This umbrella review aimed to explore current research on food systems initiatives and their relationship with human health and sustainability outcomes. An umbrella review of systematic and scoping reviews describing food system initiatives with cobenefits for health and at least one sustainability outcome was conducted. Five databases were searched, covering 2015-2024. The systematic search identified 2770 records and 20 articles were included. Most reviews described initiatives on sustainable diets (n = 7), food security (n = 3), urban agriculture (n = 4), food supply chain (n = 3), education (n = 2), and the global syndemic (n = 1). Three reviews (15%) reported on all three sustainability outcomes combined. Economic sustainability was reported only alongside social (n = 4) or environmental (n = 3) outcomes. Social and environmental outcomes were examined in isolation (social [n = 3]; environmental [n = 3]) or in combination (n = 4). No clear trends emerged between intervention topics and outcomes. Included reviews identified the need for further research that took a holistic approach to food system sustainability. This review supports the crucial need for robust, methodological multidisciplinary systems research to effectively integrate all sustainability dimensions to drive transformative food systems' change.

Dynamic risk-aware ant colony optimization for low-carbon routing in perishable food supply chains

Intelligent label systems in fresh food supply chain: from single-function to multi-parameter integration

Portable smartphone-assisted fluorescence platform based on dual-excitation nitrogen-doped carbon dots for simultaneous detection of chlorogenic acid and tinidazole.

ABSTRACT Traditional chestnut farming in the Sierra de Aracena, Spain, is threatened by land abandonment driven by its declining profitability within the prevailing global agrifood paradigm. An agroecological transformation of the chestnut value chain (VC) is seen by community stakeholders as a pathway to ensure its economic viability while maintaining social and environmental sustainability. This research aimed to co-create actionable knowledge with stakeholders by analyzing the VC’s actor network, governance mechanisms and power dynamics, to identify barriers and leverage points supporting an agroecological transformation. Field work including in-depth interviews, participatory mapping, and an analysis of monetary value distribution along the chain, served to map the VC and identify 15 barriers and 14 leverage points for agroecological transformation. Barriers were mostly found in the Long Food Supply Chains (LFSCs) and included hierarchical governance, marked power imbalances, and distributive unfairness toward farmers, unlike shorter ones. Yet LFSCs were found to be important due to limited local chestnut consumption and concentrated production areas. Therefore, many leverage points target LFSC’s functioning, and range from producer cooperation to shifting governance to prioritize social-ecological goals. Our findings provide a foundation for knowledge co-producers can use to navigate change and develop strategies to safeguard this invaluable traditional system.

There have been several calls among circular economy (CE) scholars for a greater understanding of its historical origins. CE thinking first emerged in Britain in the late 1850s and 1860s associated with the emerging animal feeds sector. Despite large literatures on the history of the beef and dairying sectors, animal feeds remain under-researched in business history. The invention of compound animal feed in 1859 enabled the unwanted byproducts from many parts of the human food supply chain to be reused as animal feed. This was sufficiently important that several large producers of human foods diversified into animal feeds solely to valorize their waste byproducts. We explore the role of Victorian values and theological motivations for waste valorization and the general importance of perishability to the retention of value in residuals to explain why investment in technological innovation to promote recycling became so significant to the animal feeds sector.

The global expansion of the halal industry has placed considerable pressure on food supply chains, particularly among small and medium enterprises (SMEs) in West Java's food sector. This research examines the interplay between halal operations management practices and supply chain integration to determine their combined effects on logistics performance, addressing persistent gaps in halal logistics efficiency. A quantitative approach employing partial least squares structural equation modeling (PLS-SEM) analyzes survey responses from 186 food SMEs across West Java, treating halal operations management and supply chain integration as key independent constructs, with logistics performance as the dependent variable; mediation effects were tested through bootstrapping procedures. Halal operations management significantly improves logistics performance, while supply chain integration fully mediates this relationship — West Java SMEs show measurable gains in on-time delivery and inventory efficiency when halal practices are structurally aligned with supply chain coordination. The cross-sectional design limits causal inference, and findings may not generalize beyond food SMEs in West Java; future research should examine longitudinal effects and multi-sector applications across Indonesia. This study is among the first to connect halal operations management with supply chain integration in explaining logistics performance among Indonesian SMEs, addressing theoretical gaps between Islamic business practices and modern supply chain theory while offering a practical framework for West Java's halal sector development.

This review aims to critically evaluate sustainable smart sensing technologies and AI-driven platforms for real-time mycotoxin detection, highlighting innovations, integration across the food supply chain, current limitations, and future directions for safer, data-driven food safety management. This systematic review followed PRISMA guidelines and covered studies published between 2015 and 2025. Literature searches were conducted in Scopus, Web of Science, PubMed, IEEE Xplore, and Google Scholar, yielding a total sample of 620 identified records. Peer-reviewed articles on smart sensors, biosensors, and AI-driven mycotoxin monitoring were included. After title, abstract, and full-text screening based on predefined eligibility criteria, approximately 160 studies were retained and formed the final sample for qualitative synthesis across the food supply chain. Sustainable smart sensing and AI-driven platforms are transforming real-time mycotoxin detection across the food supply chain by enabling rapid, sensitive, and decentralized monitoring from farm to fork. Emerging biosensors, optical sensors, and IoT-enabled devices integrated with machine learning improve early warning, traceability, and decision-making. However, key gaps remain, including limited sensor robustness under variable field conditions, high costs of advanced materials, energy demands, and scarcity of large, standardized datasets for AI training. Interoperability between sensing platforms and regulatory frameworks is also underdeveloped. Sustainability challenges involve balancing analytical performance with low-energy operation, sensor recyclability, and accessibility for low-resource settings. Future directions should prioritize biodegradable and reusable sensor materials, edge-AI and low-power electronics, federated data-sharing models, and climate-resilient deployment strategies. Integrating predictive analytics with risk assessment and policy alignment will be essential for scalable, sustainable mycotoxin management systems.

Modelling environmental, social and nutritional impacts of food consumption requires detailed, disaggregated data linking consumption-level food items to agricultural commodities. Here, we present a harmonised dataset for the decomposition of composite foods - such as mixed dishes, processed products, and multi-ingredient items - recorded in European dietary surveys (classified using European Food Safety Authority (EFSA)'s FoodEx2 system) and their association with life cycle inventory data. The dataset includes a decomposition table as well as matching tables linking FoodEx2 items to food item labels of three commonly used environmental impact databases (Poore and Nemecek dataset, Agribalyse v3.2, Ecoinvent v3.10). Yield conversion factors and consumer food waste coefficients are incorporated to support full food supply chain impact modelling. The dataset is complemented by an R script that supports semi-automatic matching, which can easily be applied to other datasets. Together, these open-access resources support high-resolution modelling of food systems in nutrition, sustainability, and food policy research by transparently connecting reported food consumption to underlying ingredient and commodity data.