Introducing reticular chemistry into agrochemistry

A tailored dual core-shell magnetic SERS substrate with precise shell-thickness control for trace organophosphorus pesticides residues detection

For addressing the challenges of strong affinity SERS substrate to organophosphorus pesticides (OPs), herein, a rapid water-assisted layer-by-layer heteronuclear growth method was investigated to grow uniform UiO-66 shell with controllable thickness outside the magnetic core and provide abundant defect sites for OPs adsorption. By further assembling the tailored Au@Ag, a highly sensitive SERS substrate Fe3O4-COOH@UiO-66/Au@Ag (FCUAA) was synthesized with a SERS enhancement factor of 2.11 × 107. The substrate's suitability for the actual vegetable samples (cowpeas and peppers) was confirmed under both destructive and non-destructive detection conditions, showing a strong SERS response to fenthion and triazophos, with limits of detection of 1.21 × 10-5 and 2.96 × 10-3 mg/kg in the vegetables under destructive conditions, and 0.13 and 1.39 ng/cm2 for non-destructive detection, respectively. The FCUAA substrate had high SERS performance, effective adsorption capability for OPs, and demonstrated good applicability, thus exhibiting great potential for rapid detection of trace OPs residues in the food industry.

Fast real-time monitoring of meat freshness based on fluorescent sensing array and deep learning: From development to deployment

A fluorescent sensor array (FSA) combined with deep learning (DL) techniques was developed for meat freshness real-time monitoring from development to deployment. The array was made up of copper metal nanoclusters (CuNCs) and fluorescent dyes, having a good ability in the quantitative and qualitative detection of ammonia, dimethylamine, and trimethylamine gases with a low limit of detection (as low as 131.56 ppb) in range of 5 ∼ 1000 ppm and visually monitoring the freshness of various meats stored at 4 °C. Moreover, SqueezeNet was applied to automatically identify the fresh level of meat based on FSA images with high accuracy (98.17 %) and further deployed in various production environments such as personal computers, mobile devices, and websites by using open neural network exchange (ONNX) technique. The entire meat freshness recognition process only takes 5 ∼ 7 s. Furthermore, gradient-weighted class activation mapping (Grad-CAM) and uniform manifold approximation and projection (UMAP) explanatory algorithms were used to improve the interpretability and transparency of SqueezeNet. Thus, this study shows a new idea for FSA assisted with DL in meat freshness intelligent monitoring from development to deployment.

Elevating nanomaterial optical sensor arrays through the integration of advanced machine learning techniques for enhancing visual inspection of food quality and safety

Food quality and safety problems caused by inefficient control in the food chain have significant implications for human health, social stability, and economic progress and optical sensor arrays (OSAs) can effectively address these challenges. This review aims to summarize the recent applications of nanomaterials-based OSA for food quality and safety visual monitoring, including colourimetric sensor array (CSA) and fluorescent sensor array (FSA). First, the fundamental properties of various advanced nanomaterials, mainly including metal nanoparticles (MNPs) and nanoclusters (MNCs), quantum dots (QDs), upconversion nanoparticles (UCNPs), and others, were described. Besides, the diverse machine learning (ML) and deep learning (DL) methods of high-dimensional data obtained from the responses between different sensing elements and analytes were presented. Moreover, the recent and representative applications in pesticide residues, heavy metal ions, bacterial contamination, antioxidants, flavor matters, and food freshness detection were comprehensively summarized. Finally, the challenges and future perspectives for nanomaterials-based OSAs are discussed. It is believed that with the advancements in artificial intelligence (AI) techniques and integrated technology, nanomaterials-based OSAs are expected to be an intelligent, effective, and rapid tool for food quality assessment and safety control.

