From detection methods to risk prevention: Control of N-nitrosamines in foods and the role of natural bioactive compounds.

Food processing unavoidably introduces various risky ingredients that threaten food safety. N-Nitrosamines (NAs) constitute a class of food contaminants, which are considered carcinogenic to humans. According to the compiled information, pretreatment methods based on solid-phase extraction (SPE) were widely used before the determination of volatile NAs in foods. The innovation of adsorbents and hybridization of other methods have been confirmed as the future trends of SPE-based pretreatment methods. Moreover, technologies based on liquid chromatography and gas chromatography were popularly applied for the detection of NAs. Recently, sensor-based methods have garnered increasing attention due to their efficiency and flexibility. More portable sensor-based technologies are recommended for on-site monitoring of NAs in the future. The application of artificial intelligence can facilitate data processing during high-throughput detection of NAs. Natural bioactive compounds have been confirmed to be effective in mitigating NAs in foods through antioxidation, scavenging precursors, and regulating microbial activities. Meanwhile, they exhibit strong protective activities against hepatic damage, pancreatic cancer, and other NA injuries. Further supplementation of data on the bioavailability of bioactives can be achieved through encapsulation and clinical trials. The utilization of bioinformatics tools rooted in various omics technologies is suggested for investigating novel mechanisms and finally broadening their applications in targeted therapies.

Blockchain implementation for food safety in supply chain: A review.

Food safety has emerged as the topmost priority in the current fast-paced food industry era. According to the World Health Organization, around 600 million people, approximately 1 in 10 individuals worldwide, experience illness due to contaminated food consumption, resulting in nearly 0.42 million fatalities annually. The recent development in software and hardware sectors has created opportunities to improve the safety concerns in the food supply chain. The objective of this review is to explain the fundamentals of blockchain and its integration into the supply chain of various food commodities to enhance food safety. This paper presents the analysis of 31 conceptual works, 10 implementation works, 39 case studies, and other investigations in blockchain-based food supply chain from a total of 80 published papers. In this paper, the significance of adapting conceptual ideas into practical applications for effectively tracing food commodities throughout the supply chain has been discussed. This paper also describes the transformative role of blockchain platforms in the food industry, providing a decentralized and transparent ledger to access real-time and immutable records of a product's journey. In addition, both the positive impacts and challenges associated with implementing blockchain technology in the food supply chain have been evaluated. In summary, the blockchain-based food supply chains offer greater transparency, traceability, and trust, ultimately resulting in higher standards of food safety and quality.

Transplanting network pharmacology technology into food science research: A comprehensive review on uncovering food-sourced functional factors and their health benefits.

Network pharmacology is an emerging interdisciplinary research method. The application of network pharmacology to reveal the nutritional effects and mechanisms of active ingredients in food is of great significance in promoting the development of functional food, facilitating personalized nutrition, and exploring the mechanisms of food health effects. This article systematically reviews the application of network pharmacology in the field of food science using a literature review method. The application progress of network pharmacology in food science is discussed, and the mechanisms of functional factors in food on the basis of network pharmacology are explored. Additionally, the limitations and challenges of network pharmacology are discussed, and future directions and application prospects are proposed. Network pharmacology serves as an important tool to reveal the mechanisms of action and health benefits of functional factors in food. It helps to conduct in-depth research on the biological activities of individual ingredients, composite foods, and compounds in food, and assessment of the potential health effects of food components. Moreover, it can help to control and enhance their functionality through relevant information during the production and processing of samples to guarantee food safety. The application of network pharmacology in exploring the mechanisms of functional factors in food is further analyzed and summarized. Combining machine learning, artificial intelligence, clinical experiments, and in vitro validation, the achievement transformation of functional factor in food driven by network pharmacology is of great significance for the future development of network pharmacology research.

Comparative analysis of nutritional quality and microbial contamination in camel milk: Evaluating safety and public health risks between camel milk obtained from street vendors and farms in Saudi Arabia.

