Abstract
The advent of microfluidic systems has led to significant developments in lab-on-a-chip devices integrating several functions onto a single platform. Over the years, these miniature devices have become a promising tool for faster analytical testing, displaying high precision and efficiency. Nonetheless, most microfluidic systems are not commercially available. Research is actually undergoing on the application of these devices in environmental, food, biomedical, and healthcare industries. The lab-on-a-chip industry is predicted to grow annually by 20%. Here, we review the use of lab-on-a-chip devices in the food sector. We present fabrication technologies and materials to developing lab-on-a-chip devices. We compare electrochemical, optical, colorimetric, chemiluminescence and biological methods for the detection of pathogens and microorganisms. We emphasize emulsion processing, food formulation, nutraceutical development due to their promising characteristics. Last, smart packaging technologies like radio frequency identification and indicators are highlighted because they allow better product identification and traceability.
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Introduction
Rapid urbanization in the last few decades has driven the agro-food sector to undergo a massive transformation with the advent of new technologies and products. The rate at which chemical agents are used in agriculture and industry has risen rapidly with increasing demand for food. Although these chemicals have improved the efficiency of the processes, equal importance needs to be given to environmental and health impacts. Extensive production, usage of pesticides, and the presence of complex contaminants have led to issues in soil fertility, agricultural crop quality, and contaminated water (Ponnuchamy et al. 2021; Sridhar et al. 2022). These hazardous agents pose a serious threat to the environment and ecosystem with concerns arising on the safety of food. According to Food and Agricultural Organization, more than 1.3 billion tons of food gets thrown away and this wastage has increased by 50% (in weight) in recent years (Amicarelli et al. 2020). Significant amounts of food have also been wasted due to microbiological contamination at the post-harvest and consumer levels. The food contamination at any stage significantly impacts health and the economy (Sridhar et al. 2021c). Unsafe food commodities often remain unmonitored and pose a huge health risk for consumers, especially in developing countries. Thus, the detection and prevention of any food contamination and food spoilage should be addressed carefully to reduce the overall health risks as well as to improve productivity and quality of food.
With the rapidly evolving techno-economic landscapes, there has been a significant demand in food and agriculture sector to produce low-cost, environment-friendly, and sustainable technologies. Traditionally, analytical methods such as thin-layer chromatography. high-performance liquid chromatography, gas chromatography, and gas chromatography coupled with mass spectrometry have been used for toxicity and contaminant detection in various agricultural and food products (Guo et al. 2015). Although these techniques are reliable, the equipment space requirements and initial costs are high. In recent years, a rapid change in technological development has been observed aiming to deliver cost-effective solutions utilizing least raw materials with improved overall productivity. Researchers have been focusing on developing new technologies giving considerable attention to food quality, quantity, and safety. However, due to the complexity of agro-food systems, several drawbacks exist that need long-lasting innovations for creating new processes, tools, and technologies.
Advancements in manufacturing began with the development of several novel devices and components like microfluidic chips, microvalves, and micropumps (Min et al. 2004; Mark et al. 2010). This led to the advent of lab-on-a-chip (LOC) technology providing the basis for automation, cost, handling, and portability. LOC refers to a miniaturized device that allows one or more laboratory-scale operations, such as synthesis and analysis of chemicals, to run on a small scale within a handheld portable system. These devices have an overall size ranging from millimeters to a few centimeters with microfluidic channels suitable for handling tiny volumes of fluid samples. The devices are designed and fabricated to accurately and precisely handle fluids in the range of 10–6 to 10–9 L. There has been a huge demand for such technologies offering next-generation devices for different applications. However, only a fraction of the total fabricated devices manages to reach the market due to various reasons such as technical performance, user acceptability, and cost (Wongsrichanalai et al. 2007).
Rapid diagnostic tests are one of the most widely accepted and commercialized lab-on-a-chip technologies so far. These diagnostic devices work on the spot testing or lateral flow principle and are easy to operate. In recent years, significant advancements have been carried out in the development of smartphone-based chips, paper-based microfluidics, and miniature environmental monitoring systems (Hong et al. 2018; Marquez et al. 2019; Puangbanlang et al. 2019; Nelis et al. 2020; Fernández-Abedul 2021). The portable diagnostic test kits have been explored extensively in the healthcare sector and with pandemics like COVID-19, the requirements for accurate sample handling and analysis become even more crucial globally (Yang et al. 2018; Kim et al. 2019; Bhalla et al. 2020; Ghosh et al. 2020; Rasmi et al. 2021).
Apart from pathogen detection in bodily fluids, LOC devices have shown their versatility in the environmental and biomedical industry primarily for air quality detection and glucose measurements (Poenar 2019; Teymourian et al. 2020). When it comes to the food industry, major developments have been carried out in the detection of pathogens and pesticide levels in fruits, vegetables, and other packaged foods (Dooley et al. 2005; Chen et al. 2014; Hou et al. 2019). Studies have also involved efforts to dispense small amounts of liquid for simple pH measurements or sensing (Ude et al. 2015). The applicability of LOC technology in the food industry ranges from simple to complex systems. LOC devices have shown promise in food safety and pathogen control applications like detection of mycotoxins, bacteria, etc. (Wahyuni et al. 2019). However, they are not only limited to applications in detection and sampling. An evaluation was conducted to correlate different fluid flow parameters to produce a single emulsion in emulsion processing (Viza and Harding 2018). Investigation on formation, stability, and release characteristics for designing a one-step multiple emulsion system for encapsulation purposes has also been researched (Clegg et al. 2016). Additionally, applications of LOC technology in sensory studies in aroma and flavor testing have been explored (Ravi et al. 2013). It is noteworthy to mention that a lot of scope lies in related areas of food technology namely emulsion processing, nutraceutical developments, formulation, and packaging. However, these investigations are scattered and require more comprehensive research. With an increasing market growth and ever-changing landscape, the LOC industry is expanding rapidly (Rios et al. 2018). The food and nutraceutical industry would play a crucial role in integrating LOC in addition to biosensing and healthcare sectors. Until today, the market has dominated more in the research arena rather than business to consumer. The need of the hour lies in producing new materials and technologies for cost-effective fabrication methods for such microscale devices.
Review methodology
Bibliometric analysis is one of the useful ways to identify the area and scope of research. The analysis draws improved research output data making the scientists assess the future trends for a specific topic. In the present study, a bibliometric analysis was conducted using Scopus (https://www.scopus.com) and Dimensions (https://www.dimensions.ai/). Scopus is one of the most extensively used databases having wide coverage of journals and hence is chosen for analysis (Singh et al. 2021). However, in the last few years, new scholarly databases like Dimensions have provided possible alternatives to existing databases. They aim to offer high coverage, free cost, and unlimited accessibility and encompass a plethora of topics debated at a global level. Dimensions database is an open-source platform covering a wide range of topics compared to other traditional databases and is, therefore, explored to improve the ecosystem of scientific information (Orduña-Malea and López-Cózar 2018).
The data for the present work was extracted from Scopus and Dimensions on July 7, 2021, for the last two decades (2000–2020). Figure 1 illustrates the bibliometric analysis conducted to evaluate the growth trend of the two databases in the last two decades. As the present study involves a more focused approach toward the food industry, keywords relevant to lab-on-a-chip devices and the food industry were used. The results showed a higher number of documents being captured using Scopus (1721 documents) compared to Dimensions (500 documents). The possible reason for a higher number of documents in Scopus could be due to database popularity. The annual growth of publications for the topic investigated in this study for both the databases was on a positive scale (Scopus: 28.72%, Dimensions: 17.67%) implying the increasing demand for the utilization of lab-on-a-chip devices in food systems. Thus, the goal of this bibliometric analysis and review lies in helping researchers to evaluate the recent developments in the area of lab-on-a-chip technologies in the food industry.
The data extraction from the databases retrieved 1721 documents and 500 documents from Scopus and Dimensions, respectively. Although both the databases showed promising benefits in covering a wide range of topics, Scopus provided a more comprehensive coverage possibly due to its recognition among various researchers compared to Dimensions (Stahlschmidt and Stephen 2021). Figure 2 illustrates the summary of country-wise analysis for the research contribution according to bibliometric data extracted from (a) Scopus and, (b) Dimensions. The pie charts show the top 5 countries have contributed to more than 56% and 71% in Scopus and Dimensions, respectively, as compared to the rest of the world. It can also be inferred that China contributes to one of the highest number of articles along with the USA and Denmark. A significant contribution was also seen by scientists in countries like Germany, Korea, and France providing promising research outputs to the topic.
Keywords play an important role in evaluating the scope of the work as well as bringing out emerging and popular themes for the topic. The keywords “foods,” “proteins,” “beverages,” “agriculture,” “food safety,” “food pathogens” or “food processing” were given in addition to “lab-on-a-chip devices,” “lab-on-chip devices,” “lab on a chip” or “microfluidics” were used for the present study based on authors linguistic abilities. The minimum number of occurrences for a keyword was set to 10 words aiming for a robust keyword clustering analysis. Since a greater number of articles were retrieved using the Scopus database, it was used for further analysis and interpretations.
VOSviewer software was used to map the data from the Scopus database and presented using keyword cluster analysis (van Eck and Waltman 2010, 2017). Figure 3 illustrates the future themes formed along with the number of items (keywords) present based on data extracted from Scopus. In the network view, the color-coding depicts the number of similar areas and their links that collectively account for a theme. A total of 5 clusters were formed through keywords connecting to the topic of this study. For instance, Cluster I (red color) constituting 378 items highlight the themes protein synthesis, biosensing, and nanotechnology using keywords like “protein,” “nanofabrication,” “bioassay” and “metal nanoparticles.” Similarly, the keywords “cell migration,” “in-vitro study” or “stem cells” link specific areas in drug delivery and health care (Cluster II—Green color). The words “food safety,” “food analysis,” “food control” and “microbiology” clearly stated the trends in food technology occupying 115 items (Cluster III—blue color). In addition to these themes, importance was also given to genetic engineering (Cluster IV—yellow color) and the pathology (Cluster V—purple color).