Developing a magnetic SERS nanosensor utilizing aminated Fe-Based MOF for ultrasensitive trace detection of organophosphorus pesticides in apple juice

The unreasonable use of organophosphorus pesticides leads to excessive pesticide residues in food, seriously threatening public health, and the potential of surface-enhanced Raman spectroscopy (SERS) technology, incorporating a metal-organic framework, is substantial for the rapid detection of trace pesticide residues. Here, a novel Fe3O4@NH2-MIL-101(Fe)@Ag (FNMA) SERS nanosensor was developed. Results indicated that the FNMA had a high enhancement factor of 1.53 × 108, a low limit of detection (LOD) of 4.55 × 10-12 M, and a relative standard deviation of 7.73 % for 4-nitrothiophenol, demonstrating its good SERS sensitivity and uniformity, and also possessed good storage stability for one month. In quantifying fenthion and methyl parathion in standard solutions and apple juice in the range of 0.05/0.02-20 mg/L, it showed LODs of 3.02 × 10-3 mg/L and 1.43 × 10-3 mg/L, and 0.0407 and 0.0075 mg/L, respectively, demonstrating potentials in ultrasensitive trace detection of pesticides in food.

Visible detection of chilled beef freshness using a paper-based colourimetric sensor array combining with deep learning algorithms

This study developed an innovative approach that combines a colourimetric sensor array (CSA) composed of twelve pH-response dyes with advanced algorithms, aiming to detect amine gases and assess the freshness of chilled beef. With the assistance of multivariate statistical analysis, the sensor array can effectively distinguish five amine gases and enable rapid quantification of trimethylamine vapour with a limit of detection (LOD) of 8.02 ppb and visually monitor the fresh levels of chilled beef. Moreover, the utilization of deep learning models (ResNet34, VGG16, and GoogleNet) for chilled beef freshness evaluation achieved an overall accuracy of 98.0 %. Furthermore, t-distributed stochastic neighbour embedding (t-SNE) visualized the feature extraction process and provided explanations to understand the classification process of deep learning. The results demonstrated that applying deep learning techniques in the process of pattern recognition of CSA can help in realizing the rapid, robust, and accurate assessment of chilled beef freshness.

Dose-Dependent Effect on Plant Growth of Exposure to Metal-Organic Framework MIL-101(Cr)

With the increasing use of metal-organic frameworks (MOFs), they will inevitably enter the environment intentionally or unintentionally. However, the effects of MOFs on plant growth are poorly understood. Here, we investigated the effects of exposure of the rhizosphere to MOFs on plant growth. MIL-101(Cr) was selected as a research model due to its commercial availability and wide use. Soybean plants at the two-leaf stage were subjected to various durations (1-7 days) and concentrations (0-1000 mg/L) of exposure in hydroculture with a control group treated with ultrapure water. We found that MIL-101(Cr) had a positive effect on soybean growth at a lower dose (i.e., 200 mg/L); however, at higher doses (i.e., 500 and 1000 mg/L), it exhibited significant toxicity to plant growth, which is evidenced by leaf damage. To investigate the mechanism of this effect, we used Cr as an indicator to quantify, track, and image MIL-101(Cr) in the plant with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Results indicated that MIL-101(Cr) primarily accumulated in the cortex of roots (up to 40 times higher than that in stems), with limited translocation to stems and negligible presence in leaves and cotyledons. In addition, metabolomic analysis of soybeans indicated that low-dose MIL-101(Cr) could increase the sucrose content of soybean roots to promote plant growth, while a high dose could induce lipid oxidation in roots. This study provides valuable insights into the ecological toxicology of MOFs and underscores the importance of assessing their environmental impact for sustainable agricultural practices.