OBJECTIVES: To evaluate the nutritional quality and microbial contamination of raw camel milk sourced from street vendors and compare it with milk obtained from farms, with a particular emphasis on pathogenic organisms. METHODS: Twenty samples were systematically collected from street vendors and farms between July 2022 and February 2023 and analyzed at King Fahad Medical Research Centre and the Pharmacy College, King Abdulaziz University, Jeddah, Saudi Arabia. The microbial analysis employed culture-dependent techniques for colony-forming unit analysis and isolation of microbial colonies from milk samples. Microbial identification utilized advanced methods, including VITEK-MS equipment and the MALDI-TOF technique. The chemical composition was analysed through enzyme-linked immunosorbent assays. RESULTS: The findings revealed significant differences in microbial loads, with milk sourced from street vendors exhibiting considerably higher microbial counts than farm-sourced milk, including pathogenic species like Staphylococcus aureus and Escherichia coli. The results indicated that camel milk from street vendors possessed a higher level of microbial contamination, suggesting potential health risks associated with its purchase and consumption from these sources. CONCLUSION: This study highlights the urgent need for stringent food safety practices in handling, selling, and distributing camel milk to reduce microbial risks to safe levels, thereby mitigating potential health hazards.

Impact of COVID-19 on Chinese urban consumers' food safety knowledge and behavior - A comparative study between pre and post pandemic eras.

The COVID-19 pandemic caused notable changes to the food-related habits of consumers worldwide due to their concerns about the risk of infection and the requirement to follow government mandates. To investigate the impact of the pandemic on Chinese consumers' food safety knowledge, food safety behaviors, and their most recent food poisoning experiences, we compared the results from an online survey (n = 583, Dec 2019) conducted before the pandemic was officially announced with an identical survey (n = 599, Aug 2023) conducted seven months after the Chinese government downgraded restrictions related to COVID-19. Post-pandemic there was a significant decrease in consumers' food safety knowledge and self-reported food safety behaviors and a significant increase in their self-reported experiences of food poisoning. Despite respondents stating that their food safety knowledge and behaviors had improved since the start of the pandemic, the data obtained from the two surveys and the respondents self-reporting of foodborne illness suggest that in fact their safety knowledge and behaviors had decreased. These findings highlight the need to reinforce food safety education and behaviors during times when the food system is disrupted, and consumers are focusing on what they perceive to be more immediate issues.

Decentralized food safety and authentication on cellulose paper-based analytical platform: A review.

Food safety and authenticity analysis play a pivotal role in guaranteeing food quality, safeguarding public health, and upholding consumer trust. In recent years, significant social progress has presented fresh challenges in the realm of food analysis, underscoring the imperative requirement to devise innovative and expedient approaches for conducting on-site assessments. Consequently, cellulose paper-based devices (PADs) have come into the spotlight due to their characteristics of microchannels and inherent capillary action. This review summarizes the recent advances in cellulose PADs in various food products, comprising various fabrication strategies, detection methods such as mass spectrometry and multi-mode detection, sampling and processing considerations, as well as applications in screening food safety factors and assessing food authenticity developed in the past 3 years. According to the above studies, cellulose PADs face challenges such as limited sample processing, inadequate multiplexing capabilities, and the requirement for workflow integration, while emerging innovations, comprising the use of simplified sample pretreatment techniques, the integration of advanced nanomaterials, and advanced instruments such as portable mass spectrometer and the innovation of multimodal detection methods, offer potential solutions and are highlighted as promising directions. This review underscores the significant potential of cellulose PADs in facilitating decentralized, cost-effective, and simplified testing methodologies to maintain food safety standards. With the progression of interdisciplinary research, cellulose PADs are expected to become essential platforms for on-site food safety and authentication analysis, thereby significantly enhancing global food safety for consumers.

Underexplored food safety hazards of beekeeping products: Key knowledge gaps and suggestions for future research.