The bibliometric mapping and analysis revealed rapid advancements in lab-on-a-chip technologies for food systems. Considering the above points, this review is structured to focus on the application of LOC technologies in various aspects of the food industry. Several fabrication techniques like photolithography, plotting, inkjet printing, laser printing, wax screen printing, and plasma oxidation used in the food industry have been highlighted. In addition, their food-related applications are discussed. Different fabricating materials and patterning agents with a focus on biopolymers have also been reviewed. The applications of LOC devices in practically relevant areas like food safety, processing, and packaging have been critically examined. The detection of pathogens and microorganisms in the area of food safety has been possible by using technologies like electrochemical, optical, colorimetric, chemiluminescence, and biological methods like polymerase chain reaction (PCR), which have been presented here. Further, the growing potential of such miniaturized devices in emulsion, food formulation, nutraceutical developments, radio frequency detection systems (RFID) scanning, and indicator techniques have been elucidated.
Several interesting review articles have been published with a major focus on the analysis of pathogens, mycotoxins, pesticide residues, and other contaminants for food safety applications (Choi et al. 2019; Nelis et al. 2020; Xu et al. 2020; Saravanan et al. 2021). The need of the hour lies in exploring deeper into the value of LOC devices in the food industry. The present study encompasses a broader scope in the food industry giving importance to advancements in lab-on-a-chip technology in the area of safety, processing, and packaging. The inferences from literature findings reported in the work could open opportunities for LOC devices in the food industry addressing key issues like food quality, adaptability, fabrication, and cost.
Fabrication and detection of lab-on-a-chip devices
Lab-on-a-chip devices hold promising platforms for on-site sample testing as they are easily portable. Figure 4 shows the characteristics of conventional techniques and lab-on-a-chip technology. They serve as efficient tools in rapid analysis for pathogen testing in laboratories. Additionally, these devices require only small reagent and sample volumes and generate minimal byproducts thus making them safe and cost-effective (Sri Sruthi et al. 2021). These devices could also be useful in minimizing quality-related issues before the material reaches the consumer (Moschou and Tserepi 2017).
Various LOC device fabrication methods have been explored for creating different flow patterns for controlled mixing and detection. The commonly used fabrication technologies in LOC development include photolithography (Phiphatanaphiphop et al. 2020), inkjet printing (Papamatthaiou et al. 2020), screen printing (Sitanurak et al. 2019), plasma oxidation (Wong et al. 2020), and laser treatment (Grist et al. 2012). Table 1 summarizes the chief features of various LOC device fabrication techniques and their food-related applications. The technologies work on the principle of fluid dynamics and can be categorized into active mixing (fluid flow by application of external force) and passive mixing (use of capillarity and geometrical features to drive the fluid flow) (Lee et al. 2016). Fluid flow parameters, fluid composition, mixing patterns, and device design features determine the overall efficiency of the microfluidic device (Calado et al. 2016).
In recent years, significant developments have been carried out to understand the mixing performance and improvements in device design. For instance, researchers created a low-cost 3D printed microfluidic device using a solvent bonding method of polymethyl methacrylate and acrylonitrile butadiene styrene (Duong and Chen 2019). The overall mixing efficiency achieved post optical transmission was 89% with a bonding strength of 8 bars. Similar studies were also investigated to understand the design parameters to fabricate a hybrid microfluidic mixer using finite element analysis. Mixing efficiency of 48–53% was achieved showing its potential for future iterations in additive manufacturing (Agarwal et al. 2020). Thus, the effective construction of devices based on samples acts as a pivot for determining the success of these microdevices.
Apart from fabrication methods, different patterning agents also play a critical role in device development. A variety of hydrophobic agents have been extensively studied. These range from expensive agents like photoresists to cheaper options like wax (Martinez et al. 2008). Table 2 gives a list of substrates used for performing LOC study in various foods samples. LOC studies commonly use polymer-based patterning agents due to their strong binding power and versatile characteristics. They are rigid, durable, and can generate high-resolution patterns. However, the fabrication of polymer-based LOCs is complicated and costly. Further, these devices require external energy using pumps for efficient transport of liquid and mixing. In contrast, paper-based devices have gained more interest recently due to the simplicity of the fabrication process, cost-effectiveness, and elimination of the need for pumps or any external devices for fluid transport (Hu and Lu 2020).
In recent years, a significant number of biopolymers like cellulose, chitin, and collagen have shown promising results as flexible substrates. Biodegradable fabricating materials have found applications in flexible edible food biosensors (Tao et al. 2012). Besides these, proteins and carbohydrates have also been tried for fabricating LOCs through pattern transfer from silicon substrates. For instance, collagen was taken to fabricate a strain temperature sensor using thermal techniques through a shadow mask (Moreno et al. 2015). However, key aspects of safety and regulatory measures should be considered for a potential scale-up.
The increased interest in designing and patterning techniques has led to advancements in detection, optimization, control, and efficiency improvements. For instance, a tree-shaped microfluidic device was designed and fabricated using paper and demonstrated for multiple analyte detection (Wang et al. 2010). The design gave a promising approach for colorimetric detection of protein to measure the concentration of analyte and color intensity with self-calibration. Another study showed the fabrication of a 3D printed acrylate-based polymer microchip using magnetic zinc–imidazole framework as an adsorbent. The portable device showed a dual approach in the simultaneous determination of total phenolic acids and flavonoids present in tea and honey samples with detection limits in the range of 0.04–0.10 µg/mL along with bioactive recovery rate 95.4–104.1% (Bagheri et al. 2021). Similar work has been done to develop a one-step approach with 3D wax printed paper-based device for glucose determination. The conclusions gave a strong linear relationship of R2 = 0.985 and resolution of 468 ± 72 µm with effective barrier properties, thus giving a better manufacturing approach for paper-based devices (Chiang et al. 2019). Although several iterations and feature additions are being done aiming to improve the microscale device efficiency, aspects on cost, convenience, pattern resolution, and scale-up are to be considered.
Application of lab-on-a-chip devices in the food industry
Food safety
With the increasing demand for nutritious meals, the safety of food plays a vital role in achieving balanced human health. Food safety refers to proper food preparation, management, handling, storage, and treatment to prevent any sort of contamination (Zhang et al. 2019). In recent years, there have been many cases of microorganisms, food poisoning, and adulteration causing harm to consumer health (Ellis et al. 2012; Bansal et al. 2017; Kong et al. 2017; El Sheikha 2019). External factors like allergens, physical contaminants, toxins, pesticides, and heavy metals are equal contributors and need to be removed for safe consumption.
Numerous analytical methods like high-performance liquid chromatography and gas chromatography have been evaluated to ensure the quality and safety of food. These technologies are well-established and provide high precision and sensitivity. Various technological approaches have been explored for food quality testing. Table 3 gives a detailed list of detection methods for improving the sensing capabilities in food samples. However, it is equally important for consumers to be aware of the quality and safety of the foods they consume.
Developments in different biosensing technologies play a fundamental role in implementing new sensors to ensure the safety and quality of foods. Various detection techniques have been employed aiming to combine complex technical advances onto a single platform. The most commonly used detection techniques involve enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) effective for detecting different kinds of pathogens and mainly used in agriculture and food industries. For instance, a study done in Manila, Philippines, showed the detection of Salmonella species in the meat where 57.64% was found to be contaminated post PCR testing (Santos et al. 2020). Similar studies were investigated for rapid detection of E. coli in beef using the ELISA method where the whole operation time for detection was less than 3 h (Zhao et al. 2020). In PCR, the target pathogen and genetic material are analyzed. The primers and enzymes are then added followed by parameter optimization by varying the temperatures, agitation, or operating cycles. The potential of target material is later detected using gel electrophoresis (Yoon and Kim 2012).
Table 4 shows a list of target groups that need to be considered for food safety. In recent years, non-conventional fabrication materials have been evaluated which showed improved characteristics and safety at a reduced cost. The selection of efficient materials plays an important role as they could aid in saving costs, environmental impact as well as provide better performance. However, these materials should deliver precise results within a shorter period as well as be portable (Dincer et al. 2019). Jokerst et al. developed a paper-based device for colorimetric detection of E. coli O157:H7, L. monocytogenes, and Salmonella in ready-to-eat meat products (Jokerst et al. 2012). The fabricated analytical device could detect concentrations as low as 101 colony forming unit (CFU)/mL in meat within 12 h or less in comparison with the standard detection methods. Chitosan reinforced with cellulose nanocrystals was also used for the detection of listeria monocytogenes in proteins using ELISA. After biopolymer optimization, the detection and safety characteristics improved by 17 to 24% (Etty et al. 2019). Thus, such techniques and fabrication materials give more accurate results overcoming the drawbacks.
The integration of nanotechnology has developed sensors in providing a significant enhancement to overall performance. For instance, techniques involving nano-biosensors using magnetic beads and quantum dots have gained a lot of interest in recent years (Mekkaoui et al. 2018; Moerland et al. 2019; Saadat et al. 2020). The portable device primarily includes two inlets, one outlet, and a detection source. The antibodies conjugated to the magnetic beads capture the analytes present in the sample and concentrate the target analytes. In the case of quantum dot labeling separation, the detection method takes place in three steps (reaction, washing, and isolation). Such technologies have shown promising approaches for selective detection of Salmonella in various foods (Kim et al. 2015). Magnetic-based sample separation using loop-mediated isothermal amplification for detection of Salmonella species in chicken breast has also provided merits (Kim et al. 2015). The quantum dot magnetic nanoparticles were water-soluble with high fluorescence properties effectively detecting S. Typhimurium and E. coli with the limit of detection of 103 CFU/mL for both. Similar magnetic bead-based integrated lab-on-chip systems were made for the separation of Salmonella species in food samples (Sun et al. 2015).
Another novel LOC technology was implemented by integrating electrokinetic magnetic bead-based assay which can moderate and inhibit the permitted mycotoxin level in infant foods. The technology was designed using a T-junction layout. An enzymatic reaction takes place on the application of an electric field driving the inner mixing of fluids for performing reactions. Simple low-cost magnetic actuators trap and move the beads within the microfluidic chamber providing more than 2.7-fold sensitivity enhancements compared to conventional systems (Berenguel-Alonso et al. 2014). The LOC approach has been shown to give more reliability in terms of ease of sample preparation, cost, and monitoring safety (Escarpa 2014).
