Novel Nondestructive Biosensors for the Food Industry

Seafood product safety: A hybrid graphene/gold-based electrochemical immunosensor for fish allergen analysis

Seafood product labels with accurate allergen contents can avoid and/or minimize allergic reactions. Therefore, an electrochemical immunosensor for the analysis of β-parvalbumin (β-PV, a major fish allergen) was developed. Screen-printed carbon electrodes were nanostructured with reduced graphene oxide and gold nanoparticles. The platform was characterized by scanning electron microscopy and elemental analysis. In a sandwich-type assay (∼75 min), the antigen-antibody interaction was detected by chronoamperometry using horseradish peroxidase and TMB-H2O2. A linear range of 25-3000 ng/mL, a sensitivity of 2.99 µA.mL/ng, and a limit of detection of 9.9 ng/mL (corresponding to 0.40 ng in the analysed aliquot) were obtained. The selectivity and possible interferences were assessed by analysing several other food allergens and a marine toxin. The sensor was applied to the analysis of 17 commercial foods and the effect of culinary processing (e.g., grilled, canned, smoked) on the β-PV concentration was assessed. Traces of β-PV were successfully quantified and ELISA was used to assess the results.

Revolutionizing food safety with electrochemical biosensors for rapid and portable pathogen detection

Foodborne diseases remain a worldwide concern, despite the advances made in sanitation, pathogen surveillance and food safety management systems. The methods routinely applied for detecting pathogens in foods are time consuming, labor intensive and usually require trained and qualified individuals. The objective of this review was to highlight the use of biosensors, with a focus on the electrochemical devices, as promising alternatives for detecting foodborne pathogens. These biosensors present high speed for obtaining results, with the possibility of evaluating foods in real time, at low cost, ease of use, in addition to being compact and portable. These aspects are considered advantageous and suitable for use in food safety management systems. This work also shows some limitations for the application of biosensors, and we present perspectives with the development and use of nanomaterials.

The Magnitude and Impact of Food Allergens and the Potential of AI-Based Non-Destructive Testing Methods in Their Detection and Quantification

Reaction to food allergens is on the increase and so is the attending cost on consumers, the food industry, and society at large. According to FDA, the "big-eight" allergens found in foods include wheat (gluten), peanuts, egg, shellfish, milk, tree nuts, fish, and soybeans. Sesame was added to the list in 2023, making the target allergen list nine instead of eight. These allergenic foods are major ingredients in many food products that can cause severe reactions in those allergic to them if found at a dose that can elicit a reaction. Defining the level of contamination that can elicit sensitivity is a work in progress. The first step in preventing an allergic reaction is reliable detection, then an effective quantification method. These are critical steps in keeping contaminated foods out of the supply chain of foods with allergen-free labels. The conventional methods of chemical assay, DNA-PCR, and enzyme protocols like enzyme-linked immunosorbent assay are effective in allergen detection but slow in providing a response. Most of these methods are incapable of quantifying the level of allergen contamination. There are emerging non-destructive methods that combine the power of sensors and machine learning to provide reliable detection and quantification. This review paper highlights some of the critical information on the types of prevalent food allergens, the mechanism of an allergic reaction in humans, the measure of allergenic sensitivity and eliciting doses, and the conventional and emerging AI-based methods of detection and quantification-the merits and downsides of each type.

Advancing biological investigations using portable sensors for detection of sensitive samples

Portable biosensors are emerged as powerful diagnostic tools for analyzing intricately complex biological samples. These biosensors offer sensitive detection capabilities by utilizing biomolecules such as proteins, nucleic acids, microbes or microbial products, antibodies, and enzymes. Their speed, accuracy, stability, specificity, and low cost make them indispensable in forensic investigations and criminal cases. Notably, portable biosensors have been developed to rapidly detect toxins, poisons, body fluids, and explosives; they have proven invaluable in forensic examinations of suspected samples, generating efficient results that enable effective and fair trials. One of the key advantages of portable biosensors is their ability to provide sensitive and non-destructive detection of forensic samples without requiring extensive sample preparation, thereby reducing the possibility of false results. This comprehensive review provides an overview of the current advancements in portable biosensors for the detection of sensitive materials, highlighting their significance in advancing investigations and enhancing sensitive sample detection capabilities.