These days, a growing consumer demand and scientific interest can be observed for nutraceuticals of natural origin, including apiculture products. Due to the growing emphasis on environmental protection, extensive research has been conducted on the pesticide and heavy metal contamination of bee products; however, less attention is devoted on other food safety aspects. In our review, scientific information on the less-researched food safety hazards of honey, bee bread, royal jelly, propolis, and beeswax are summarized. Bee products originating from certain plants may inherently contain phytotoxins, like pyrrolizidine alkaloids, tropane alkaloids, matrine alkaloids, grayanotoxins, gelsemium alkaloids, or tutin. Several case studies evidence that bee products can induce allergic responses to sensitive individuals, varying from mild to severe symptoms, including the potentially lethal anaphylaxis. Exposure to high temperature or long storage may lead to the formation of the potentially toxic 5-hydroxymethylfurfural. Persistent organic pollutants, radionuclides, and microplastics can potentially be transferred to bee products from contaminated environmental sources. And lastly, inappropriate beekeeping practices can lead to the contamination of beekeeping products with harmful microorganisms and mycotoxins. Our review demonstrates the necessity of applying good beekeeping practices in order to protect honeybees and consumers of their products. An important aim of our work is to identify key knowledge gaps regarding the food safety of apiculture products.

Systematic risk ranking of microbiological hazards in infant foods.

Ensuring food safety, particularly for vulnerable groups, like infants and young children, requires identifying and prioritizing potential hazards in food chains. We previously developed a web-based decision support system (DSS) to identify specific microbiological hazards (MHs) in infant and toddler foods through a structured five-step process. This study takes the framework further by introducing systematic risk ranking (RR) steps to rank MH risks with seven criteria: process survival, recontamination, growth opportunity, meal preparation, hazard-food association evidence, food consumption habits of infants and toddlers in the EU, and MH severity. Each criterion is given a semi-quantitative or quantitative score or risk value, contributing to the final MH risk calculation via three aggregation methods: semi-quantitative risk scoring, semi-quantitative risk value, and outranking multi-criteria decision analysis (MCDA). To validate the criteria and ranking approaches, we conducted a case study to rank MH risks in infant formula, compared the results of the three risk ranking methods, and additionally evaluated the ranking results against expert opinions to ensure their accuracy. The results showed strong agreement among the three methods, consistently ranking Salmonella non-Typhi and Cronobacter spp. and Shiga-toxin-producing Escherichia coli as the top MH risks in infant formulae, with minor deviations. When MHs were ranked after an initial hazard identification step, all three methods produced nearly identical MH rankings, reinforcing the reliability of the ranking steps and the selected criteria. Notably, the risk value and MCDA methods provided more informative MH rankings compared to the risk scoring method. The risk value and risk scoring methods were implemented into an online tool, called the MIcrobiological hazards risk RAnking decision support system (Mira-DSS), available at https://foodmicrobiologywur.shinyapps.io/MIcrobial_hazards_RAnking/. In conclusion, our framework enables the ranking of MH risks, facilitating intervention comparisons and resource allocations to mitigate MH risks in infant foods, with potential applicability to broader food categories.

Functional black phosphorus-based sensors for food safety applications: A review.

Food safety has garnered global attention, necessitating advanced methods for the quick and accurate detection of contaminants. Sensors, notable for their ease of use, high sensitivity, and fast analysis, are prominent. Two-dimensional (2D) nanomaterials have been employed to improve sensor performance. Particularly, black phosphorus (BP) stands out with its multifunctional capabilities, attributed to unique layered structure, ultra-high charge mobility, easy surface functionalization, enhanced optical absorption, and tunable direct bandgap. These characteristics suggest that BP could significantly enhance sensor selectivity, sensitivity, and response speed for contaminant detection. Despite numerous studies on BP-based sensors in food safety, few reviews have been comprehensively summarized. Moreover, challenges in BP's preparation and stability restrict its wider use. This paper reviews recent research on BP's role in food safety, covering preparation, passivation, and applications. Through analysis of challenges and prospects, this review aims to provide insightful guidance for upcoming research in this area.

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays.