The application of microfluidic devices has also kindled interest in digitalization mainly due to the ease of testing in a short duration (Balasubramanian et al. 2021). For instance, the use of smartphone-assisted LOC devices primarily involves performing the test using spot or lateral flow assay and positioning the detection zone for digital imaging (Ghosh et al. 2019). The strip is scanned using a smartphone and it captures the data accordingly. Colorimetric smartphone-based sensors deal with the complementary metal–oxide–semiconductor filters of phones to obtain red, green, and blue components of light. Thereby, changes in optical density are detected by giving light signals to the user for various experimental conditions (Ross et al. 2018). Smartphone-based sensing has shown promising potential for various foods like yogurt, egg, and milk (Zeinhom et al. 2018; Costa et al. 2020). When it comes to cost-effectiveness, different fabrication materials like glass, acrylic, polydimethylsiloxane, polysulfone, and hydrogels were investigated. However, paper-based analytical devices have rapidly progressed over the recent years as it poses a viable method for fast detection (Govindarajalu et al. 2019). These paper-based chips have been implemented for quantitative analysis in various food safety and quality applications (Chanu et al. 2020; Muthukumar et al. 2020).
Food production and processing
The food production industry is vital for human health. The global food production industry revolves around the following few major factors like economic growth, technological advancements, integration with electrical and communication technology as well as transportation (Sridhar et al. 2021a, b, c). Microfluidics and LOC devices represent a reliable technological system integrating multiple technologies like sensing and nanotechnology. These systems rely on the concept of a micrototal analysis system, which combines multiple analytical sensing systems into a single device converting chemical information to digital information (Guijt and Manz 2018). These systems give an edge over other conventional technologies in terms of rapid processing, least raw material requirement, and minimal space. Few developing food-related applications of these devices include emulsion processing, sensory analysis, and formulation as well as nutraceuticals.
Emulsion processing
The most simplified categorization of an emulsion is primarily oil in water (for example, mayonnaise) and water in oil (for example, butter) (Galus and Kadzińska 2015; He et al. 2020a). Generation of emulsion using conventional methods requires a tremendous amount of energy, mixing equipment, time, and raw material. Figure 5 shows the mechanism of conventional emulsion processing for different compounds and lab-on-a-chip-based approach in emulsion technology. An increased amount of energy is normally used up for the processing and denaturing of compounds during conventional emulsion processing. Non-thermal techniques like high-pressure homogenization and ultrasonic homogenization have been considered suitable processes for producing emulsions due to their stability, oil droplet dispersion, and high speed in obtaining results (Gharibzahedi et al. 2013; Wang et al. 2015). For instance, a study was done to investigate the stability of emulsions at different pressures (40, 80, and 120 MPa) using high-pressure homogenization. Pressure treatments showed an increase in emulsifying activity index from 56.93 to 87.68 m2/g and the stability index rise from 59.33 to 154.62 min. The process parameters were shown to improve the solubility from 16.5% to 75.1% producing a stable emulsion at 80 MPa (Cha et al. 2019).
Another study showed that both ultrasound and high-pressure treatment had a stable emulsion for more than 30 days post-processing making it feasible in improving the performance and estimating shelf life in the food and beverage industry (Li and Xiang 2019). In another study, a co-flowing step emulsification strategy was adopted for in-line control of microdroplets (Lian et al. 2019). The study considered a mathematical approach using computational fluid dynamics for analyzing droplet size, generation, and initial pressure as well as providing predictive equations. This allowed the devices to dispense liquid in a controlled manner consuming less energy during droplet mixing. Additionally, greater control over particle size distribution of emulsified particles with faster response time was achieved compared to conventional emulsion processing (Clegg et al. 2016).
Food formulation
LOC devices have paved the way for their usage in understanding food formulation and commercial food processing. The technology offers promise to overcome the challenges faced by various sensory experts and participants for analysis and study for different foods. For instance, a sensory evaluation technique involved 12 sensory panelists for the effective assessment of wine (Guld et al. 2020). Similar sensory and consumer studies were done for different foods namely soy sauce, olive oils, and soups (Yang and Lee 2019). These studies allow better prediction of descriptors that influence consumer acceptability, leading to product modifications. In contrast, rapid testing technologies require the least manpower and limited resources for functioning. In addition to these aspects, the tests are portable with easy operation and multiple reusability options (Romao et al. 2017). Further, it can be easily cleaned for better performance with precise results in a short duration. Although such techniques are in their early stages, they have a promising potential for a possible scale-up in the future.
A novel technology that extensively uses the concept of microfluidics and sensors is electric nose and electronic tongue testing. Figure 6 shows the comparison of the functioning of the human nose with an e-nose device. The former has the potential to measure different tastes using a pattern recognition system while the latter can detect different odors, flavors, and quality of foods simultaneously in the form of electrical or optical signals. The e-nose instrument has completely replaced the need for human interaction with foods thereby minimizing any microbiological risks. In addition, these instruments are reproducible, reliable, inexpensive, simple, fast, and can operate at very low levels (parts per billion) (Chilo 2016; Huang et al. 2019). Further, the integration of bioelectronics with olfactory research aid in significant improvements in rapid, sensitive quantitative assessments of odorant molecules (Lee and Park 2010).
The technology has been successfully applied to different foods like apple fruit and meat for determining the aroma profiles and freshness. Studies conducted on apples showed great variation in sourness, saltiness, and umami with the significant amount of esters and the presence of volatile compounds like hexyl butyrate and toluene (Zhu et al. 2020). Similar studies were evaluated to analyze the meat freshness (Weng et al. 2020). It is noteworthy to mention the most recent advancement of 3D printed chip technology. The technology can be used to print microchannels based on specific demands within few hours enabling rapid prototyping (Jamaledin et al. 2020).
Microneedles or patches then act as a pathway to transport the viscous materials or proteins through the nozzle onto the preparation tray. 3D printing has provided increasing interest among scientists and the commercial arena to manufacture food of different shapes and structures as per convenience by monitoring different printing variables. For instance, Derossi et al. investigated the effect of two printing factors, print speed, and flow level to manufacture a fruit-based formulation for young children (Derossi et al. 2017). The studies concluded a flow rate less than 70% and a print speed of 50 m/s would be ideal for preparing the formulation and restrict irregular structures and oversized porosities. Similar experiments were conducted to understand the textural properties and the variation in the structure of 3D printed processed cheese (Le et al. 2018). Thus, such research provides an insight on the customization of foods, personalized nutrition catering to consumer needs as well as in faster food packaging applications.
Recently, studies have also been undertaken on integrating artificial neural networks, machine learning, and computer vision with e-nose testing. Such e-nose technology coupled with artificial intelligence concept offers practical implementation in field conditions using sensor networks. These technologies have also been used in food samples like wines by modeling different parameters like amount of phenol, the concentration of berries, and consumer sensory tests as a function of time. The models showed a promising regression value ranging between 0.98 and 0.99 (Fuentes et al. 2020). Similar e-nose systems equipped with machine learning and neural network models have been used for aroma testing of different gas releases through sensors as a function of time in beer. The total sensor testing time was between 50 and 400 s producing regression values between 0.93 and 0.97 (Gonzalez Viejo et al. 2020). Thus, such technologies could form a path toward effective data recognition and analysis for understanding food formulation.
Nutraceutical development
With changing lifestyles, there is a growing need for diet-rich foods and supplements for maintaining body immunity and health. Developments are being carried in the application of LOCs for understanding the protein–polysaccharide interactions in the nutraceutical industry. The isolation of the food matrix, the interaction between bioactive compounds, and the determination of antioxidants and carotenoids have been widely explored (Bealer et al. 2020). As these compounds are difficult to isolate, innovative techniques through LOC-based technology by encapsulation or entrapment are being investigated to determine efficient nutrient deliveries (Sridhar et al. 2021b). During encapsulation, the particle size and wall material must be carefully considered. Vortex fluidic device (VFD) has been gaining a lot of interest in recent years due to its scalable, thin-film microfluidic flow process involving efficient mass transfer technique (He et al. 2019). The rotation of the tube kept at an angle provides efficient mixing between the two products. Figure 7 shows a schematic of a VFD device with two sample inlets with one outlet. The application of this concept has been shown to reduce the processing time of raw milk pasteurization from 30 to 10 min. In recent years, the technique has also been widely applied in fish oil encapsulation and for the rapid processing of biologically active proteins (Luo et al. 2016; He et al. 2020b).
Although studies using VFD for food production and processing are scarce, a lot of scope lies in the effective scale-up of this technique due to low cost and easy operation. The cost of LOC devices ranges between $ 15,000–$ 17,000 compared to $ 150,000 for a high-pressure microfluidic device (He et al. 2020a). The VFD technology has also been successfully implemented for enzymatic hydrolysis of milk protein from 3 h to 20 min and pasteurization time from 30 to 10 min thereby suggesting its high potential (He et al. 2019).
Food packaging
Product packaging development primarily runs on four basic functions: protection, communication, convenience, and containment (Yam 2005). Food packaging is primarily done to protect food from any sort of contamination and maintain the desired quality. Excessive water through condensation, oxidation, and microbial growth are the major causes of deterioration of food quality leading to foodborne illnesses. Although traditional packaging has contributed massively to early development, it is no longer sufficient to satisfy the complex and evolving consumer needs. Consumers demand food that is safe, diet rich, attractive, and healthy. Rapid advancements have been carried out in packaging technology introducing the concept of smart packaging, time–temperature-based indicators, gas sensors, and absorbers as well as RFID systems.
Smart packaging system
Smart packaging devices are small inexpensive labels or tags that are attached to the main package (pouches, trays, labs, bottles, and caps). They work on the principle of collecting, storing, and transmitting data. These devices are generally connected to a host computer where data recording is done for traceability purposes. For instance, miniature stick packaging integrated with a pressure-controlled seal serves as an effective technology for foods containing high moisture as well as aids in determining shelf life (Van Oordt et al. 2011). The study revealed an adjustment of pressure between 20 and 100 kPa showed promising results for a low-cost mass production system. Similar food packaging wraps were developed by printing DNAzyme probe to a cyclo-olefin polymer film (Yousefi et al. 2018). The flexible fabricated wrap has the potential to generate a fluorescence signal when a target bacterium like E. coli comes in contact with the wrapping film. The biosensor was successfully tested for E. coli in meat and apple juice for concentrations as low as 103 CFU/mL at pH 3–9 up to 14 days.
