Quantum dots as advanced nanomaterials for food quality and safety applications: A comprehensive review and future perspectives.

The importance of food quality and safety lies in ensuring the best product quality to meet consumer demands and public health. Advanced technologies play a crucial role in minimizing the risk of foodborne illnesses, contamination, drug residue, and other potential hazards in food. Significant materials and technological advancements have been made throughout the food supply chain. Among them, quantum dots (QDs), as a class of advanced nanomaterials with unique physicochemical properties, are progressively demonstrating their value in the field of food quality and safety. This review aims to explore cutting-edge research on the different applications of QDs in food quality and safety, including encapsulation of bioactive compounds, detection of food analytes, food preservation and packaging, and intelligent food freshness indicators. Moreover, the modification strategies and potential toxicities of diverse QDs are outlined, which can affect performance and hinder applications in the food industry. The findings suggested that QDs are mainly used in analyte detection and active/intelligent food packaging. Various food analytes can be detected using QD-based sensors, including heavy metal ions, pesticides, antibiotics, microorganisms, additives, and functional components. Moreover, QD incorporation aided in improving the antibacterial and antioxidant activities of film/coatings, resulting in extended shelf life for packaged food. Finally, the perspectives and critical challenges for the productivity, toxicity, and practical application of QDs are also summarized. By consolidating these essential aspects into this review, the way for developing high-performance QD-based nanomaterials is presented for researchers and food technologists to better capitalize upon this technology in food applications.

Flexible-fabricated sensor module with programmable magnetic actuators coupled to L-cysteine functionalized Ag@Fe3O4 complexes for Cu2+ detection in fish tissues.

Heavy metal contamination for seafood, particularly fish, is arising great concerns, and consequentially it is necessary to develop a simple and direct detection method. In this work, Ag@Fe3O4 is successfully prepared by simple solvothermal method, and we present a flexible-fabricated sensor module with assembled programmable magnetic actuators. The resulting sensor integrates a three-electrode system with two programmable magnetic actuators at the bottom of the device, which regulates the amount of current by adjusting the brake to control the adsorption force and vibration. The L-Cysteine functionalized Ag@Fe3O4 is coated on the surface of the electrode, then the Cu2+ is dropped into the reaction tank. Its performance is studied by cyclic voltammetry and electrochemical impedance spectroscopy, and the key experimental conditions such as deposition potential, deposition time, and electrolyte pH are gradually optimized. Under optimal conditions, Cu2+ can be detected over a wide linear range (0.01 ~ 4 µM) and at a low LOD (0.34 nM). The results show that the proposed method has a good application prospect in the detection of Cu2+. This method is successfully applied to Cu2+ analysis in fish samples with an acceptable recovery of 93 ~ 102%.

Construction of Graphene@Ag-MLF composite structure SERS platform and its differentiating performance for different foodborne bacterial spores.

A new surface-enhanced Raman spectroscopy (SERS) biosensor of Graphene@Ag-MLF composite structure has been fabricated by loading AgNPs on graphene films. The response of the biosensor is  based on plasmonic sensing. The results showed that the enhancement factor of three different spores reached 107 based on the Graphene@Ag-MLF substrate. In addition, the SERS performance was stable, with good reproducibility (RSD<3%). Multivariate statistical analysis and chemometrics were used to distinguish different spores. The accumulated variance contribution rate was up to 96.35% for the top three PCs, while HCA results revealed that the spectra were differentiated completely. Based on optimal principal components, chemometrics of KNN and LS-SVM were applied to construct a model for rapid qualitative identification of different spores, of which the prediction set and training set of LS-SVM achieved 100%. Finally, based on the Graphene@Ag-MLF substrate, the LOD of three different spores was lower than 102 CFU/mL. Hence, this novel Graphene@Ag-MLF SERS substrate sensor was rapid, sensitive, and stable in detecting spores, providing strong technical support for the application of SERS technology in food safety.

A Renewable Biosensor Based on LNA-Aptamer Hybridization for the Detection of Salmonella enteritidis in Penaeus vannamei.