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple cross-reactive sensors to identify specific targets via pattern recognition. When the sensor arrays are fabricated with nanomaterials, the binding affinity of analytes to the sensors and the response of sensor arrays can be remarkably enhanced, thereby making the detection process more rapid, sensitive, and accurate. Data analysis is vital in converting the signals from sensor arrays into meaningful information regarding the analytes. As the sensor arrays can generate complex, high-dimensional data in response to analytes, they require the use of machine learning algorithms to reduce the dimensionality of the data to gain more reliable outcomes. Moreover, the advances in handheld smart devices have made it easier to read and analyze the sensor array signals, with the advantages of convenience, portability, and efficiency. While facing some challenges, the integration of artificial intelligence with nanosensor arrays holds promise for enhancing food safety monitoring.

Smart food packaging: Recent advancement and trends.

Food packaging plays an important role in protecting the safety and quality of food products and enables communication with consumers. With the improved consumers' awareness of safety and quality of food products, the changes in consumers' lifestyle, and the growing demand for transparency of food products along the supply chain, food packaging technologies have evolved from only providing the four fundamental functions (i.e., protection and preservation, containment, communication and marketing, and convenience) to possessing additional functions including active modification of the inside microenvironment (i.e., active packaging) and monitoring the safety and quality of products in real-time (i.e., intelligent packaging). A variety of active and intelligent packaging systems have been developed to better protect and monitor the quality and safety of food products during the past several decades. Recently, advanced versions of smart packaging technologies, such as smart active packaging and smart intelligent packaging technologies have also been developed to enhance the effectiveness of conventional smart packaging systems. Additionally, smart packaging systems that harvest the advantages of both active packaging and intelligent packaging have also been developed. In this chapter, a brief overview of smart packaging technologies was provided. Specific technologies being covered include conventional smart packaging technologies and advanced smart packaging technologies, such as smart active packaging, smart intelligent packaging and dual-function smart packaging.

Microfluidics in smart food safety.

The evolution of food safety practices is crucial in addressing the challenges posed by a growing global population and increasingly complex food supply chains. Traditional methods are often labor-intensive, time-consuming, and susceptible to human error. This chapter explores the transformative potential of integrating microfluidics into smart food safety protocols. Microfluidics, involving the manipulation of small fluid volumes within microscale channels, offers a sophisticated platform for developing miniaturized devices capable of complex tasks. Combined with sensors, actuators, big data analytics, artificial intelligence, and the Internet of Things, smart microfluidic systems enable real-time data acquisition, analysis, and decision-making. These systems enhance control, automation, and adaptability, making them ideal for detecting contaminants, pathogens, and chemical residues in food products. The chapter covers the fundamentals of microfluidics, its integration with smart technologies, and its applications in food safety, addressing the challenges and future directions in this field.

Machine learning-enabled colorimetric sensors for foodborne pathogen detection.

In the past decade, there have been various advancements to colorimetric sensors to improve their potential applications in food and agriculture. One application of growing interest is sensing foodborne pathogens. There are unique considerations for sensing in the food industry, including food sample destruction, specificity amidst a complex food matrix, and high sensitivity requirements. Incorporating novel technology, such as nanotechnology, microfluidics, and smartphone app development, into colorimetric sensing methodology can enhance sensor performance. Nonetheless, there remain challenges to integrating sensors with existing food safety infrastructure. Recently, increasingly advanced machine learning techniques have been employed to facilitate nondestructive, multiplex detection for feasible assimilation of sensors into the food industry. With its ability to analyze and make predictions from highly complex data, machine learning holds potential for advanced yet practical colorimetric sensing of foodborne pathogens. This article summarizes recent developments and hurdles of machine learning-enabled colorimetric foodborne pathogen sensing. These advancements underscore the potential of interdisciplinary, cutting-edge technology in providing safer and more efficient food systems.

Intelligent food packaging for smart sensing of food safety.