Radio frequency identification tags
Radio frequency identification (RFID) is an advanced form of carrying data for product identification and traceability. The tags are generally put for easier tracking of items. In recent years, they have broadened their application in providing nutrient information of the specific packaged product. Figure 8 shows the application of RFID technology for product identification. In a typical RFID system, the reader emits radio frequency waves on the food commodity to capture the data. This data is transferred to the tag which is connected to the main server. The user then checks the server for analysis and decision-making (Zheng et al. 2020). An ideal RFID tag works on a small microchip with a tiny antenna for transferring signals to the user (Reyes et al. 2013; Gillenson 2019).
The technology has proven advantageous as compared to traditional barcode scanners. For instance, it can store larger amounts of data (more than 1 megabyte), provides real-time information, and does not require a specific site area for scanning as compared to barcodes (Chen and Tu 2009). In recent years, a displacement and tilt detection method has been found using a passive ultra-high-frequency RFID reader. The novel method uses high-frequency waves to measure the phase variation and tag response using the polarized reader. The results showed displacement less than 2 mm and a tilt angle of 2.5° and 500 mm working range would be the ideal conditions for detection (Lai et al. 2018). Similar fabrication studies were done combining RFID with microfluidics and inkjet printing technology for sensing contaminants in the fluid. The low-cost and rapid microfluidic RFID device showed promising results as it could detect less than 1% water adulteration in alcohol samples (Cook et al. 2013). Thus, the concept has gained a growing interest in retail centers, food industries, supply chains (Wang et al. 2019; Alfian et al. 2020), health care (Hariraj and Selvarajah 2020), and security controls (Khalil et al. 2019).
In recent years, technology with the concept of the Internet of Things (IoT) has introduced the idea of “smart shopping” where an RFID chip is attached to smart carts and shelves. The technology involves an artificial intelligence approach where the cart saves all the selected goods and produces the bill by updating it on the LCD screen of the shopping cart thus removing any human intervention (Hussien et al. 2020). Similar RFID-based systems compiled with machine learning models have been developed for better sensing of tagged products in perishable foods, which move through the gates thus improving traceability and efficiency (Alfian et al. 2020).
Indicators
Indicators are small miniaturized self-adhesive labels attached to food packages and containers. These special labels show visual indications using sensors for maintaining the required temperature or giving a warning through a color change (freshness indicators). There are three major classes of indicators; gas indicators, freshness indicators, and time–temperature indicators (Vanderroost et al. 2014). Table 5 shows the characteristics of different types of indicators used in the food industry. These technologies have gained continuous up-gradation in the information and communication technology sector. Systems like wireless networks, mobile phones, touch screens, and global positioning systems play a key role in making up the IoT. The concept of “making products smart” has increased the use of temperature/freshness or gas-based indicators for ensuring efficient delivery as well as food safety across the supply chain to meet the consumer standards (Maksimović et al. 2015).
There has been a growing interest in recent times in developing irreversible spoilage sensors for foods. For instance, Liu et al. developed an irreversible food sensor that shows halochromic behavior toward amines and volatile compounds in seafood, meat products, and protein-based foods (Liu et al. 2020). Similar rapid indicator systems with single-cell detection methods were developed to analyze foodborne pathogens (Salmonella contamination) in milk samples. The results showed a detection limit of 50 CFU/mL with fluorescence-based pathogen identification within 5 h (An et al. 2020). Experiments on polymer-based flexible strain sensors with visual LED indicators were also fabricated for providing an effective packaging system. The light intensity (maximum brightness = 67 lx) decreased as spoilage was observed in the food package (Escobedo et al. 2020). Thus, such technologies can form an initial path for detection ensuring greater food safety and public health.
Challenges
Significant advancements have taken place in the area of LOC devices and their application in the food industry. A bibliometric analysis is conducted to evaluate the scope and progress of lab-on-a-chip devices in different areas. The review emphasizes the recent developments in the potential of LOCs in the food industry in specific areas of food safety, production, processing, and packaging. Food fraud along with microbial contamination has instilled the need for better safety standards and improved practices. However, as of today, the system still lacks traceability and transparency. Although continuous improvements through revised policies are being implemented by regulatory authorities such as Food and Drug Administration, more intensive monitoring across the entire supply chain is required. The research findings in our study point toward the integration of detection techniques with information and communication technology.
Smartphone-based sensors pose an excellent option for portable analysis as they can instantly acquire data, analyze and store results. Such sensors, if installed along the production line, could help detect contaminants at specific stages. Nanotechnology could offer a possible path for development of precise and accurate sensors by facilitating design of novel materials and enabling selective surface modification. In recent years, materials like graphite, graphene (Shahdeo et al. 2020; Bauer et al. 2021), carbon nanotubes (Sobhan et al. 2020), and chitosan (Lin et al. 2020) have shown promising results for the development of lab-on-a-chip devices and their scale-up. Further, scale-out strategies must also be explored to achieve higher throughput in production.
However, challenges like mass-scale production and user acceptability still need to be considered before they arrive in the market. A systematic investigation needs to be done in choosing analytes, dosages, material as well as fabrication approaches. Improvements in developing re-usable sensors for production and safety testing could be one of the possible ways forward. More importance should be given to device performance, its integration in food processing lines as well as testing standards for it to become commercially available. Lab-on-a-chip devices should also be combined with strategies for valorization and agricultural and food waste for integrated technological solutions in environmental protection (Ponnuchamy et al. 2020). Lab-on-a-chip technology has potential to play a major role in facilitating end-to-end traceability throughout the food production chain.
Conclusion
The promising potential of the lab-on-a-chip sensing technique has given an attractive option for rapid detection with minimal sample and reagent volumes. The review discusses the few most promising applications of chips in the food industry. The innovative fabrication techniques along with advancements in materials and design aspects could be beneficial for the development of advanced micrototal analysis systems. Other prospective uses of lab-on-a-chip systems in foods, which were not discussed but are not limited to, include nano-encapsulated nutrient delivery, security inks, or nano-barcodes to protect against counterfeiting as well as analyzing gut microbiota profiles using chips. In addition to continuous technology advancements, equal importance on marketing, public satisfaction and adequate support from the government would help in the successful implementation of these applications. It is needless to mention that these microscale devices could drastically save time, as well as bring high efficiency to the current systems if a constant dialogue is maintained between the scientists and companies who purchase them. These benefits could ultimately make an efficient food supply chain, reduce wastage, and ensure the safety of food products for consumption.
Abbreviations
- CFU:
-
Colony forming unit
- DNA:
-
Deoxyribonucleic acid
- ELISA:
-
Enzyme-linked immunosorbent assay
- IoT:
-
Internet of Things
- LOC:
-
Lab-on-a-chip
- PCR:
-
Polymerase chain reaction
- RFID:
-
Radio frequency identification
- VFD:
-
Vortex fluidic device
References
Agarwal A, Salahuddin A, Wang H, Ahamed MJ (2020) Design and development of an efficient fluid mixing for 3D printed lab-on-a-chip. Microsyst Technol 26:2465–2477. https://doi.org/10.1007/s00542-020-04787-9
Ahn H, Batule BS, Seok Y, Kim MG (2018) Single-Step recombinase polymerase amplification assay based on a paper chip for simultaneous detection of multiple foodborne pathogens. Anal Chem 90:10211–10216. https://doi.org/10.1021/acs.analchem.8b01309
