Optimization of the flow cytometry method of detection, quantification and qualification of microorganisms in carrot juice.

Fresh, unpasteurized carrot juice is a popular element of the everyday diet of many consumers, and as such the matter of the juice's microbial safety remains an important one. Imaging flow cytometry (FCM) allows a fast enumeration and determination of cells, as well as their further differentiation. However, carrot juice is a difficult food product to analyze with the use of FCM due to interference from autofluorescence and the presence of plant debris. In this research, we aimed to obtain an effective and repeatable protocol for the preparation of carrot juice samples for FCM analysis. Through experimental and software-based means we successfully determined a reliable protocol for the preparation of fresh, unpasteurized carrot juice, which consisted of a sequence of filtering, centrifugation, enzyme treatment, and finally the implementation of the Machine Learning protocol for the best result.

A sensitive intelligent point-of-care test method for tert-butylhydroquinone in edible oil via a test strip with a smartphone.

Tert-butylhydroquinone (TBHQ) is easily overused or illegally added to edible oil and attracts a growing concern because of its cytotoxic, liver-damaging, and carcinogenic effects. Thus, a sensitive and intelligent point-of-care testing (iPOCT) method is developed to fulfill the on-site monitoring. This iPOCT method depended on a fluorescent immunochromatographic assay within 15 min. Under optimization, the limit of quantification (LOQ) was calculated as 0.03 µg mL-1. The iPOCT method provided a low limit of detection (LOD) of 0.02 µg mL-1, a wide linear range of 0.03-100 µg mL-1, and great selectivity. Recoveries by the spiking experiments ranged from 97.4% to 103.5% with relative standard deviations (RSDs) of 2.4%-4.9% in soybean, peanut, rapeseed, and corn oil samples. The results showed that the iPOCT method is highly consistent with the high-performance liquid chromatography (HPLC) method.

Accurate and rapid mercury susceptibility detection in aquatic samples using fluorescent probe integrated rhodamine with pyridyl isothiocyanate.

Mercury, one of the various harmful metals, is particularly significant in affecting aquatic organisms, currently gaining more attentions and sparking discussions. In response to the limitations of traditional detections, fluorescent probes have emerged as a promising solution with some advantages, such as weaker background interference, shorter processing time, higher accuracy. Thus, a novel fluorescent probe, FS-Hg-1, has been developed for assessing mercury ion (Hg2+) concentrations in aquatic products. This probe displays specific recognition of mercury ions in fluorescence spectra. Notably, FS-Hg-1 exhibits a distinct color change to pink when combined with Hg2+ (with a 948-fold increase in absorption at 568 nm) and a substantial fluorescence change towards Hg2+ (361-fold increase, excitation at 562 nm, emission at 594 nm) in N, N-dimethylformamide. The probe boasts a detection limit of 0.14 µM and rapid reaction with Hg2+ within 10 s, showing an excellent linear correlation with [Hg2+] in the range of 0 to 10 µM. Through thorough analysis using FS-Hg-1, the results align with those from the standard method (P > 0.05), with spiked recovery rates ranging from 108.4% to 113.2%. With its precise recognition, low detection limit, and remarkable sensitivity, this fluorescent assay proves effective in mercury concentration determination in aquatic samples without interference. The potential of FS-Hg-1 is promising for speedy detection of residual Hg2+ and holds significance in ensuring food safety.

Antimicrobial resistance induction potential of grapefruit seed extract on multi-species biofilm of E. coli in food industry.

Biofilm formation in natural environments involving complex multi-structural arrangements hinders challenges in antimicrobial resistance. This study investigated the antimicrobial resistance potential of grapefruit seed extract (GSE) by examining the formation of mono-, dual-, and multi-species biofilms. We also explored the counterintuitive effect in response to GSE at various concentrations, including minimum inhibitory concentration (MIC) and sub-MIC (1/2 and 1/4 MIC). The results of the swimming and swarming motility tests revealed increased motility at the sub-MIC of GSE. The crystal violet assay demonstrated increased biofilm formation in multi-species biofilms, highlighting the synergistic effect of Escherichia coli, Salmonella Typhimurium, and Listeria monocytogenes. At the MIC concentration of GSE, field emission scanning electron microscopy (FE-SEM) revealed cell morphology damage, while sub-MIC increased biofilm formation and architectural complexity. Multi-species biofilms demonstrated greater biofilm-forming ability and antimicrobial resistance than mono-species biofilms, indicating synergistic interactions and enhanced resilience. These findings highlight the importance of understanding biofilm dynamics and antimicrobial resistance to ensure environmental safety.