Salmonella enteritidis (SE) is an important factor causing foodborne disease, and electrochemical sensors have drawn much attention for SE prevention and detection due to their many advantages. A renewable electrochemical sensor using specially designed locked nucleic acids (LNA) as linkers for the detection of SE was proposed to improve the reusability and reproducibility of biosensors. One end of the LNA was designed as an anchor to attach to modified electrodes through the sulfhydryl group; the other end was used to match with a short segment of SE aptamers, which will allow for the convenient renewal of occupied aptamers by raising the temperature. Results revealed that the manufactured biosensor had good stability, reproducibility, and selectivity in addition to a linear range of 6 × 101-6 × 105 CFU/mL and a limit of detection (LOD) of 20.704 CFU/mL. The recovery rate of SE for the real sample varied from 98.84% to 134.82% without exceeding 16.27% in the relative standard deviation (RSD). The proposed biosensor appears to be a promising tool for foodborne pathogen detection.

Non-destructive discrimination of homochromatic foreign materials in cut tobacco based on VIS-NIR hyperspectral imaging.

BACKGROUND: The presence of foreign materials (FM) not only reduces the commercial value of tobacco and the quality of cigarette products, but also affects the aroma and flavor of cigarettes. Existing tobacco deblending equipment has received little study with respect to homochromatic FM. In the present study, visible-near infrared (VIS-NIR) hyperspectral imaging technique combined with chemometrics were used to identify and visualize the homochromatic FM on the surface of thining tobacco. A comparison with conventional vision method was made to analyze the feasibility of the method. The importance of detecting FM in cut tobacco was further demonstrated by first studying the volatile organic compounds produced in cigarette mixed FM smoke and their effects on human health before conducting hyperspectral experiments. RESULTS: The results indicated that solid-phase microextraction and gas chromatography mass spectrometry could detect volatile organic compounds in mainstream cigarette smoke that were not cigarette components and affected consumer health. Then, spectral features of the samples were extracted from hyperspectral images for building identification models to distinguish FM from cut tobacco. The visual RGB values of cut tobacco and FM were also used for the analysis of the recognition models. The results showed that the accuracy, precision and recall reached 100.00% using the back propagation artificial neural network classification model based on the principal component analysis raw wavelengths. The visualization results based on the optimal model produced clearer localization than conventional computer vision method. CONCLUSION: The present study revealed that the VIS-NIR hyperspectral imaging technology had advantage in the detection and localization of FM on the surface of thinning tobacco, which provided a foundation for improving the quality and safety of cut tobacco production. © 2023 Society of Chemical Industry.

Fluorometric and electrochemical dual-mode nanoprobe for tetracycline by using a nanocomposite prepared from carbon nitride quantum dots and silver nanoparticles.

A fluorometric and electrochemical dual-mode method is described for sensitive and specific detection of tetracycline (Tc). A novel nanoprobe was designed that is making use of a Tc-specific aptamer (apta), carbon nitride quantum dots (CNQDs) and silver nanoparticles (AgNPs). The aptamer was linked to the CNQDs which then were used as templates to synthesize the apta-CNQD@AgNP nanocomposites. The blue fluorescence of the nanocomposites (with excitation/emission maxima at 365/440 nm) is quenched. The addition of Tc leads to fluorescence recovery and a decrease in the electroconductivity of a gold electrode modified with apta-CNQD@AgNPs. The fluorometric method has a linear response in the 0.1 µM - 10 mM Tc concentration range and a 15 nM detection limit. The amperometric method (best performed at a working voltage of 0.21 V vs. Ag/AgCl) has a linear response in the 1 nM to 0.1 mM Tc concentration range and a 0.26 nM detection limit. Recoveries of Tc from spiked milk samples were comparable to data obtained by HPLC. Graphical abstractA fluorometric and electrochemical dual-mode nanoprobe (apta-CNQD@AgNPs) was prepared from aptamer (apta), carbon nitride quantum dots (CNQDs) and silver nanoparticles (AgNPs). The nanoprobe can be used for determination of tetracycline (Tc) based on fluorescence recovery of apta-CNQD@AgNPs and a decrease in the electroconductivity of a gold electrode modified with apta-CNQD@AgNPs.

Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics.

It is crucial for the efficacy of the apple storage to apply methods like electronic nose systems for detection and prediction of spoilage or infection by Penicillium expansum. Based on the acquisition of electronic nose signals, selected sensitive feature sensors of spoilage apple and all sensors were analyzed and compared by the recognition effect. Principal component analysis (PCA), principle component analysis-discriminant analysis (PCA-DA), linear discriminant analysis (LDA), partial least squares discriminate analysis (PLS-DA) and K-nearest neighbor (KNN) were used to establish the classification model of apple with different degrees of corruption. PCA-DA has the best prediction, the accuracy of training set and prediction set was 100% and 97.22%, respectively. synergy interval (SI), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) are three selection methods used to accurately and quickly extract appropriate feature variables, while constructing a PLS model to predict plaque area. Among them, the PLS model with unique variables was optimized by CARS method, and the best prediction result of the area of the rotten apple was obtained. The best results are as follows: Rc = 0.953, root mean square error of calibration (RMSEC) = 1.28, Rp = 0.972, root mean square error of prediction (RMSEP) = 1.01. The results demonstrated that the electronic nose has a potential application in the classification of rotten apples and the quantitative detection of spoilage area.

A ratiometric fluorescence sensor for ultra-sensitive detection of trypsin inhibitor in soybean flour using gold nanocluster@carbon nitride quantum dots.

Gold nanocluster@carbon nitride quantum dot nanocomposites protected by bovine serum albumin (BSA-AuNC@CNQDs) were designed as a ratiometric fluorescence nanosensor for ultra-sensitive detection of trypsin inhibitor (TI). CNQDs were prepared via thermal treatment of carbon nitride powder. BSA-CNQDs acted as templates to synthesize BSA-AuNC@CNQDs with dual-emission peaks at 450 and 650 nm. Trypsin can catalyze the hydrolysis of BSA and decompose BSA-AuNC@CNQDs resulting in fluorescence quenching. The fluorescence quenching at 650 nm was prevented by the addition of TI to inhibit the activity of trypsin. The nanosensor-trypsin system showed a satisfactory ability toward TI detection. The ratiometric responses (the ratio of intensity at 650 to 450 nm, I650/I450) had an excellent linearity (R2 = 0.981) with logarithmic values of TI concentrations in the broad range of 1-10,000 ng/mL. The limit of detection (LOD, 0.089 ng/mL) indicates ultra-sensitive detection of TI can be achieved. Additionally, TI in soybean flour was detected by the proposed ratiometric method with satisfactory recoveries (98.15-105.52%) and less than 6% of coefficient of variation. This study reveals that BSA-AuNC@CNQDs have potential applications in detection of TI in real samples.

Study on the Diffusion and Optimization of Sucrose in Gaido Seak Based on Finite Element Analysis and Hyperspectral Imaging Technology.

As a traditional Chinese dish cutting technology process, Gaidao artificially create cuts embedded in the food surface by cutting through it with knife, a process that currently plays an important role in the beef marinating process. And different Gaidao processes directly affect the beef marination flavour and marination efficiency. This study is the first to propose the use of Hyperspectral imaging technology (HSI) combined with finite element analysis to investigate the effect of Gaidao process on the quality of marinated beef. The study was carried out by collecting spectral information of beef marinated with different sucrose concentrations and combining various pre-processing methods and algorithms such as PLS, BiPLS, iPLS, and SiPLS to establish a quantitative model of sucrose concentration in beef, and finally optimizing parameters such as the length, position and number of Gaidao by Finite Element Analysis (FEA), which showed that when marinated with 1.0 mol/m³ sucrose solution, the concentration of sucrose in all tissues in the Gaidao steak reached 0.8 mol/m³ and above, which greatly improved the diffusion effect of the marinade. This work provides new ideas and methods to optimize the beef marinade Gaidao process, which has important practical value and research significance.