Al Mughairy B, Al-Lawati HAJ (2020) Recent analytical advancements in microfluidics using chemiluminescence detection systems for food analysis. TrAC - Trends Anal Chem 124:115–802. https://doi.org/10.1016/j.trac.2019.115802
Alfian G, Syafrudin M, Farooq U et al (2020) Improving efficiency of RFID-based traceability system for perishable food by utilizing IoT sensors and machine learning model. Food Control 110:1–30. https://doi.org/10.1016/j.foodcont.2019.107016
Al-Kahtani HA, Ismail EA, Asif Ahmed M (2017) Pork detection in binary meat mixtures and some commercial food products using conventional and real-time PCR techniques. Food Chem 219:54–60. https://doi.org/10.1016/j.foodchem.2016.09.108
Amicarelli V, Bux C, Lagioia G (2020) How to measure food loss and waste? A material flow analysis application. Br Food J 123:67–85. https://doi.org/10.1108/BFJ-03-2020-0241
Amor-Gutiérrez O, Costa-Rama E, Fernández-Abedul MT (2019) Sampling and multiplexing in lab-on-paper bioelectroanalytical devices for glucose determination. Biosens Bioelectron 135:64–70. https://doi.org/10.1016/j.bios.2019.04.006
An X, Zuo P, Ye BC (2020) A single cell droplet microfluidic system for quantitative determination of food-borne pathogens. Talanta 209:120–571. https://doi.org/10.1016/j.talanta.2019.120571
Ashley J, D’Aurelio R, Piekarska M et al (2018) Development of a β-Lactoglobulin sensor based on SPR for milk allergens detection. Biosensors 8:1–11. https://doi.org/10.3390/bios8020032
Bagheri N, Al Lawati HAJ, Hassanzadeh J (2021) Simultaneous determination of total phenolic acids and total flavonoids in tea and honey samples using an integrated lab on a chip device. Food Chem 342:128–338. https://doi.org/10.1016/j.foodchem.2020.128338
Balasubramanian S, Udayabhanu A, Kumar PS et al (2021) Digital colorimetric analysis for estimation of iron in water with smartphone-assisted microfluidic paper-based analytical devices. Int J Environ Anal Chem. https://doi.org/10.1080/03067319.2021.1893711
Bansal S, Singh A, Mangal M et al (2017) Food adulteration: sources, health risks, and detection methods. Crit Rev Food Sci Nutr 57:1174–1189. https://doi.org/10.1080/10408398.2014.967834
Bauer M, Wunderlich L, Weinzierl F et al (2021) Electrochemical multi-analyte point-of-care perspiration sensors using on-chip three-dimensional graphene electrodes. Anal Bioanal Chem 413:763–777. https://doi.org/10.1007/s00216-020-02939-4
Bealer EJ, Onissema-karimu S, Rivera-galletti A et al (2020) Protein polysaccharide composite materials. Polym (Basel) 12:1–28. https://doi.org/10.3390/polym12020464
Berenguel-Alonso M, Granados X, Faraudo J et al (2014) Magnetic actuator for the control and mixing of magnetic bead-based reactions on-chip. Anal Bioanal Chem 406:6607–6616. https://doi.org/10.1007/s00216-014-8100-5
Bhalla N, Pan Y, Yang Z, Payam AF (2020) Opportunities and challenges for biosensors and nanoscale analytical tools for pandemics: COVID-19. ACS Nano 14:7783–7807. https://doi.org/10.1021/acsnano.0c04421
Bordbar MM, Nguyen TA, Arduini F, Bagheri H (2020) A paper-based colorimetric sensor array for discrimination and simultaneous determination of organophosphate and carbamate pesticides in tap water, apple juice, and rice. Microchim Acta 187:1–13. https://doi.org/10.1007/s00604-020-04596-x
Bouguelia S, Roupioz Y, Slimani S et al (2013) On-chip microbial culture for the specific detection of very low levels of bacteria. Lab Chip 13:4024–4032. https://doi.org/10.1039/c3lc50473e
Brazey B, Cottet J, Bolopion A et al (2018) Impedance-based real-time position sensor for lab-on-a-chip devices. Lab Chip 18:818–831. https://doi.org/10.1039/c7lc01344b
Calado B, dos Santos A, Semiao V (2016) Characterization of the mixing regimes of Newtonian fluid flows in asymmetrical T-shaped micromixers. Exp Therm Fluid Sci 72:218–227. https://doi.org/10.1016/j.expthermflusci.2015.11.010
Cha Y, Shi X, Wu F et al (2019) Improving the stability of oil-in-water emulsions by using mussel myofibrillar proteins and lecithin as emulsifiers and high-pressure homogenization. J Food Eng 258:1–8. https://doi.org/10.1016/j.jfoodeng.2019.04.009
Chaiyo S, Siangproh W, Apilux A, Chailapakul O (2015) Highly selective and sensitive paper-based colorimetric sensor using thiosulfate catalytic etching of silver nanoplates for trace determination of copper ions. Anal Chim Acta 866:75–83. https://doi.org/10.1016/j.aca.2015.01.042
Chanu OR, Kapoor A, Karthik V (2020) Digital image analysis for microfluidic paper based pH sensor platform. Mater Today Proc 40:S64–S68. https://doi.org/10.1016/j.matpr.2020.03.503
Chen RS, Tu M (2009) Development of an agent-based system for manufacturing control and coordination with ontology and RFID technology. Expert Syst Appl 36:7581–7593. https://doi.org/10.1016/j.eswa.2008.09.068
Chen S, Zhang Y, Li H et al (2014) Differentiation of fish species in Taiwan Strait by PCR-RFLP and lab-on-a-chip system. Food Control 44:26–34. https://doi.org/10.1016/j.foodcont.2014.03.019
Chiang CK, Kurniawan A, Kao CY, Wang MJ (2019) Single step and mask-free 3D wax printing of microfluidic paper-based analytical devices for glucose and nitrite assays. Talanta 194:837–845. https://doi.org/10.1016/j.talanta.2018.10.104
Chilo J (2016) E-nose application to food industry production. IEE Instrum Meas 19:27–33. https://doi.org/10.1109/MIM.2016.7384957
Choi JR, Yong KW, Choi JY, Cowie AC (2019) Emerging point-of-care technologies for food safety analysis. Sens (Switzerland) 19:1–31. https://doi.org/10.3390/s19040817
Clegg PS, Tavacoli JW, Wilde PJ (2016) One-step production of multiple emulsions: microfluidic, polymer-stabilized and particle-stabilized approaches. Soft Matter 12:998–1008. https://doi.org/10.1039/c5sm01663k
Cook BS, Cooper JR, Tentzeris MM (2013) An inkjet-printed microfluidic rfid-enabled platform for wireless lab-on-chip applications. IEEE Trans Microw Theory Tech 61:4714–4723. https://doi.org/10.1109/TMTT.2013.2287478
Costa RA, Morais CLM, Rosa TR et al (2020) Quantification of milk adulterants (starch, H2O2, and NaClO) using colorimetric assays coupled to smartphone image analysis. Microchem J 156:104968. https://doi.org/10.1016/j.microc.2020.104968
Das C, Chakraborty S, Karmakar A, Chattopadhyay S (2018) On-chip detection and quantification of soap as an adulterant in milk employing electrical impedance spectroscopy. 2018 Int Symp Devices. Circuits Syst ISDCS 2018:1–4. https://doi.org/10.1109/ISDCS.2018.8379634
Deng D, Lin Q, Li H et al (2019) Rapid detection of malachite green residues in fish using a surface-enhanced Raman scattering-active glass fiber paper prepared by in situ reduction method. Talanta 200:272–278. https://doi.org/10.1016/j.talanta.2019.03.021
Derossi A, Caporizzi R, Azzollini D, Severini C (2017) Application of 3D printing for customized food. A case on the development of a fruit-based snack for children. J Food Eng 220:65–75. https://doi.org/10.1016/j.jfoodeng.2017.05.015
Dincer C, Bruch R, Costa-Rama E et al (2019) Disposable sensors in diagnostics, food, and environmental monitoring. Adv Mater 31:1–28. https://doi.org/10.1002/adma.201806739
Dooley JJ, Sage HD, Brown HM, Garrett SD (2005) Improved fish species identification by use of lab-on-a-chip technology. Food Control 16:601–607. https://doi.org/10.1016/j.foodcont.2004.06.022
Duong LH, Chen PC (2019) Simple and low-cost production of hybrid 3D-printed microfluidic devices. Biomicrofluidics 13:1–11. https://doi.org/10.1063/1.5092529
El Sheikha AF (2019) DNAFoil: novel technology for the rapid detection of food adulteration. Trends Food Sci Technol 86:544–552. https://doi.org/10.1016/j.tifs.2018.11.012
Ellis DI, Brewster VL, Dunn WB et al (2012) Fingerprinting food: current technologies for the detection of food adulteration and contamination. Chem Soc Rev 41:5706–5727. https://doi.org/10.1039/c2cs35138b
Escarpa A (2014) Lights and shadows on Food Microfluidics. Lab Chip 14:3213–3224. https://doi.org/10.1039/c4lc00172a
Escobedo P, Bhattacharjee M, Nikbakhtnasrabadi F, Dahiya R (2020) Flexible Strain Sensor with NFC Tag for Food Packaging FLEPS 2020 - IEEE Int Conf Flex Printable Sensors Syst, 9781728152:16–19. Doi: https://doi.org/10.1109/FLEPS49123.2020.9239568
Etty MC, D’Auria S, Shankar S et al (2019) New immobilization method of anti-PepD monoclonal antibodies for the detection of Listeria monocytogenes p60 protein – Part B: Rapid and specific sandwich ELISA using antibodies immobilized on a chitosan/CNC film support. React Funct Polym 143:104317. https://doi.org/10.1016/j.reactfunctpolym.2019.104317
Fernández-Abedul MT (2021) Paper based sensors. Anal Bioanal Chem 413:3143–3144. https://doi.org/10.1007/s00216-021-03277-9
Fernández-Ramos MD, Ogunneye AL, Barbarinde NAA et al (2020) Bioactive microfluidic paper device for pesticide determination in waters. Talanta 218:121108. https://doi.org/10.1016/j.talanta.2020.121108
Franek M, Rubio D, Diblikova I, Rubio F (2014) Analytical evaluation of a high-throughput enzyme-linked immunosorbent assay for acrylamide determination in fried foods. Talanta 123:146–150. https://doi.org/10.1016/j.talanta.2014.02.007
Fuentes S, Summerson V, Viejo CG et al (2020) Assessment of smoke contamination in grapevine berries and taint in wines due to bushfires using a low-cost e-nose and an artificial intelligence approach. Sens (Switzerland) 20:1–15. https://doi.org/10.3390/s20185108