Terahertz spectra reconstructed using convolutional denoising autoencoder for identification of rice grains infested with Sitophilus oryzae at different growth stages

Rice grains are often infected by Sitophilus oryzae due to improper storage, resulting in quality and quantity losses. The efficacy of terahertz time-domain spectroscopy (THz-TDS) technology in detecting Sitophilus oryzae at different stages of infestation in stored rice was employed in the current research. Terahertz (THz) spectra for rice grains infested by Sitophilus oryzae at different growth stages were acquired. Then, the convolutional denoising autoencoder (CDAE) was used to reconstruct THz spectra to reduce the noise-to-signal ratio. Finally, a random forest classification (RFC) model was developed to identify the infestation levels. Results showed that the RFC model based on the reconstructed second-order derivative spectrum with an accuracy of 84.78%, a specificity of 86.75%, a sensitivity of 86.36% and an F1-score of 85.87% performed better than the original first-order derivative THz spectrum with an accuracy of 89.13%, a specificity of 91.38%, a sensitivity of 88.18% and an F1-score of 89.16%. In addition, the convolutional layers inside the CDAE were visualized using feature maps to explain the improvement in results, illustrating that the CDAE can eliminate noise in the spectral data. Overall, THz spectra reconstructed with the CDAE provided a novel method for effective THz detection of infected grains.

Metal-pyrimidine nanocubes immobilized enzymes with pH-switchable multienzyme-like activity for broad-pH-responsive sensing assay for organophosphorus pesticides

Peroxidase (POD)-like can only function in acidic environments and the pH mismatch restricts the application of enzyme-nanozyme cascade catalytic sensing platforms in the broad-pH-responsive assay for organophosphorus pesticides (OPs). Herein, the metal-pyrimidine nanocubes (MPNCs) with intrinsic pH-switchable POD-like and catalase (CAT)-like properties were synthesized via the coordination of pyrimidin-2-ol with Cu2+. Meanwhile, acetylcholinesterase (AChE) and choline oxidase (CHO) were simultaneously encapsulated in MPNCs to construct an enzyme-nanozyme cascade catalytic platform (AChE/CHO@MPNCs). AChE/CHO@MPNCs could catalyze the hydrolysis of acetylcholine to choline, which was subsequently converted to H2O2. The POD-like activity of MPNCs was dominant under acidic conditions, while the CAT-like activity prevailed under neutral and alkaline conditions, which could catalyze H2O2 to •OH and O2, respectively, then oxidizing dopamine (DA) to polydopamine quantum dots (PDA QDs) with different fluorescence characteristics. Consequently, OPs could be detected in a linear range from 0.05 to 1000 nM with a LOD of 0.015 nM in acidic environments and a linear range from 0.05 to 500 nM with a LOD of 0.023 nM in alkaline environments. Overall, our work expands the horizon of constructing enzyme@MOFs composites with high catalytic activity. Meanwhile, the intrinsic pH-switchable multienzyme-like property opens avenues to construct sensing platforms with broad-pH-responsive for OPs and other analytes detection.

A durian-shaped multilayer core-shell SERS substrate for flow magnetic detection of pesticide residues on foods

A new type of durian-shaped Fe3O4@Au@Ag@Au (DFAAA) multilayer core-shell composite was prepared as an efficient surface-enhanced Raman scattering (SERS) substrate. The optimization process and SERS enhancement mechanism of the substrate were further explained with finite-difference time-domain simulation. The dense and uniform spiny array on the DFAAA surface had abundant "hot spots", greatly improving sensitivity, uniformity and reproducibility, with a Raman enhancement factor of 3.01 × 107 and storage-life of 30 d. A "flow magnetic detection method" was proposed to realize rapid and flexible detection of pesticide residues on the surface of different foods including fish and apple. The limit of detection of malachite green and thiram on the fish and apple surfaces were 0.13 and 0.18 ng/cm2, respectively. With its high SERS performance and good magnetic, the DFAAA possessed great application prospects as a facile SERS substrate for rapid and non-destructive detection of trace pesticide residues on foods.