Preparation of edible antibacterial films based on corn starch /carbon nanodots for bioactive food packaging.

Packaging plays an important role in protecting food from environmental impacts. However, traditional petroleum-based packaging has difficulty in meeting the antimicrobial and antioxidant requirements of prepared foods. This study introduced carbon dots (CDs), prepared by using carrot as a precursor, into corn starch (CS) to construct a bio-friendly composite film with high freshness retention properties. The scavenging of DPPH radicals reached 92.77 % at a CDs concentration of 512 µg/mL, and the antimicrobial activity of CS/5% CDs against Escherichia coli and Staphylococcus aureus was increased to 99.9 %. Notably, the homogeneous doping of CDs creates a dense surface and high carbon content inside the film, which promotes the elasticity and thermal stability of the composite film. Finally, we encapsulated deep-fried meatballs in CS-CDs films. The results showed that the CS-CDs films effectively protected the quality of deep-fried meatballs, and have excellent potential for application in food preservation.

Incorporation of Lactococcus lactis and Chia Mucilage for Improving the Physical and Biological Properties of Gelatin-Based Coating: Application for Strawberry Preservation.

In this work, a gelatin/chia mucilage (GN/CM) composite coating material doped with Lactococcus lactis (LS) was developed for strawberry preservation applications. The results of the scanning electron microscope and Fourier transform infrared spectroscopy stated that the enhanced molecular interaction between the CM and GN matrix strengthened the density and compactness of the GN film. Antifungal results indicated that the addition of LS significantly (p < 0.05) improved the ability of the GN coating to inhibit the growth of Botrytis cinerea (inhibition percentage = 62.0 ± 4.6%). Adding CM significantly (p < 0.05) decreased the water vapour permeability and oxygen permeability of the GN coating by 32.7 ± 4.0% and 15.76 ± 1.89%, respectively. In addition, the incorporated CM also significantly (p < 0.05) improved the LS viability and elongation at break of the film by 13.11 ± 2.05% and 42.58 ± 1.21%, respectively. The GN/CM/LS composite coating material also exhibited an excellent washability. The results of this study indicated that the developed GN/CM/LS coating could be used as a novel active material for strawberry preservation.

Ammonia-Responsive Colorimetric Film of Phytochemical Formulation (Alizarin) Grafted onto ZIF-8 Carrier with Poly(vinyl alcohol) and Sodium Alginate for Beef Freshness Monitoring.

In this study, we devised a photothermally stable phytochemical dye by leveraging alizarin in conjunction with the metal-organic framework ZIF-8 (AL@ZIF-8). The approach involved grafting alizarin into the microporous structure of ZIF-8 through physical adsorption and hydrogen-bonding interactions. AL@ZIF-8 significantly enhanced the photostability and thermostability of alizarin. The nanoparticles demonstrate substantial color changes in various pH environments, showcasing their potential for meat freshness monitoring. Furthermore, we introduced an intelligent film utilizing poly(vinyl alcohol)-sodium alginate-AL@ZIF-8 (PA-SA-ZA) for detecting beef freshness. The sensor exhibited a superior water contact angle (52.34°) compared to the alizarin indicator. The color stability of the film was significantly enhanced under visible and UV light (ΔE < 5). During beef storage, the film displayed significant color fluctuations correlating with TVB-N (R2=0.9067), providing precise early warning signals for assessing beef freshness.

Rapid determination of geographical authenticity and pungency intensity of the red Sichuan pepper (Zanthoxylum bungeanum) using differential pulse voltammetry and machine learning algorithms.