Galus S, Kadzińska J (2015) Food applications of emulsion-based edible films and coatings. Trends Food Sci Technol 45:273–283. https://doi.org/10.1016/j.tifs.2015.07.011
Gharaghani FM, Akhond M, Hemmateenejad B (2020) A three-dimensional origami microfluidic device for paper chromatography: Application to quantification of Tartrazine and Indigo carmine in food samples. J Chromatogr A 1621:461049. https://doi.org/10.1016/j.chroma.2020.461049
Gharibzahedi SMT, Razavi SH, Mousavi SM (2013) Ultrasound-assisted formation of the canthaxanthin emulsions stabilized by arabic and xanthan gums. Carbohydr Polym 96:21–30. https://doi.org/10.1016/j.carbpol.2013.03.085
Ghasemi A, Amiri H, Zare H et al (2017) Carbon nanotubes in microfluidic lab-on-a-chip technology: current trends and future perspectives. Microfluid Nanofluidics 21:1–19. https://doi.org/10.1007/s10404-017-1989-1
Ghosh R, Vaishampayan V, Mahapatra A et al (2019) Enhancement of limit of detection by inducing coffee-ring effect in water quality monitoring microfluidic paper-based devices. Desalin Water Treat 156:316–322. https://doi.org/10.5004/dwt.2019.23715
Ghosh S, Aggarwal K, Ahn CH (2020) A new mobile healthcare system using smartphone and lab-on-a-chip for on-site diagnostics of malaria. 21st Int Conf Miniaturized Syst Chem Life Sci MicroTAS 2017 1:233–234
Gillenson ML (2019) I’ve got you under my skin: The past, present and future use of RFID technology in people and animals. J Inf Technol Manag 30:19–29
Gonzalez Viejo C, Fuentes S, Godbole A et al (2020) Development of a low-cost e-nose to assess aroma profiles: An artificial intelligence application to assess beer quality. Sens Actuat, B Chem 308:127688. https://doi.org/10.1016/j.snb.2020.127688
Govindarajalu AK, Ponnuchamy M, Sivasamy B et al (2019) A cellulosic paper-based sensor for detection of starch contamination in milk. Bull Mater Sci 42:1–6. https://doi.org/10.1007/s12034-019-1958-2
Grist S, Oyunerdene N, Flueckiger J et al (2012) Fabrication and laser patterning of polystyrene optical oxygen sensor films for lab-on-a-chip applications. RSC Adv 139:5718–5727. https://doi.org/10.1039/C4AN00765D
Guijt RM, Manz A (2018) Miniaturised total chemical-analysis systems (ΜTAS) that periodically convert chemical into electronic information. Sens Actuat, B Chem 273:1334–1345. https://doi.org/10.1016/j.snb.2018.06.054
Guld Z, Nyitrainé Sárdy D, Gere A, Rácz A (2020) Comparison of sensory evaluation techniques for Hungarian wines. J Chemom 34:1–15. https://doi.org/10.1002/cem.3219
Guo L, Feng J, Fang Z et al (2015) Application of microfluidic “lab-on-a-chip” for the detection of mycotoxins in foods. Trends Food Sci Technol 46:252–263. https://doi.org/10.1016/j.tifs.2015.09.005
Hariraj S, Selvarajah V (2020) Implementation of rfid technology in managing health information in a hospital. Int J Curr Res Rev 12:177–182. https://doi.org/10.31782/IJCRR.2020.122029
He S, Joseph N, Luo X, Raston CL (2019) Vortex fluidic mediated food processing. PLoS ONE 14:1–12. https://doi.org/10.1371/journal.pone.0216816
He S, Joseph N, Feng S et al (2020a) Application of microfluidic technology in food processing. Food Funct 11:5726–5737. https://doi.org/10.1039/d0fo01278e
He S, Joseph N, Mirzamani M et al (2020) Vortex fluidic mediated encapsulation of functional fish oil featuring in situ probed small angle neutron scattering. Npj Sci Food 4:1–11. https://doi.org/10.1038/s41538-020-00072-1
He T, Li J, Liu L et al (2020c) Origami-based “book” shaped three-dimensional electrochemical paper microdevice for sample-to-answer detection of pathogens. RSC Adv 10:25808–25816. https://doi.org/10.1039/d0ra03833d
Hong W, Jeong SG, Shim G et al (2018) Improvement in the reproducibility of a paper-based analytical device (PAD) using stable covalent binding between proteins and cellulose paper. Biotechnol Bioprocess Eng 23:686–692. https://doi.org/10.1007/s12257-018-0430-2
Hou Y, Cai G, Zheng L, Lin J (2019) A microfluidic signal-off biosensor for rapid and sensitive detection of Salmonella using magnetic separation and enzymatic catalysis. Food Control 103:186–193. https://doi.org/10.1016/j.foodcont.2019.04.008
Hu Y, Lu X (2020) Rapid pomegranate juice authentication using a simple sample-to-answer hybrid paper/polymer-based lab-on-a-chip device. ACS Sens 5:2168–2176. https://doi.org/10.1021/acssensors.0c00786
Huang X, Yu S, Xu H et al (2019) Rapid and nondestructive detection of freshness quality of postharvest spinaches based on machine vision and electronic nose. J Food Saf 39:1–8. https://doi.org/10.1111/jfs.12708
Hussien NA, Alsaidi SAAA, Ajlan IK et al (2020) Smart shopping system with RFID technology based on internet of things. Int J Interact Mob Technol 14:17–29. https://doi.org/10.3991/ijim.v14i04.13511
Jamaledin R, Di Natale C, Onesto V et al (2020) Progress in microneedle-mediated protein delivery. J Clin Med 9:542. https://doi.org/10.3390/jcm9020542
Jokerst JC, Adkins JA, Bisha B et al (2012) Development of a paper-based analytical device for colorimetric detection of select foodborne pathogens. Anal Chem 84:2900–2907. https://doi.org/10.1021/ac203466y
Kasoju A, Shahdeo D, Khan AA et al (2020) Fabrication of microfluidic device for Aflatoxin M1 detection in milk samples with specific aptamers. Sci Rep 10:1–8. https://doi.org/10.1038/s41598-020-60926-2
Khalil G, Doss R, Chowdhury M (2019) A comparison survey study on RFID based anti-counterfeiting systems. J Sens Actuator Netw 8:1–15. https://doi.org/10.3390/jsan8030037
Khnouf R, Chapman B, Jin S et al (2015) Detection of ricin in beverages using cell-free protein synthesis in a microfluidic device. Sens Actuat B Chem 221:723–729. https://doi.org/10.1016/j.snb.2015.06.077
Kim G, Moon J, Moh C, Lim J (2015) A micro fluidic nano-biosensor for the detection of pathogenic Salmonella. Biosens Bioelectron 67:243–247. https://doi.org/10.1016/j.bios.2014.08.023
Kim J, Campbell AS, de Ávila BEF, Wang J (2019) Wearable biosensors for healthcare monitoring. Nat Biotechnol 37:389–406. https://doi.org/10.1038/s41587-019-0045-y
Kong X, Squire K, Chong X, Wang AX (2017) Ultra-sensitive lab-on-a-chip detection of Sudan I in food using plasmonics-enhanced diatomaceous thin film. Food Control 79:258–265. https://doi.org/10.1016/j.foodcont.2017.04.007
Kumar Y (2021) Isothermal amplification-based methods for assessment of microbiological safety and authenticity of meat and meat products. Food Control 121:107679. https://doi.org/10.1016/j.foodcont.2020.107679
Kuswandi B (2017) Freshness Sensors for Food Packaging. https://doi.org/10.1016/B978-0-08-100596-5.21876-3
Lai X, Cai Z, Xie Z, Zhu H (2018) A novel displacement and tilt detection method using passive UHF RFID technology. Sens (Switzerland) 18:1–14. https://doi.org/10.3390/s18051644
Le C, Sullivan JJO, Drapala KP et al (2018) Effect of 3D printing on the structure and textural properties of processed cheese. J Food Eng 220:56–64. https://doi.org/10.1016/j.jfoodeng.2017.02.003
Lee SH, Park TH (2010) Recent advances in the development of bioelectronic nose. Biotechnol Bioprocess Eng 15:22–29. https://doi.org/10.1007/s12257-009-3077-1
Lee CY, Wang WT, Liu CC, Fu LM (2016) Passive mixers in microfluidic systems: a review. Chem Eng J 288:146–160. https://doi.org/10.1016/j.cej.2015.10.122
Li Y, Xiang D (2019) Stability of oil-in-water emulsions performed by ultrasound power or high-pressure homogenization. PLoS ONE 14:1–14. https://doi.org/10.1371/journal.pone.0213189
Li X, Ballerini DR, Shen W (2012) A perspective on paper-based microfluidics: current status and future trends. Biomicrofluidics 6:1–14. https://doi.org/10.1063/1.3687398
Li Y, Liu Y, Kim E et al (2018) Electrodeposition of a magnetic and redox-active chitosan film for capturing and sensing metabolic active bacteria. Carbohydr Polym 195:505–514. https://doi.org/10.1016/j.carbpol.2018.04.096
Lian J, Zheng S, Liu C et al (2019) Investigation of microfluidic co-flow effects on step emulsification: wall contact angle and critical dimensions. Coll Surf A Physicochem Eng Asp 580:123733. https://doi.org/10.1016/j.colsurfa.2019.123733
Lin CT, Kuo SH, Lin PH et al (2020) Hand-powered centrifugal microfluidic disc with magnetic chitosan bead-based ELISA for antibody quantitation. Sens Actuat, B Chem 316:1–10. https://doi.org/10.1016/j.snb.2020.128003
Liu W, Guo Y, Luo J et al (2015) A molecularly imprinted polymer based a lab-on-paper chemiluminescence device for the detection of dichlorvos. Spectrochim Acta - Part A Mol Biomol Spectrosc 141:51–57. https://doi.org/10.1016/j.saa.2015.01.020
Liu B, Gurr PA, Qiao GG (2020) Irreversible spoilage sensors for protein-based food. ACS Sens 5:2903–2908. https://doi.org/10.1021/acssensors.0c01211
Luo X, Smith P, Raston CL, Zhang W (2016) Vortex fluidic device-intensified aqueous two phase extraction of C-phycocyanin from spirulina maxima. ACS Sustain Chem Eng 4:3905–3911. https://doi.org/10.1021/acssuschemeng.6b00756
Ma Y, Mao Y, Huang D et al (2016) Portable visual quantitative detection of aflatoxin B1 using a target-responsive hydrogel and a distance-readout microfluidic chip. Lab Chip 16:3097–3104. https://doi.org/10.1039/c6lc00474a