Fluorescent polythymidine-templated copper nanoclusters aptasensor for sensitive detection of tropomyosin in processed shrimp products

Tropomyosin (TM) is the main allergen in shellfish. Developing a novel, simple and accurate method to track and detect TM in food products is necessary. In this work, a label-free fluorescent aptasensor based on polythymidine (poly(T))-templated copper nanoclusters (CuNCs) was designed for sensitive detection of TM in processed shrimp products. Magnetic beads (MBs), aptamer and cDNA were used to construct an MBs-aptamer@cDNA complex as a detection probe, and with the presence of TM, the poly(T)-templated CuNCs attached at the end of the cDNA as the fluorescent signal was released from the complex to turn on the fluorescence. Under optimal conditions, the poly(T)-templated CuNCs aptasensor achieved a linear range from 0.1 to 50 μg/mL (R2 = 0.9980), a low limit of detection of 0.0489 μg/mL and an excellent recovery percentage of 105.29%-108.91% in the complex food matrix, providing a new approach for food safety assurance.

A three-dimensional gold nanoparticles spherical liquid array for SERS sensitive detection of pesticide residues in apple

High-performance plasmonic substrates have recently attracted much research attention. Herein, a three-dimensional gold nanoparticles (AuNPs) spherical liquid array (SLA) with high "hot spots" and tunable nanometer gap by optimizing the proportion of AuNPs colloids over chloroform was synthesized based on a water-oil interfacial self-assembly strategy. The substrate demonstrated excellent surface-enhanced Raman scattering (SERS) performance using tetrathiafulvalene and rhodamine 6G (R6G) as probe molecules. With a simple extraction and soaking pretreatment process, the SLA exhibited high sensitivity for analysing triazophos on apple peels, with a limit of detection (LOD) of 0.005 µg/mL and recovery ranging from 96 to 110 %. Particularly, the chloroform produced an inherent characteristic peak at 665 cm-1, which was used as the internal standard to correct SERS signal fluctuation, leading to an improvement of the corresponding coefficient R2 from 0.97 to 0.99, thus improving the reproducibility. Therefore the SLA substrate possesses the potential for quantitative analysis of food contaminants.

Visualization detection of mycotoxin patulin in fruit juices by a small-molecule fluorescent probe

The mycotoxin patulin is a common contaminant in rotten fruits, posing severe food safety risks and threats to human health. Developing a convenient, sensitive and reliable method for patulin detection is of utmost importance but remains challenging. In this study, we have successfully designed and synthesized a small-molecule fluorescent probe, FITC-Lys, which demonstrates good sensitivity in detecting patulin. Upon contact with patulin, the terminal Lys group of the FITC-Lys probe reacts with patulin, resulting in the formation of the fluorescein dimer that subsequently quenches fluorescence. This variation of fluorescence enables the visualization and sensitive detection of patulin. The probe exhibits good sensitivity with a low LOD of 8 ng mL-1 for the fluorescence spectrum method and a LOD of 12 ng mL-1 for the fluorescence imaging method. Moreover, we have validated the probe's capability for patulin detection in apple and pear juices, achieving good recoveries ranging from 98.60% to 103.80%. Notably, the probe FITC-Lys is the first small-molecule fluorescent probe that has proven successful in visualizing patulin in juices derived from decayed apples and pears. Consequently, this probe holds great potential as a practical tool for monitoring patulin in foodstuffs, thereby contributing to enhanced food safety standards.

Aggregates-based fluorescence sensing technology for food hazard detection: Principles, improvement strategies, and applications