In this contemporary era, with over 8 billion people worldwide, ensuring food safety has become more critical than ever. To address this concern, the introduction of intelligent packaging marks a significant breakthrough. Essentially, this innovation tackles the challenge of rapid deterioration in perishable foods, which is vital to the well-being of communities and food safety. Unlike traditional methods that primarily emphasize shelf-life extension, intelligent packaging goes further by incorporating advanced sensing technologies to detect signs of spoilage and contamination in real-time, such as changes in temperature, oxygen levels, carbon dioxide levels, humidity, and the presence of harmful microorganisms. The innovation can rely on various packaging materials like plastics, metals, papers, or biodegradable polymers, combined with sophisticated sensing techniques such as colorimetric sensors, time-temperature indicators, radio-frequency identification tags, electronic noses, or biosensors. Together, these elements form a dynamic and tailored packaging system. This system not only protects food from spoilage but also offers stakeholders immediate and adequate information about food quality. Moreover, the real-world application on seafood, meat, dairy, fruits, and vegetables demonstrates the feasibility of using intelligent packaging to significantly enhance the safety and shelf life of a wide variety of perishable goods. By adopting intelligent packaging for smart sensing solutions, both the food industry and consumers can significantly reduce health risks linked with contamination and reduce unnecessary food waste. This underscores the crucial role of intelligent packaging in modern food safety and distribution systems, showcasing an effective fusion of technology, safety, and sustainability efforts aimed at nourishing a rapidly growing global population.

Virtualization and digital twins of the food supply chain for enhanced food safety.

Meeting food safety requirements without jeopardizing quality attributes or sustainability involves adopting a holistic perspective of food products, their manufacturing processes and their storage and distribution practices. The virtualization of the food supply chain offers opportunities to evaluate, simulate, and predict challenges and mishaps potentially contributing to present and future food safety risks. Food systems virtualization poses several requirements: (1) a comprehensive framework composed of instrumental, digital, and computational methods to evaluate internal and external factors that impact food safety; (2) nondestructive and real-time sensing methods, such as spectroscopic-based techniques, to facilitate mapping and tracking food safety and quality indicators; (3) a dynamic platform supported by the Internet of Things (IoT) interconnectivity to integrate information, perform online data analysis and exchange information on product history, outbreaks, exposure to risky situations, etc.; and (4) comprehensive and complementary mathematical modeling techniques (including but not limited to chemical reactions and microbial inactivation and growth kinetics) based on extensive data sets to make realistic simulations and predictions possible. Despite current limitations in data integration and technical skills for virtualization to reach its full potential, its increasing adoption as an interactive and dynamic tool for food systems evaluation can improve resource utilization and rational design of products, processes and logistics for enhanced food safety. Virtualization offers affordable and reliable options to assist stakeholders in decision-making and personnel training. This chapter focuses on definitions and requirements for developing and applying virtual food systems, including digital twins, and their role and future trends in enhancing food safety.

Application of photothermal effects of nanomaterials in food safety detection.

Numerous nanomaterials endowed with outstanding light harvesting and photothermal conversion abilities have been extensively applied in various fields, such as photothermal diagnosis and therapy, trace substance detection, and optical imaging. Although photothermal detection methods have been established utilizing the photothermal effect of nanomaterials in recent years, there is a scarcity of reviews regarding their application in food safety detection. Herein, the recent advancements in the photothermal conversion mechanism, photothermal conversion efficiency calculation, and preparation method of photothermal nanomaterials were reviewed. In particular, the application of photothermal nanomaterials in various food hazard analyses and the newly established photothermal detection methods were comprehensively discussed. Moreover, the development and promising future trends of photothermal nanomaterial-based detection methods were discussed, which provide a reference for researchers to propose more effective, sensitive, and accurate detection methods.

Modernization of digital food safety control.