Maddipatla D, Narakathu BB, Ochoa M et al (2019) Rapid prototyping of a novel and flexible paper based oxygen sensing patch via additive inkjet printing process. RSC Adv 9:22695–22704. https://doi.org/10.1039/c9ra02883h
Maksimović M, Vujović V, Omanović-Mikličanin E (2015) Application of internet of things in food packaging and transportation. Int J Sustain Agric Manag Inform 1:333–350. https://doi.org/10.1504/IJSAMI.2015.075053
Mark D, Haeberle S, Roth G et al (2010) Microfluidic lab-on-a-chip platforms: requirements, characteristics and applications. Chem Soc Rev 39:1153–1182. https://doi.org/10.1039/b820557b
Marquez S, Liu J, Morales-Narváez E (2019) Paper-based analytical devices in environmental applications and their integration with portable technologies. Curr Opin Environ Sci Heal 10:1–8. https://doi.org/10.1016/j.coesh.2019.08.002
Martinez AW, Phillips ST, Wiley BJ et al (2008) FLASH: a rapid method for prototyping paper-based microfluidic devices. Lab Chip 8:2146–2150. https://doi.org/10.1039/b811135a
Mekkaoui S, Le Roy D, Audry MC et al (2018) Arrays of high aspect ratio magnetic microstructures for large trapping throughput in lab-on-chip systems. Microfluid Nanofluidics 22:1–10. https://doi.org/10.1007/s10404-018-2141-6
Min J, Kim J-H, Kim S (2004) Microfluidic device for bio analytical systems. Biotechnol Bioprocess Eng 9:100–106. https://doi.org/10.1007/BF02932991
Moerland CP, Van Ijzendoorn LJ, Prins MWJ (2019) Rotating magnetic particles for lab-on-chip applications-a comprehensive review. Lab Chip 19:919–933. https://doi.org/10.1039/C8LC01323C
Moreno S, Baniasadi M, Mohammed S et al (2015) Biocompatible collagen films as substrates for flexible implantable electronics. Adv Electron Mater 1:1–8. https://doi.org/10.1002/aelm.201500154
Moschou D, Tserepi A (2017) The lab-on-PCB approach: tackling the μTAS commercial upscaling bottleneck. Lab Chip 17:1388–1405. https://doi.org/10.1039/c7lc00121e
Moya A, Gabriel G, Villa R, Javier del Campo F (2017) Inkjet-printed electrochemical sensors. Curr Opin Electrochem 3:29–39. https://doi.org/10.1016/j.coelec.2017.05.003
Muthukumar R, Kapoor A, Balasubramanian S et al (2020) Detection of adulteration in sunflower oil using paper-based microfluidic lab-on-a-chip devices. Mater Today Proc 34:496–501. https://doi.org/10.1016/j.matpr.2020.03.099
Nagabooshanam S, Sharma S, Roy S et al (2020) Development of field deployable sensor for detection of pesticide from food chain. IEEE Sens J XX 21:4129–4134. https://doi.org/10.1109/jsen.2020.3030034
Nelis JLD, Tsagkaris AS, Dillon MJ et al (2020) Smartphone-based optical assays in the food safety field. TrAC - Trends Anal Chem 129:1–13. https://doi.org/10.1016/j.trac.2020.115934
Nie J, Zhang Y, Lin L et al (2012) Low-cost fabrication of paper-based microfluidic devices by one-step plotting. Anal Chem 84:6331–6335. https://doi.org/10.1021/ac203496c
Oliveira TMBF, Fátima Barroso M, Morais S et al (2013) Biosensor based on multi-walled carbon nanotubes paste electrode modified with laccase for pirimicarb pesticide quantification. Talanta 106:137–143. https://doi.org/10.1016/j.talanta.2012.12.017
Oliverira (2015) Mobile health technologies: Methods and protocols. Mob Heal Technol Methods Protoc 1256:1–496. https://doi.org/10.1007/978-1-4939-2172-0
Van Oordt T, Barb Y, Zengerle R, Von Stetten F (2011) Miniature stick-packaging - An industrial technology for pre-storage and release of reagents in lab-on-a-chip systems. 15th Int Conf Miniaturized Syst Chem Life Sci 2011, MicroTAS 2011 1:437–439 https://doi.org/10.1039/C3LC50404B
Orduña-Malea E, López-Cózar ED (2018) Dimensions: re-discovering the ecosystem of scientific information. Prof La Inf 27:420–431. https://doi.org/10.3145/epi.2018.mar.21
Papamatthaiou S, Zupancic U, Kalha C et al (2020) Ultra stable, inkjet-printed pseudo reference electrodes for lab-on-chip integrated electrochemical biosensors. Sci Rep 10:1–10. https://doi.org/10.1038/s41598-020-74340-1
Parsons K, Brown L, Clark H et al (2020) Gluten cross-contact from common food practices and preparations. Clin Nutr 40:3279–3287. https://doi.org/10.1016/j.clnu.2020.10.053
Peli Thanthri SH, Ward CL, Cornejo MA, Linz TH (2020) Simultaneous preconcentration and separation of native protein variants using thermal gel electrophoresis. Anal Chem 92:6741–6747. https://doi.org/10.1021/acs.analchem.0c00876
Phiphatanaphiphop C, Leksakul K, Phatthanakun R et al (2020) Multiwalled carbon nanotubes in microfluidic chip for the separation of X- And Y-sperm based on a photolithography technique. J Microelectromech Syst 29:1264–1277. https://doi.org/10.1109/JMEMS.2020.3020130
Poenar DP (2019) Microfluidic and micromachined/MEMS devices for separation, discrimination and detection of airborne particles for pollution monitoring. Micromachines 10:1–34. https://doi.org/10.3390/mi10070483
Poltronieri P, Cimaglia F, De Lorenzis E et al (2016) Protein chips for detection of Salmonella spp. from enrichment culture. Sens (Switzerland) 16:1–13. https://doi.org/10.3390/s16040574
Ponnuchamy M, Kapoor A, Pakkirisamy B et al (2020) Optimization, equilibrium, kinetic and thermodynamic studies on adsorptive remediation of phenol onto natural guava leaf powder. Environ Sci Pollut Res 27:20576–20597. https://doi.org/10.1007/s11356-019-07145-z
Ponnuchamy M, Kapoor A, Senthil P et al (2021) Sustainable adsorbents for the removal of pesticides from water : a review. Environ Chem Lett 19:2425–2463. https://doi.org/10.1007/s10311-021-01183-1
Puangbanlang C, Sirivibulkovit K, Nacapricha D, Sameenoi Y (2019) A paper-based device for simultaneous determination of antioxidant activity and total phenolic content in food samples. Talanta 198:542–549. https://doi.org/10.1016/j.talanta.2019.02.048
Rasmi Y, Li X, Khan J et al (2021) Emerging point-of-care biosensors for rapid diagnosis of COVID-19: current progress, challenges, and future prospects. Anal Bioanal Chem 413:4137–4159. https://doi.org/10.1007/s00216-021-03377-6
Ravi R, Prakash M, Bhat KK (2013) Characterization of aroma active compounds of cumin (Cuminum cyminum L.) by GC-MS, E-Nose, and sensory techniques. Int J Food Prop 16:1048–1058. https://doi.org/10.1080/10942912.2011.576356
Reyes PI, Li J, Duan Z et al (2013) ZnO surface acoustic wave sensors built on zein-coated flexible food packages. Sens Lett 11:539–544. https://doi.org/10.1166/sl.2013.2822
Rios A, Zougagh M, Avila M (2018) Miniaturization through lab-on-a- chip: Utopia or reality for routine laboratories ? A review. Anal Chim Acta 740:1–10. https://doi.org/10.1016/j.aca.2012.06.024
Romao VC, Martins SAM, Germano J et al (2017) Lab-on-Chip devices: gaining ground losing size. ACS Nano 11:10659–10664. https://doi.org/10.1021/acsnano.7b06703
Ross GMS, Bremer MGEG, Nielen MWF (2018) Consumer-friendly food allergen detection: moving towards smartphone-based immunoassays. Anal Bioanal Chem 410:5353–5371. https://doi.org/10.1007/s00216-018-0989-7
Saadat M, Shafii MB, Ghassemi M (2020) Numerical investigation on mixing intensification of ferrofluid and deionized water inside a microchannel using magnetic actuation generated by embedded microcoils for lab-on-chip systems. Chem Eng Process - Process Intensif 147:107727. https://doi.org/10.1016/j.cep.2019.107727
Sanchiz Á, Ballesteros I, Marqués E et al (2018) Evaluation of locked nucleic acid and TaqMan probes for specific detection of cashew nut in processed food by real time PCR. Food Control 89:227–234. https://doi.org/10.1016/j.foodcont.2018.02.021
Santos PDM, Widmer KW, Rivera WL (2020) PCR-based detection and serovar identification of Salmonella in retail meat collected from wet markets in Metro Manila, Philippines. PLoS ONE 15:1–17. https://doi.org/10.1371/journal.pone.0239457
Saravanan A, Kumar PS, Hemavathy RV et al (2021) Methods of detection of food-borne pathogens: a review. Environ Chem Lett 19:189–207. https://doi.org/10.1007/s10311-020-01072-z
Sayad AA, Ibrahim F, Uddin SM et al (2016) A microfluidic lab-on-a-disc integrated loop mediated isothermal amplification for foodborne pathogen detection. Sens Actuat, B Chem 227:600–609. https://doi.org/10.1016/j.snb.2015.10.116
Shahdeo D, Roberts A, Abbineni N, Gandhi S (2020) Graphene based sensors. Compr Anal Chem 91:175–199. https://doi.org/10.1016/bs.coac.2020.08.007
Shaibani PM, Etayash H, Jiang K et al (2018) Portable nanofiber-light addressable potentiometric sensor for rapid escherichia coli detection in orange juice. ACS Sens 3:815–822. https://doi.org/10.1021/acssensors.8b00063
Sher M, Zhuang R, Demirci U, Asghar W (2017) Paper-based analytical devices for clinical diagnosis: recent advances in the fabrication techniques and sensing mechanisms. Expert Rev Mol Diagn 17:351–366. https://doi.org/10.1080/14737159.2017.1285228
Singh VK, Singh P, Karmakar M et al (2021) The journal coverage of web of science, Scopus and dimensions: a comparative analysis. Scientometrics 126:5113–5142. https://doi.org/10.1007/s11192-021-03948-5
Sitanurak J, Fukana N, Wongpakdee T, Thepchuay Y (2019) Talanta T-shirt ink for one-step screen-printing of hydrophobic barriers for 2D- and 3D-microfluidic paper-based analytical devices. Talanta 205:120113. https://doi.org/10.1016/j.talanta.2019.120113
Sobhan A, Oh JH, Park MK, Lee J (2020) Reusability of a single-walled carbon nanotube-based biosensor for detecting peanut allergens and Y enterocolitica. Microelectron Eng 225:111281. https://doi.org/10.1016/j.mee.2020.111281