Aggregates often exhibit modified or completely new properties compared with their molecular elements, making them an extraordinarily advantageous form of materials. The fluorescence signal change characteristics resulting from molecular aggregation endow aggregates with high sensitivity and broad applicability. In molecular aggregates, the photoluminescence properties at the molecular level can be annihilated or elevated, leading to aggregation-causing quenching (ACQ) or aggregation-induced emission (AIE) effects. This change in photoluminescence properties can be intelligently introduced in food hazard detection. Recognition units can combine with the aggregate-based sensor by joining the aggregation process, endowing the sensor with the high specificity of analytes (such as mycotoxins, pathogens, and complex organic molecules). In this review, aggregation mechanisms, structural characteristics of fluorescent materials (including ACQ/AIE-activated), and their applications in food hazard detection (with/without recognition units) are summarized. Because the design of aggregate-based sensors may be influenced by the properties of their components, the sensing mechanisms of different fluorescent materials were described separately. Details of fluorescent materials, including conventional organic dyes, carbon nanomaterials, quantum dots, polymers and polymer-based nanostructures and metal nanoclusters, and recognition units, such as aptamer, antibody, molecular imprinting, and host-guest recognition, are discussed. In addition, future trends of developing aggregate-based fluorescence sensing technology in monitoring food hazards are also proposed.

Latest advances in layered covalent organic frameworks for water and wastewater treatment

This review provides an overview of recent progress in the development of layered covalent organic frameworks (LCOFs) for the adsorption and degradation of pollutants in water and wastewater treatment. LCOFs have unique properties such as high surface area, porosity, and tunability, which make them attractive adsorbents and catalysts for water and wastewater treatment. The review covers the different synthesis methods for LCOFs, including self-assembly, co-crystallization, template-directed synthesis, covalent organic polymerization (COP), and solvothermal synthesis. It also covers the structural and chemical characteristics of LCOFs, their adsorption and degradation capacity for different pollutants, and their comparison with other adsorbents and catalysts. Additionally, it discussed the mechanism of adsorption and degradation by LCOFs, the potential applications of LCOFs in water and wastewater treatment, case studies and pilot-scale experiments, challenges, and limitations of using LCOFs, and future research directions. The current state of research on LCOFs for water and wastewater treatment is promising, however, more research is needed to improve their performance and practicality. The review highlights that LCOFs have the potential to significantly improve the efficiency and effectiveness of current water and wastewater treatment methods and can also have implications for policy and practice.

Preparation of Fe3O4@UiO-66(Zr)@Ag NPs core-shell-satellite structured SERS substrate for trace detection of organophosphorus pesticides residues

Surface-enhanced Raman spectroscopy (SERS) technology has been revived and developed with the introduction of metal-organic frameworks (MOFs), while more valuable properties of MOFs for SERS substrates remain largely unexplored. This work constructed a new SERS substrate Fe₃O₄@UiO-66(Zr)@Ag nanoparticles (FUAs) with excellent SERS detection sensitivity, uniformity, reproducibility and stability, exhibiting a high Raman enhancement factor (5.62 × 10⁶), low limit of detection (LOD, 2.11 × 10^-11 M) and RSD (12.41 %) for 4-NBT, and maintaining 81 % SERS activity within 60 days. The FUAs took full advantage of the strong affinity of UiO-66(Zr) for organophosphorus pesticides (OPs) to realize trace OPs detection. The LODs of phoxim, triazophos and methyl parathion in apple juice were 0.041, 0.021 and 0.0031 mg/L, respectively, with good linearities ranging from 0.02 or 0.1-50 mg/L, meeting the requirements of the food control standards, indicating that the potentials and prospects of the FUAs SERS substrate for trace detecting OPs in foods.

Photoexcited Ru single-atomic sites for efficient biomimetic redox catalysis

The unsatisfactory catalytic activity of nanozymes owing to their inefficient electron transfer (ET) is the major challenge in biomimetic catalysis-related biomedical applications. Inspired by the photoelectron transfers in natural photoenzymes, we herein report a photonanozyme of single-atom Ru anchored on metal-organic frameworks (UiO-67-Ru) for achieving photoenhanced peroxidase (POD)-like activity. We demonstrate that the atomically dispersed Ru sites can realize high photoelectric conversion efficiency, superior POD-like activity (7.0-fold photoactivity enhancement relative to that of UiO-67), and good catalytic specificity. Both in situ experiments and theoretical calculations reveal that photoelectrons follow the cofactor-mediated ET process of enzymes to promote the production of active intermediates and the release of products, demonstrating more favorable thermodynamics and kinetics in H2O2 reduction. Taking advantage of the unique interaction of the Zr-O-P bond, we establish a UiO-67-Ru-based immunoassay platform for the photoenhanced detection of organophosphorus pesticides.