Advances in aptamers, and application of mycotoxins detection: A review

Mycotoxin contamination in food products can easily cause serious health hazards and economic losses to human beings. How to accurately detect and effectively control mycotoxin contamination has become a global concern. Mycotoxins conventional detection techniques e.g; ELISA, HPLC, have limitations like, low sensitivity, high cost and time-consuming. Aptamer-based biosensing technology has the advantages of high sensitivity, high specificity, wide linear range, high feasibility, and non-destructiveness, which overcomes the shortcomings of conventional analysis techniques. This review summarizes the sequences of mycotoxin aptamers that have been reported so far. Based on the application of four classic POST-SELEX strategies, it also discusses the bioinformatics-assisted POST-SELEX technology in obtaining optimal aptamers. Furthermore, trends in the study of aptamer sequences and their binding mechanisms to targets is also discussed. The latest examples of aptasensor detection of mycotoxins are classified and summarized in detail. Newly developed dual-signal detection, dual-channel detection, multi-target detection and some types of single-signal detection combined with unique strategies or novel materials in recent years are focused. Finally, the challenges and prospects of aptamer sensors in the detection of mycotoxins are discussed. The development of aptamer biosensing technology provides a new approach with multiple advantages for on-site detection of mycotoxins. Although aptamer biosensing shows great development potential, still some challenges and difficulties are there in practical applications. Future research need high focus on the practical applications of aptasensors and the development of convenient and highly automated aptamers. This may lead to the transition of aptamer biosensing technology from laboratory to commercialization.

Applications of Smartphone-Based Aptasensor for Diverse Targets Detection

Aptamers are a particular class of functional recognition ligands with high specificity and affinity to their targets. As the candidate recognition layer of biosensors, aptamers can be used to sense biomolecules. Aptasensors, aptamer-based biosensors, have been demonstrated to be specific, sensitive, and cost-effective. Furthermore, smartphone-based devices have shown their advantages in binding to aptasensors for point-of-care testing (POCT), which offers an immediate or spontaneous responding time for biological testing. This review describes smartphone-based aptasensors to detect various targets such as metal ions, nucleic acids, proteins, and cells. Additionally, the focus is also on aptasensors-related technologies and configurations.

Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry

The food industry faces many challenges, including the need to feed a growing population, food loss and waste, and inefficient production systems. To cope with those challenges, digital twins that create a digital representation of physical entities by integrating real-time and real-world data seem to be a promising approach. This paper aims to provide an overview of digital twin applications in the food industry and analyze their challenges and potentials. Therefore, a literature review is executed to examine digital twin applications in the food supply chain. The applications found are classified according to a taxonomy and key elements to implement digital twins are identified. Further, the challenges and potentials of digital twin applications in the food industry are discussed. The survey revealed that the application of digital twins mainly targets the production (agriculture) or the food processing stage. Nearly all applications are used for monitoring and many for prediction. However, only a small amount focuses on the integration in systems for autonomous control or providing recommendations to humans. The main challenges of implementing digital twins are combining multidisciplinary knowledge and providing enough data. Nevertheless, digital twins provide huge potentials, e.g., in determining food quality, traceability, or designing personalized foods.

Ultrasensitive On-Field Luminescence Detection Using a Low-Cost Silicon Photomultiplier Device

The availability of portable analytical devices for on-site monitoring and rapid detection of analytes of forensic, environmental, and clinical interest is vital. We report the development of a portable device for the detection of biochemiluminescence relying on silicon photomultiplier (SiPM) technology, called LuminoSiPM, which includes a 3D printed sample holder that can be adapted for both liquid samples and paper-based biosensing. We performed a comparison of analytical performance in terms of detectability with a benchtop luminometer, a portable cooled charge-coupled device (CCD sensor), and smartphone-integrated complementary metal oxide semiconductor (CMOS) sensors. As model systems, we used two luciferase/luciferin systems emitting at different wavelengths using purified protein solutions: the green-emitting P. pyralis mutant Ppy-GR-TS (λ_max 550 nm) and the blue-emitting NanoLuc (λ_max 460 nm). A limit of detection of 9 femtomoles was obtained for NanoLuc luciferase, about 2 and 3 orders of magnitude lower than that obtained with the portable CCD camera and with the smartphone, respectively. A proof-of-principle forensic application of LuminoSiPM is provided, exploiting an origami chemiluminescent paper-based sensor for acetylcholinesterase inhibitors, showing high potential for this portable low-cost device for on-site applications with adequate sensitivity for detecting low light intensities in critical fields.