Sri Sruthi P, Balasubramanian S, Senthil Kumar P et al (2021) Eco-friendly pH detecting paper-based analytical device: towards process intensification. Anal Chim Acta 1182:338953. https://doi.org/10.1016/j.aca.2021.338953
Sridhar A, Kapoor A, Kumar PS (2021a) Conversion of food waste to energy : a focus on sustainability and life cycle assessment. Fuel 302:121069. https://doi.org/10.1016/j.fuel.2021.121069
Sridhar A, Ponnuchamy M, Kumar PS et al (2021b) Techniques and modeling of polyphenol extraction from food: a review. Environ Chem Lett 19:3409–3443. https://doi.org/10.1007/s10311-021-01217-8
Sridhar A, Ponnuchamy M, Kumar PS, Kapoor A (2021c) Food preservation techniques and nanotechnology for increased shelf life of fruits, vegetables, beverages and spices: a review. Environ Chem Lett 2:1–21. https://doi.org/10.1007/s10311-020-01126-2
Sridhar A, Kannan D, Kapoor A, Prabhakar S (2022) Extraction and detection methods of microplastics in food and marine systems: a critical review. Chemosphere 286:131–653. https://doi.org/10.1016/j.chemosphere.2021.131653
Stahlschmidt S, Stephen D (2021) From indexation policies through citation networks to normalized citation impacts : Web of Science , Scopus , and Dimensions as varying resonance chambers. Cornell arXiv 1–17
Sun Y, Quyen TL, Hung TQ et al (2015) A lab-on-a-chip system with integrated sample preparation and loop-mediated isothermal amplification for rapid and quantitative detection of Salmonella spp. in food samples. Lab Chip 15:1898–1904. https://doi.org/10.1039/c4lc01459f
Tao H, Brenckle MA, Yang M et al (2012) Silk-based conformal, adhesive, edible food sensors. Adv Mater 24:1067–1072. https://doi.org/10.1002/adma.201103814
Teymourian H, Barfidokht A, Wang J (2020) Electrochemical glucose sensors in diabetes management: an updated review (2010–2020). Chem Soc Rev 49:7671–7709. https://doi.org/10.1039/d0cs00304b
Trofimchuk E, Hu Y, Nilghaz A et al (2020) Development of paper-based microfluidic device for the determination of nitrite in meat. Food Chem 316:126396. https://doi.org/10.1016/j.foodchem.2020.126396
Tsen HY, Shih CM, Teng PH et al (2013) Detection of Salmonella in chicken meat by insulated isothermal PCR. J Food Prot 76:1322–1329. https://doi.org/10.4315/0362-028X.JFP-12-553
Ude C, Hentrop T, Lindner P et al (2015) New perspectives in shake flask pH control using a 3D-printed control unit based on pH online measurement. Sens Actuat, B Chem 221:1035–1043. https://doi.org/10.1016/j.snb.2015.07.017
Uludag Y, Esen E, Kokturk G et al (2016) Lab-on-a-chip based biosensor for the real-time detection of aflatoxin. Talanta 160:381–388. https://doi.org/10.1016/j.talanta.2016.07.060
Valentini L, Bittolo Bon S, Pugno NM (2018) Combining living microorganisms with regenerated silk provides nanofibril-based thin films with heat-responsive wrinkled states for smart food packaging. Nanomaterials 8:518. https://doi.org/10.3390/nano8070518
van Eck NJ, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84:523–538. https://doi.org/10.1007/s11192-009-0146-3
van Eck NJ, Waltman L (2017) Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics 111:1053–1070. https://doi.org/10.1007/s11192-017-2300-7
Vanderroost M, Ragaert P, Devlieghere F, De Meulenaer B (2014) Intelligent food packaging: the next generation. Trends Food Sci Technol 39:47–62. https://doi.org/10.1016/j.tifs.2014.06.009
Verma S, Gaganjot TJ et al (2018) Biodegradable photolithography compatible substrate for transparent transient electronics and flexible energy storage devices. Appl Mater Today 13:83–90. https://doi.org/10.1016/j.apmt.2018.08.010
Viza ND, Harding DR (2018) Performance of different “Lab-On-Chip” geometries for making double emulsions to form polystyrene shells. Fusion Sci Technol 72:248–257. https://doi.org/10.1080/15361055.2017.1391662
Vu CHT, Won K (2013) Novel water-resistant UV-activated oxygen indicator for intelligent food packaging. Food Chem 140:52–56. https://doi.org/10.1016/j.foodchem.2013.02.056
Wahyuni H, Vanany I, Ciptomulyono U (2019) Food safety and halal food in the supply chain: review and bibliometric analysis. J Ind Eng Manag 12:373–391. https://doi.org/10.3926/jiem.2803
Wang W, Wu WY, Wang W, Zhu JJ (2010) Tree-shaped paper strip for semiquantitative colorimetric detection of protein with self-calibration. J Chromatogr A 1217:3896–3899. https://doi.org/10.1016/j.chroma.2010.04.017
Wang Y, Wei X, Li J et al (2015) Study on nanocellulose by high pressure homogenization in homogeneous isolation. Fibers Polym 16:572–578. https://doi.org/10.1007/s12221-015-0572-1
Wang R, Tsai W-T, He J et al (2019) Logistics management system based on permissioned blockchains and RFID technology. Int Conf Comput Netw, Commun Inf Syst 88:426–432. https://doi.org/10.2991/cnci-19.2019.58
Weng X, Gaur G, Neethirajan S (2016) Rapid detection of food allergens by microfluidics ELISA-Based optical sensor. Biosensors 6:24. https://doi.org/10.3390/bios6020024
Weng X, Luan X, Kong C et al (2020) A comprehensive method for assessing meat freshness using fusing electronic nose, computer vision, and artificial tactile technologies. J Sens 2020:1–14. https://doi.org/10.1155/2020/8838535
Wong B, Kasparek E, Robillard A et al (2020) Improving the longevity of passive microfluidic systems through plasma polymer films with a vertical chemical gradient. Microfluid Nanofluidics 24:1–8. https://doi.org/10.1007/s10404-020-2324-9
Wongsrichanalai C, Barcus MJ, Muth S et al (2007) A review of malaria diagnostic tools: microscopy and rapid diagnostic test (RDT). Am J Trop Med Hyg 77:119–127. https://doi.org/10.4269/ajtmh.2007.77.119
Wu X, Li Y, Liu B et al (2016) Two-Site antibody immunoanalytical detection of food allergens by surface plasmon resonance. Food Anal Methods 9:582–588. https://doi.org/10.1007/s12161-015-0232-5
Xia Y, Si J, Li Z (2016) Fabrication techniques for microfluidic paper-based analytical devices and their applications for biological testing: a review. Biosens Bioelectron 77:774–789. https://doi.org/10.1016/j.bios.2015.10.032
Xu B, Guo J, Fu Y et al (2020) A review on microfluidics in the detection of food pesticide residues. Electrophoresis 41:821–832. https://doi.org/10.1002/elps.201900209
Yam P (2005) Intelligent packaging: concepts and applications. J Food Sci 66:379–379. https://doi.org/10.1111/j.1365-2621.2001.tb16112.x
Yamada K, Henares TG, Suzuki K, Citterio D (2015) Paper-based inkjet-printed microfluidic analytical devices. Angew Chemie - Int Ed 54:5294–5310. https://doi.org/10.1002/anie.201411508
Yang J, Lee J (2019) Application of sensory descriptive analysis and consumer studies to investigate traditional and authentic foods: a review. Foods 8:1–17. https://doi.org/10.3390/foods8020054
Yang JM, Kim KR, Kim CS (2018) Biosensor for rapid and sensitive detection of influenza virus. Biotechnol Bioprocess Eng 23:371–382. https://doi.org/10.1007/s12257-018-0220-x
Yoon JY, Kim B (2012) Lab-on-a-chip pathogen sensors for food safety. Sens (Switzerland) 12:10713–10741. https://doi.org/10.3390/s120810713
Yousefi H, Ali MM, Su HM et al (2018) Sentinel wraps: real-time monitoring of food contamination by printing DNAzyme probes on food packaging. ACS Nano 12:3287–3294. https://doi.org/10.1021/acsnano.7b08010
Zeinhom MMA, Wang Y, Song Y et al (2018) A portable smart-phone device for rapid and sensitive detection of E. coli O157:H7 in Yoghurt and Egg. Biosens Bioelectron 99:479–485. https://doi.org/10.1016/j.bios.2017.08.002
Zhang C, Yin AX, Jiang R et al (2013) Time-temperature indicator for perishable products based on kinetically programmable Ag overgrowth on Au nanorods. ACS Nano 7:4561–4568. https://doi.org/10.1021/nn401266u
Zhang G, Zhu C, Huang Y et al (2018) A lateral flow strip based aptasensor for detection of Ochratoxin a in corn samples. Molecules 23:1–12. https://doi.org/10.3390/molecules23020291
Zhang Y, Li G, Wu D et al (2019) Recent advances in emerging nanomaterials based food sample pretreatment methods for food safety screening. TrAC - Trends Anal Chem 121:1–71. https://doi.org/10.1016/j.trac.2019.115669
Zhao Y, Zeng D, Yan C et al (2020) Rapid and accurate detection of: escherichia coli O157:H7 in beef using microfluidic wax-printed paper-based ELISA. Analyst 145:3106–3115. https://doi.org/10.1039/d0an00224k
Zheng Y, Zou M, Hu G (2020) Implementation of a lightweight RFID security authentication protocol system. J Phys Conf Ser 1549:1–6. https://doi.org/10.1088/1742-6596/1549/4/042038
Zhou J, Qi Q, Wang C et al (2019) Surface plasmon resonance (SPR) biosensors for food allergen detection in food matrices. Biosens Bioelectron 142:111449. https://doi.org/10.1016/j.bios.2019.111449
Zhu D, Ren X, Wei L et al (2020) Collaborative analysis on difference of apple fruits flavour using electronic nose and electronic tongue. Sci Hortic (Amsterdam) 260:108879. https://doi.org/10.1016/j.scienta.2019.108879
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Sridhar, A., Kapoor, A., Kumar, P.S. et al. Lab-on-a-chip technologies for food safety, processing, and packaging applications: a review. Environ Chem Lett 20, 901–927 (2022). https://doi.org/10.1007/s10311-021-01342-4
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DOI: https://doi.org/10.1007/s10311-021-01342-4