Efficacious paper-based colorimetric detection of bacterial contamination in vegetables utilizing indicator dyes and machine learning.

Global food waste (1.3 billion tons per year) is a major economic and environmental issue, contributing considerably to cash losses and greenhouse gas emissions. This study assesses the efficacy, limitations, and integration potential of four Industry 4.0 technologies—IoT sensors, AI/ML algorithms, advanced active packaging, and blockchain traceability—for waste reduction at key food supply chain stages (production, logistics, retail, and consumption). We show that each technology has different waste reduction advantages using a rigorous literature synthesis (2020-2025), techno-economic evaluation, and environmental impact analysis. Crucially, coordinated deployment unleashes synergistic potential, resulting in considerably larger systemic waste reduction than standalone applications. However, fulfilling this promise requires overcoming long-standing obstacles such as implementation costs, data needs, recyclability issues, and energy usage. The results highlight the need for coordinated policy frameworks that promote interoperable technology, standardized data protocols, and circular design principles. This study outlines a systematic approach for changing food waste from a systemic failure to a controllable engineering issue, resulting in more resilient and efficient food systems.

The global food supply chain is highly susceptible to spoilage and contamination risks, posing severe health hazards to consumers. This creates the need for preservation and safety-monitoring methods to reduce the exposure of both industries and consumers to these risks. Recent innovations using functional materials to construct nano- and microrobots of different shapes and sizes show substantial improvements in optimizing various food processes. Here we review the benefits of applying autonomous functional microrobotics to food science and technology, focusing on applications in food safety control, preservation and processing. We identify current limitations specific to each application and general constraints that must be overcome to transition from proof of concept to real-world implementation in the food industry.

The importance of market gardeners’ characteristics, distribution channels and food supply chain challenges for the viability of their farms: insights from a territorial study in Belgium

Managing Shiga toxin-producing Escherichia coli (STEC) risk in beef: how lack of data impairs risk analysis.

Multi-Criteria Decision Making (MCDM) models are valuable tools for addressing complex decision-making within multiple domains of supply chain management. Considering the complex and uncertain environments that Food Supply Chains (FSCs) operate in, MCDM applications are crucial for optimizing FSC performance across multiple dimensions. Consequently, several research studies focused on the application of MCDM methods within FSCs, with a few focusing on reviewing the literature. However, the literature studies till date revolved around a particular type of FSC or towards enhancing specific FSC capabilities. Besides, no review has used innovative frameworks – such as TCM-ADO, TCCM, 5W+H, etc. to synthesize the existing literature. Hence, this article uses Theories-Contexts-Methods-Antecedents-Decisions-Outcomes (TCM-ADO) framework to enhance the scope of the review. This framework for research synthesis stands unique in comparison with the regular systematic reviews, as it covers holistic synthesis of literature through handling both fronts of research aspects i.e., “what (content)” and “how (methodology)’. The results and findings highlight concentration of studies: a) within specific contexts (agri-food chains-31%, generic-food chains-30%, etc.), b) addressing specific capabilities (sustainability-28%), and c) additionally reveal a research gap in developing unique, hybrid MCDM models to address other contexts (cold chains, perishable food chains etc.) and other capabilities (food quality, food safety, food security, etc.).

Transforming agri-food waste into value: Sustainable approaches for next-generation resistant starch production.

A novel visual-magnetic relaxation switch sensor based on an organic framework nanozyme for ultrasensitive norovirus detection.

Smart food supply chain management: A bibliometric and systematic review

Mature Listeria monocytogenes Biofilms Exhibit Reduced Susceptibility to Sanitizers - Relevance to the (Leafy Green) Fresh Food Supply Chain.

Challenges and future perspectives in postharvest cold storage: technological review on sustainable and efficient cold storage of fresh produce.

Dynamic forecasting of beef freshness using multi-step time series analysis of electronic nose signals.

Enhancing food supply chain sustainability: exploring the role of IoT enablers and sustainable development goals

Aromatic short peptide-metal nanoassemblies in smart hydrogel sensors for real-time food freshness monitoring.

Blockchain-enabled traceability and certification for frozen food supply chains: A conceptual design

The rapid global shift toward organic food consumption has increased the need for reliable methods to verify product authenticity and track supply-chain activities. Conventional record-keeping systems are highly susceptible to manipulation, missing data, and certification fraud, making consumers uncertain about product quality. This research presents an advanced Organic Food Traceability Framework called TrustTrace, designed using blockchain technology, artificial intelligence, and cloud-based data management. Blockchain ensures immutable and transparent event logging, while an AI-based Trust Score evaluates each product batch using parameters such as certification validity, freshness, logistic performance, and stakeholder behavior. MongoDB Atlas functions as the cloud backbone for storing dynamic multi-stakeholder data. Consumers verify authenticity through QR-based access to tamper-proof farm-to-fork histories. This integrated approach significantly improves data reliability, minimizes fraud, and increases consumer confidence in organic food ecosystems