An ultrasensitive dual-mode aptasensor for patulin based on the upconversion particles and G-Quadruplex-hemin DNAzyme.

Patulin (PAT) is a mycotoxin-produced secondary metabolite that can contaminate foods, causing toxic effects on animal and human health. Therefore, for the first time, we have constructed a "turn-on" dual-mode aptamer sensor for PAT using oleic acid-coated upconversion nanomaterials (OA-UCNPs) and G-Quadruplex-hemin DNAzyme (G4-DNAzyme) as fluorescent and colorimetry probes. The sensor employs aptamers binding to PAT as recognition elements for specific molecule detection. Mxene-Au can be used as a biological inducer to assist OA-UCNPs in controlling fluorescence intensity. In addition, colorimetric signal amplification was performed using the trivalent G4-DNAzyme to increase detection sensitivity and reduce false positives. Under optimal conditions, the dual-mode aptasensor has a detection limit of 5.3 pg mL-1 in fluorescence and 2.4 pg mL-1 in colorimetric methods, respectively, with the wider linear range and limit of detection (LOD) of the colorimetric assay. The combination aptasensor can detect PAT with high sensitivity and high specificity and has broad application prospects in the field of food safety detection.

Determination of trace elements content of fruits from Tehran's market using ICP- OES method: a risk assessment study.

For the first time in Iran, in this study, the amount of 19 trace elements in some types of commonly consumed Iranian fruits (in their peel and pulp) was evaluated by ICP-OES (Inductively coupled plasma-optical emission spectrometry) method. Based on the outcomes, the highest and lowest average detected elements in all fruits samples were related to (Al) aluminum (1842.18) and (V) vanadium (0.28) ppm, respectively. Mercury (Hg) and antimony (Sb) were not detected (ND) in any samples. Also, the maximum mean of elements in quince, lemon, grapefruit, kiwi, orange south, orange north and tangerine samples was related to(Fe) iron (2048.32 ppm), (Zn)zinc(753.45 ppm), Fe (1056.33 ppm), Al (9794.41 ppm), Zn (717.78 ppm), Fe (1334.87 ppm) and Fe (974.93 ppm), respectively. Furthermore, our outcomes revealed, the highest mean of elements in kiwi peel, kiwi pulp, orange North peel, orange North pulp, orange South peel, orange South pulp, quince peel, quince pulp, grapefruit peel, grapefruit pulp, lemon peel, lemon pulp, tangerine peel and tangerine pulp was related to Al (17967.79 ppm), Al (1621.03 ppm), Fe (1350.01 ppm), Al (1457.66 ppm), Zn (934.71 ppm), Fe (728.06 ppm), Fe (2768.11 ppm), Fe (1328.54 ppm), Zn (1008.54 ppm), Fe (1198.00 ppm), Zn (683.35 ppm), Zn (823.55 ppm), Fe (1182.59 ppm), and Fe (767.27 ppm), respectively. Based on the Monte Carlo simulation results, the THQ (target hazard quotient) and ILCR (Incremental Lifetime Cancer Risk) related to exposure to heavy metals via fruits for adults and children showed that there is no significant non-carcinogenic risk (THQ < 1) and carcinogenic risk (ILCR < 1E-4) for adults and children.

Processing complementary foods to reduce mycotoxins in a medium scale Tanzanian mill: A hazard analysis critical control point (HACCP) approach.

Designing and implementing processing procedures for producing safe complementary foods in dynamic and unregulated food systems where common food staples are frequently contaminated with mycotoxins is challenging. This paper presents lessons about minimizing aflatoxins (AF) in groundnut flour and AF and/or fumonisins (FUM) in maize and groundnut pre-blended flour for complementary feeding in the context of a dietary research intervention in rural Tanzania. The flours were processed in collaboration with Halisi Products Limited (Halisi), a medium scale enterprise with experience in milling cereal-based flours in Arusha, Tanzania. Using a hazard analysis critical control point (HACCP) approach for quality assurance, two critical control points (CCPs) for AF in processing the pre-blended flour were identified: 1) screening maize before procurement, and 2) blending during the processing of each constituent flour. Blending of maize flour was also identified as a CCP for FUM. Visual inspection during screening and sorting were identified as important control measures for reducing AF, but these steps did not meet the criteria for a CCP due to lack of objective measurement and verifiable standards for AF. The HACCP approach enabled the production of low AF (<5 µg/kg) and FUM (<2 µg/g) flours with low rejection rates for the final products. The paper presents practical lessons that could be of value to a range of commercial processors in similar low- and middle-income contexts who are keen on improving food quality.