Foodborne illness remains a pressing global issue due to the complexities of modern food supply chains and the vast array of potential contaminants that can arise at every stage of food processing from farm to fork. Traditional food safety control systems are increasingly challenged to identify these intricate hazards. The U.S. Food and Drug Administration's (FDA) New Era of Smarter Food Safety represents a revolutionary shift in food safety methodology by leveraging cutting-edge digital technologies. Digital food safety control systems employ modern solutions to monitor food quality by efficiently detecting in real time a wide range of contaminants across diverse food matrices within a short timeframe. These systems also utilize digital tools for data analysis, providing highly predictive assessments of food safety risks. In addition, digital food safety systems can deliver a secure and reliable food supply chain with comprehensive traceability, safeguarding public health through innovative technological approaches. By utilizing new digital food safety methods, food safety authorities and businesses can establish an efficient regulatory framework that genuinely ensures food safety. These cutting-edge approaches, when applied throughout the food chain, enable the delivery of safe, contaminant-free food products to consumers.

Frontiers of machine learning in smart food safety.

Integration of machine learning (ML) technologies into the realm of smart food safety represents a rapidly evolving field with significant potential to transform the management and assurance of food quality and safety. This chapter will discuss the capabilities of ML across different segments of the food supply chain, encompassing pre-harvest agricultural activities to post-harvest processes and delivery to the consumers. Three specific examples of applying cutting-edge ML to advance food science are detailed in this chapter, including its use to improve beer flavor, using natural language processing to predict food safety incidents, and leveraging social media to detect foodborne disease outbreaks. Despite advances in both theory and practice, application of ML to smart food safety still suffers from issues such as data availability, model reliability, and transparency. Solving these problems can help realize the full potential of ML in food safety. Development of ML in smart food safety is also driven by social and industry impacts. The improvement and implementation of legal policies brings both opportunities and challenges. The future of smart food safety lies in the strategic implementation of ML technologies, navigating social and industry impacts, and adapting to regulatory changes in the AI era.

Review: Impact of food safety on global trade.

Food safety encompasses the supply and assurance of safe, high-quality food for consumers. It is a crucial aspect of food security, gaining greater global attention due to the increasing number of widespread foodborne incidents. International trade is expanding as countries increasingly rely on each other to secure a sufficient and diverse food supply. Beyond this, concerns about food safety have become more prevalent due to various factors. Therefore, this review aims to investigate the effects of food safety-associated risks on the international trade of food and related products. A total of 37 published studies retrieved using different search engines were included in this review. This review revealed that because of rapid population growth and rising food demand in developing nations, agricultural intensification is growing. It has been found that foodborne illnesses and associated discrepancies can impede the international trade of food commodities. Trade bans due to the fear of foodborne illnesses are growing. The consequences of foodborne diseases are multifaceted and include financial losses from trade restrictions, medical costs for prevention or control, resource depletion and a decline in food production. The overall effects are increased international trade tensions and livelihood vulnerability to poverty, notably for small-scale livestock producers. Potential food contaminants include microbes, pesticides, pharmaceutical residues, heavy metals and fraudulent such as improper food processing, mislabelling, poor packaging, adulteration and substitution. Hence, countries are encouraged to harmonize the rights and duties set by the World Trade Organization under sanitary and phytosanitarys to maximize their advantages in global markets. Based on this evidence, we recommend that each country develop and integrate regulations that would ensure the safety of both domestic and international food production systems. Furthermore, the global community should either revise the current functioning food regulatory and monitoring body or establish a more genuine collaborative network.

Impact of source, packaging and presence of food safety management system on heavy metals levels in spices and herbs.

Spices and herbs are susceptible to various contaminants, including heavy metals. Our study aimed to quantify the levels of lead (Pb), mercury (Hg), cadmium (As), and cadmium (Cd) in 96 composite samples of 13 herbs and spices frequently consumed in Lebanon. Twenty percent (19/96) and 4% (4/96) of the samples exceeded the permissible levels of Pb and Cd, respectively and all the samples met the permissible levels of As and Hg according to Codex Alimentarius standards. For Pb and Cd, unpackaged samples had the highest levels of unacceptable samples of 31% (8/26) and 8% (2/26), respectively. The samples locally packaged in companies with and without Food Safety Management System (FSMS) had the same levels of unacceptable samples of 12% (3/26) and 4% (1/26) for Pb and Cd, respectively. Imported packaged samples had unacceptable levels of Pb (28% (5/18)) and were acceptable for the three other heavy metals.