Serratia species are opportunistic human pathogens found in diverse environmental habitats. Here, we report the first isolation of Serratia nevei from food samples in Nigeria. During a two-month epidemiological surveillance at a local food market in Dutsin-Ma, Katsina State, Nigeria, a total of 180 food samples were collected, and isolation and species identification were performed using chromogenic agar and MicroScan autoSCAN-4, respectively. Antimicrobial susceptibility and minimum inhibitory concentrations (MICs) were determined using the MicroScan autoSCAN-4 system. Strain F129B, recovered from a fresh, unprocessed beef sample, was initially identified as Klebsiella pneumoniae by chromogenic agar and MicroScan autoSCAN-4, and subsequently as Serratia marcescens by MALDI-TOF MS. Only Whole Genome Sequencing (WGS) and bioinformatics analyses confirmed its identity as S. nevei. The strain was then selected for further characterization by Whole Genome Sequencing (WGS) and bioinformatics analyses to confirm its identity. The strain was phenotypically resistant to amoxicillin/clavulanic acid and colistin, with elevated MICs for aztreonam (4 mg/L) and cefuroxime (16 mg/L). In silico analyses of its genome confirmed the isolate as S. nevei, harboring genes conferring resistance to β-lactams (blaSTR-2), aminoglycosides (aac (6′)-Ic), fosfomycin (fosA), streptomycin (satA), and tetracycline (tet (41)). Its virulence repertoire comprises genes associated with adhesion (yidE, yidR, yidQ), colicin tolerance (creA and creD), and heavy metal resistance (czcD, chrBACF operon). These findings underscore the need for genomic characterization for accurate species identification within the Serratia genus. Our findings revealed the emergence of S. nevei in the food supply chain and highlighted its potential for zoonotic transmission. Robust surveillance of the local food supply chain is urgently needed in north-western Nigeria.

As a rapidly growing sector in the food industry, the development of ready-to-eat meals faces challenges in overcoming regional capacity barriers. Achieving sustainable growth requires systematic capacity reallocation. While the market remains concentrated in eastern China, western regions have experienced capacity outflow without establishing structured frameworks. This study examines Anjing Food Co., Ltd. as a case study, analyzing its successful capacity reallocation model to provide actionable strategies and reference frameworks for the industry. The research aims to facilitate coordinated regional capacity transfers in the ready-to-eat meal sector, ultimately advancing sustainable development across China's food supply chain.

Purpose Digital technologies offer substantial opportunities for enhancing operational efficiency; however, their precise roles in managing cold chains – especially long-distance logistics – remain unclear. Cold chains are vulnerable to various risks that can jeopardize food safety and diminish the food supply. This study employs resource-based theory to investigate how technologies and capabilities can improve cold chain performance and overall organizational effectiveness. Design/methodology/approach Using the partial least square – structural equation model (PLS-SEM), the research analyzed responses from a survey of 243 multinational and local firms operating in South and Southeast Asia. Findings The findings suggest that, although many organizations utilize technologies for traceability and data analysis, their impact on cold chain performance is limited. Companies often face challenges in effectively integrating these technologies at both operational and tactical levels. Additionally, the study highlights inadequate technology adoption across the supply chain, leading to significant fragmentation in information exchange among partners. This fragmentation not only drives up operational costs but also results in poorly coordinated and disconnected cold chains, resulting in higher food loss and waste. Practical implications This research provides practical guidance for cold chain managers to prioritize the adoption of IoT and data analytics capabilities (DAC) for improved efficiency and risk mitigation. It highlights the need for standardized technologies and enhanced collaboration to meet global compliance and market access goals. Additionally, it offers policymakers actionable insights to improve food security and logistics performance through targeted technology implementation. Originality/value This research contributes to the growing body of knowledge on digital cold chains, offering valuable insights for policymakers and scholars. The results can inform national logistics strategies and encourage practitioners to enhance technology adoption by focusing on developing capabilities beyond simple investments. Such advancements could improve food security and study.

Nanotechnology, a rapidly evolving discipline, shows remarkable promises for revolutionizing a wide range of industries, offering innovative solutions to long-lasting challenges. In the research Within the food sector, packaging and preservation, the application of nanoparticles (NPs) represents a significant breakthrough, enhancing product freshness, safety and reducing waste. Widely studied NPs such as copper oxide (CuO), silver (Ag), magnesium oxide (MgO), titanium dioxide (TiO2), silicon dioxide (SiO2), zinc oxide (ZnO), carbon dots, graphene, chitosan and mesoporous particles have demonstrated remarkable potential in extending product’s freshness and reduce safety risks by inhibiting microbial growth and lowering spoilage in tomato, broccoli, spinach and other green vegetables. This review highlights the utilization of NPs, including Ag, ZnO, TiO2, SiO2, nanoclay and nanochitosan as well as nanoencapsulation techniques, in food systems. Furthermore, it explores how nanotechnology can revolutionize food packaging and preservation by enabling more effective, efficient and environmentally sustainable practices, ultimately contributing to a greener and more secure global food supply chain.