Application of MXene composites for target gas detection in food safety.

Food contamination has long plagued agriculture, posing significant health risks to consumers. The use of volatile gases for food safety detection has proven highly effective, with composite gas sensors that leverage the two-dimensional material MXene exhibiting notable advancements in detecting various target gases. This paper reviews the progress of MXene-based composite gas sensors in the detection of food safety-related gases. The review begins by examining MXene material synthesis methods and then presents an overview of techniques aimed at enhancing MXene-based sensor detection capabilities. Recently, advancements in MXene composite gas sensors tailored for food safety gases have been highlighted. Finally, challenges encountered in gas-sensing applications of MXene-based composites are outlined, alongside predictions for their future development, aiming to offer insights for the application and advancement of intelligent gas sensors for target gases in food safety.

Safety of titanium dioxide (E171) as a food additive for humans.

Titanium dioxide (TiO2), also known as E171, is commonly used as a white colorant in food, pharmaceuticals, cosmetics, and toothpaste. However, in May 2021, the European Food Safety Authority (EFSA) expert panel, in evaluating the safety of titanium dioxide (E171) as a food additive, concluded that a concern for genotoxicity could not be ruled out. This occurred several years after EFSA had previously considered titanium dioxide to be safe as a food additive. EFSA based this new interpretation on the results of genotoxicity tests of TiO2 nanomaterials. EFSA noted that available data are insufficient to define threshold doses/concentrations of TiO2 particles below which genotoxicity will not occur in tissues containing these particles. Here, it is argued that EFSA made a manifest error regarding the safety of titanium dioxide (E171) particles as a food additive for humans. First, the notion of particle size distribution of TiO2 particles is explained. Second, the changing opinions from the various EFSA evaluations in 2016, 2018, 2019 vs. 2021 are discussed. Third, the low toxicity of TiO2 particles is described in rats exposed by oral gavage and feeding studies in rats and mice. Fourth, the importance of low absorption rates from the gastrointestinal tract vs. circulation in rats and humans but not in mice is identified. Fifth, other international health scientists have weighed in on the EFSA (EFSA J, 2021, 19 (5), 6585) decision and generally disagreed with EFSA's opinion on the safety of E171 TiO2. A common theme voiced by the United Kingdom, Canada, Australia, and New Zealand agencies is that it is inappropriate to compare nanoparticle toxicity studies of dispersed/sonicated nanoparticles with the content of E171 TiO2 in foods because the test materials used in key studies considered by EFSA (EFSA J, 2021, 19 (5), 6585) are not representative of E171 TiO2 particles. Finally, a group of experts recently considered the genotoxicity of TiO2 and could not find support for a direct DNA damaging mechanism of TiO2 (nano and other forms). For these reasons, it is suggested that EFSA made a manifest error on the safety of E171 as a food additive.

Formation and reductionof toxic compounds derived from the Maillard Reaction during the thermal processing of different food matrices.

Advanced glycation end products (AGEs), heterocyclic aromatic amines (HAAs), acrylamide (AA), 5-hydroxymethylfurfural (5-HMF), and polycyclic aromatic hydrocarbons (PAHs) are toxic substances that are produced in certain foods during thermal processing by using common high-temperature unit operations such as frying, baking, roasting, grill cooking, extrusion, among others. Understanding the formation pathways of these potential risk factors, which can cause cancer or contribute to the development of many chronic diseases in humans, is crucial for reducing their occurrence in thermally processed foods. During thermal processing, food rich in carbohydrates, proteins, and lipids undergoes a crucial Maillard reaction, leading to the production of highly active carbonyl compounds. These compounds then react with other substances to form harmful substances, which ultimately affect negatively the health of the human body. Although these toxic compounds differ in various forms of formation, they all partake in the common Maillard pathway. This review primarily summarizes the occurrence, formation pathways, and reduction measures of common toxic compounds during thermal processing of food, based on independent studies for each specific contaminant in its corresponding food matrix. Finally, it provides several approaches for the simultaneous reduction of multiple toxic compounds.

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.

Potential of bacteriophage phT4A as a biocontrol agent against Escherichia coli in food matrices.