The development of an analytical method for assessing pungency intensity and determining geographical origins is crucial for evaluating the quality of visually similar Zanthoxylum bungeanum pericarp (PZB). This study analyzed 210 PZB samples from 14 origins across China, focusing on origin adulteration identification and pungency intensity using a combination of differential pulse voltammetry (DPV) and machine learning algorithms. The artificial neural network (ANN) and K-nearest neighbor (KNN) algorithms provided the highest accuracy in origin identification (100 %) and adulteration detection (97.9 %) respectively. Moreover, the ANN excelled in predicting pungency intensity (R2 = 0.918). Assessment via feature importance analysis of DPV features revealed that segments of polyphenols (0.34-0.52 V and 1.0-1.2 V) and alkylamides (1.0-1.2 V) contributed significantly to the PZB pungency intensity. These findings highlight the potential of DPV as a reliable method for assessing the quality of PZB, and offer a promising solution for ensuring the geographical authenticity of this important crop.

Quantitative SERS sensor for mycotoxins with extraction and identification function.

The development of new sensors for on-site food toxin monitoring that combine extraction, analytes distinction and detection is important in resource-limited environments. Surface-enhanced Raman scattering (SERS)-based signal readout features fast response and high sensitivity, making it a powerful method for detecting mycotoxins. In this work, a SERS-based assay for the detection of multiple mycotoxins is presented that combines extraction and subsequent detection, achieving an analytically relevant detection limit (∼ 1 ng/mL), which is also tested in corn samples. This sensor consists of a magnetic-core and mycotoxin-absorbing polydopamine-shell, with SERS-active Au nanoparticles on the outer surface. The assay can concentrate multiple mycotoxins, which are identified through multiclass partite least squares analysis based on their SERS spectra. We developed a strategy for the analysis of multiple mycotoxins with minimal sample pretreatment, enabling in situ analytical extraction and subsequent detection, displaying the potential to rapidly identify lethal mycotoxin contamination on site.

Effect of Phenol and Alkylamide Interaction on α-Glucosidase Inhibition and Cellular Antioxidant Activity during In Vitro Digestion: Using Szechuan Pepper (Zanthoxylum genus) as a Model.

Although recent evidence indicated significant phenol and alkylamide interaction in aqueous solutions, the gastrointestinal digestion influence of the combination remains unclear. This study aims to investigate phenol and alkylamide interaction during in vitro digestion, focusing on bioaccessibility and bioactivity, including α-glucosidase inhibition and cellular antioxidant activity. Additionally, the structural mechanism of phenol and alkylamide interaction during in vitro digestion was explored. The results indicated that the presence of phenols and alkylamides significantly increased or decreased their respective bioaccessibility, depending on the Zanthoxylum varieties. Furthermore, although antagonistic phenol/alkylamide interaction was evident during α-glucosidase inhibition, cellular oxidative stress alleviation, and antioxidant gene transcription upregulation, this effect weakened gradually as digestion progressed. Glycoside bond cleavage and the methylation of phenols as well as alkylamide isomerization and addition were observed during digestion, modifying the hydrogen bonding sites and interaction behavior. This study provided insights into the phenol/alkylamide interaction in the gastrointestinal tract.

Real-Time Monitoring of Dough Quality in a Dough Mixer Based on Current Change.

Accurate assessment of dough kneading is pivotal in pasta processing, where both under-kneading and over-kneading can detrimentally impact dough quality. This study proposes an innovative approach utilizing a cost-effective current sensor to ascertain the optimal kneading time for dough. Throughout the kneading process, the dough's tensile resistance gradually increases, reflecting the evolution of properties such as the gluten network. This leads to a discernible ascending phase in dough quality, evident through an increase in the load current of the mixing machine, succeeded by a subsequent decline beyond a certain threshold. The identification of this peak point enables the achievement of optimal dough consistency, thereby enhancing the overall quality of both the dough and subsequent pasta products. After the final product quality assessment, this novel method promises to be a valuable tool in optimizing pasta processing and ensuring consistent product quality.

Green and sustainable self-cleaning flexible SERS base: Utilized for cyclic-detection of residues on apple surface.

Advances in flexible SERS substrates has made it possible to approach the ultimate goal of rapid in-situ monitoring of fruit and vegetable safety, but its vulnerability under laser ablation results in low utilization. In order to solve this problem, a 3D framework of TiO2-doped PVDF\PVP polymer was utilized to self-assemble gold-silver core-shell nanorods (Au@Ag NRs) to prepare a flexible SERS substrate with good physical stability and self-cleaning properties. This substrate showed excellent detection limit and recyclability after the detection of three pesticide residues in apple peel. The LOD of methyl-parathion (MP) was as low as 0.037 ng/cm2, with an RSD of 5.61 % for 5 cycle-detection. The recoveries of two additional pesticides thiram (TMTD) and chlorpyrifos (CPF) were 86.32 %-112.47 %. We hoped that this research will contribute to providing a recyclable and facile method for in-situ analysis of fruit and vegetable surface residues and functional manufacture of flexible SERS substrates.

A DNA tetrahedral scaffolds-based electrochemical biosensor for simultaneous detection of AFB1 and OTA.

Herein, a bifunctional electrochemical biosensor based on the DNA tetrahedral scaffolds (TDNs) was proposed, OTA@TDNs and AFB1@TDNs were adopted for electrochemical signal output in response to OTA and AFB1 concentration, simultaneously. In order to increase the conductivity of the biosensor, highly porous gold (HPG) was loaded on electrode surface by pulse electrodeposition. Under optimal conditions, the PFc displayed a linear range with AFB1 concentration between 0.05 âˆ¼ 360 ng·mL-1 with the LOD of 3.5 pg·mL-1. And the PMB selective and sensitive responses to OTA are achieved with a linear range of 0.05 âˆ¼ 420 ng·mL-1 and a LOD of 2.4 pg·mL-1. This biosensor has high sensitivity, selectivity and stability for OTA and AFB1 detection in peanut samples. The approach streamlines the experimental procedure, leading to significantly improve the detection efficiency of mycotoxins. Collectively, this method suggest a novel approach for the detection and monitoring of OTA and AFB1 in food sample.

Recent advances in electrochemical cell-based biosensors for food analysis: Strategies for sensor construction.

Owing to their advantages such as great specificity, sensitivity, rapidity, and possibility of noninvasive and real-time monitoring, electrochemical cell-based biosensors (ECBBs) have been a powerful tool for food analysis encompassing the areas of nutrition, flavor, and safety. Notably, the distinctive biological relevance of ECBBs enables them to mimic physiological environments and reflect cellular behaviors, leading to valuable insights into the biological function of target components in food. Compared with previous reviews, this review fills the current gap in the narrative of ECBB construction strategies. The review commences by providing an overview of the materials and configuration of ECBBs, including cell types, cell immobilization strategies, electrode modification materials, and electrochemical sensing types. Subsequently, a detailed discussion is presented on the fabrication strategies of ECBBs in food analysis applications, which are categorized based on distinct signal sources. Lastly, we summarize the merits, drawbacks, and application scope of these diverse strategies, and discuss the current challenges and future perspectives of ECBBs. Consequently, this review provides guidance for the design of ECBBs with specific functions and promotes the application of ECBBs in food analysis.

Energy difference-driven ROS reduction for electrochemical tracking crop growth sensitized with electron-migration nanostructures.

Aiming for sustainable crop productivity under changing climate conditions, it is essential to develop handy models for in-situ monitoring of reactive oxygen species (ROS). Herein, this work reports a simple electrochemical sensing toward hydrogen peroxide (H2O2) for tracking crop growth status sensitized with electron-migration nanostructure. To be specific, Cu-based metal-organic frameworks (MOFs) with high HOMO energy level are designed for H2O2 reduction on account of Cu(I)/Cu(II) redox switchability. Importantly, the sensing performance is improved by electrochemically reduced graphene oxide (GO) with ready to use feature. To overcome the shortcomings of traditional liquid electrolytes, conductive hydrogel as semi-solid electrolyte exhibits the adhesive property to the cut plant petiole surface. Benefitting from the preferred composite models and conductive hydrogel, the electrochemical sensing toward H2O2 with high sensitivity and good anti-interference against the coexistent molecules, well qualified for acquiring plant growth status.