Escherichia coli is one of the most prevalent foodborne pathogens, frequently found in meat and dairy products. Current decontamination methods are often associated with changes in organoleptic characteristics, nutrient loss, and potentially harmful side effects. Furthermore, despite the array of available methods, foodborne outbreaks still frequently occur. For this reason, bacteriophages (or simply phages) emerged as a natural alternative for the biocontrol of bacterial contamination in food without altering their organoleptic properties. In this study, the potential of phage phT4A was assessed in the biocontrol of E. coli in liquid (milk) and solid (ham) food matrices. Firstly, as foods have different pH and temperature values, the influence of these parameters on phage phT4A viability was also assessed to develop an effective protocol. Phage phT4A proved to be stable for long storage periods at pH 7-8 (56 days) and temperatures of 4-37 °C (21 days). Before application of phages to inactivate pathogenic bacteria in food, previous assays were carried out in Tryptic Soy Broth (TSB) to study the dynamics of phage-bacteria interaction. Then, the antibacterial potential of phage phT4A was evaluated in the two food matrices at different temperatures (4, 10 and 25 °C). This phage was more efficient at 25 °C in all tested matrices (maximum inactivation of 6.6, 3.9 and 1.8 log CFU/mL in TSB, milk and ham, respectively) than at 10 °C (maximum decrease of 4.7, 2.1 and 1.0 log CFU/mL in TSB, milk and ham, respectively) and 4 °C (maximum reduction of 2.6 and 0.7 log CFU/mL in TSB and milk, respectively). However, the decrease of temperature from 25 °C to 10 and 4 °C prevented bacterial regrowth. The results suggest that during phage treatment, a balance between an incubation temperature that provide effective results in terms of bacterial inactivation by the phages and at the same time prevents or delays bacterial regrowth, is needed. The application of phage phT4A at a temperature of 10 °C can be an effective strategy in terms of bacterial inactivation, delaying bacterial regrowth and also reducing energy costs.

A MOF-on-MOF heterostructure ratiometric/colorimetric dual-mode fluorescence sensor based on support vector machine for detecting tetracyclines in animal-derived foods.

The misuse of tetracyclines in livestock production poses significant health risks. Thus, establishing convenient detection methods to replace complex laboratory tests for food safety is crucial. In this study, a heterostructure Zn-BTC/IRMOF-3 (denoted as ZBI) asynchronous response fluorescence sensor was developed for the qualitative and quantitative detection of tetracyclines in foods. The ZBI solution exhibited blue fluorescence under UV excitation; upon the introduction of tetracyclines, ZBI selectively recognized the tetracycline molecules through electron transfer, π-π stacking, and chelation, resulting in blue fluorescence quenching and green fluorescence enhancement. The ZBI sensor for tetracycline detection achieved recovery rates ranging from 93.91 to 111.91% in food samples, with a detection limit of as low as 0.086 µmol/L. Lastly, a portable sensing device using support vector classifier was constructed for detecting tetracyclines in real-life scenarios. Our findings introduce a new approach for fabricating fluorescence sensors and offer a novel method for detecting tetracyclines.

Innovative Food Safety Approaches and Nutraceuticals to Promote Children's Health on Future Outbreaks with the Reflection of COVID-19.

After the COVID-19 pandemic, innovative methods have emerged for the management of food safety, child nutrition has become more important than ever, and increasing attention has been paid to the consequences of COVID-19. For instance, since SARS-CoV-2 is an animal-based zoonotic virus, there is a changing trend in consumer preferences from conventional meat products to cultured meat and vegan supplementation. Due to the effects mentioned, this chapter provides strategic guidance on novel foods, food safety innovations, and novel health and safety procedures in public places such as restaurants or bars. There are also long-term health impacts on children in the aftermath of COVID-19. Since the risk of myopia is one of the important long-term effects to be considered, trending nutritional immunology approaches are presented to reduce emerging problems in child eye health. The enhancement of immune system remains problematic for many children considering that they cannot use the COVID-19 vaccine. Therefore, this chapter also emphasizes the importance of breastfeeding on the side effects of viral infections and new supplements, such as probiotic drops, to improve children's and babies' immune health. Additionally, efforts should be undertaken to improve nanoencapsulation techniques to prepare for future epidemics and pandemics. Nanomaterial-supported nutraceuticals, nanoencapsulation of functional ingredients or their nanoparticles, and nano-combination of phytochemicals, fatty acids, or probiotics should be investigated to improve the immunity of children. In this sense, detailed further research in this area needs to be adapted to innovative technologies for the treatment of infants and children against future zoonotic viruses.