Distinguishing pericarpium citri reticulatae of different origins using terahertz time-domain spectroscopy combined with convolutional neural networks

The geographical indication of pericarpium citri reticulatae (PCR) is very important in grading the quality and price of PCRs. Therefore, terahertz time-domain spectroscopy (THz-TDS) technology combined with convolutional neural networks (CNN) was proposed to distinguish PCRs of different origins without damage in this study. The one-dimensional CNN (1D-CNN) model with an accuracy of 82.99% based on spectral data processed with SNV was established. The two-dimensional image features were transformed from unprocessed spectral data using the gramian angular field (GAF), the Markov transition field (MTF) and the recurrence plot (RP), which were used to build a two-dimensional CNN (2D-CNN) model with an accuracy of 78.33%. Further, the CNN models with different fusion methods were developed for fusing spectra data and image data. In addition, the adding spectra and images based on the CNN (Add-CNN) model with an accuracy of 86.17% performed better. Eventually, the Add-CNN model based on ten frequencies extracted using permutation importance (PI) achieved the identification of PCRs from different origins. Overall, the current study would provide a new method for identifying PCRs of different origins, which was expected to be used for the traceability of PCRs products.

Multifunctional Metal-Organic Framework (MOF)-Based Nanoplatforms for Crop Protection and Growth Promotion

Phytopathogen, pest, weed, and nutrient deficiency cause severe losses to global crop yields every year. As the core engine, agrochemicals drive the continuous development of modern agriculture to meet the demand for agricultural productivity and increase the environmental burden due to inefficient use. With new advances in nanotechnology, introducing nanomaterials into agriculture to realize agrochemical accurate and targeted delivery has brought new opportunities to support the sustainable development of green agriculture. Metal-Organic frameworks (MOFs), which weave metal ions/clusters and organic ligands into porous frameworks, have exhibited significant advantages in constructing biotic/abiotic stimuli-responsive nanoplatforms for controlled agrochemical delivery. This review emphasizes the recent developments of MOF-based nanoplatforms for crop protection, including phytopathogen, pest, and weed control, and crop growth promotion, including fertilizer/plant hormone delivery. Finally, forward-looking perspectives and challenges on MOF-based nanoplatforms for future applications in crop protection and growth promotion are also discussed.

Multiplex Surface-Enhanced Raman Scattering: An Emerging Tool for Multicomponent Detection of Food Contaminants

For survival and quality of human life, the search for better ways to ensure food safety is constant. However, food contaminants still threaten human health throughout the food chain. In particular, food systems are often polluted with multiple contaminants simultaneously, which can cause synergistic effects and greatly increase food toxicity. Therefore, the establishment of multiple food contaminant detection methods is significant in food safety control. The surface-enhanced Raman scattering (SERS) technique has emerged as a potent candidate for the detection of multicomponents simultaneously. The current review focuses on the SERS-based strategies in multicomponent detection, including the combination of chromatography methods, chemometrics, and microfluidic engineering with the SERS technique. Furthermore, recent applications of SERS in the detection of multiple foodborne bacteria, pesticides, veterinary drugs, food adulterants, mycotoxins and polycyclic aromatic hydrocarbons are summarized. Finally, challenges and future prospects for the SERS-based detection of multiple food contaminants are discussed to provide research orientation for further.

Discrimination of Pericarpium Citri Reticulatae in different years using Terahertz Time-Domain spectroscopy combined with convolutional neural network

Pericarpium Citri Reticulatae (PCR) in longer storage years possess higher medicinal values, but their differentiation is difficult due to similar morphological characteristics. Therefore, this study investigated the feasibility of using terahertz time-domain spectroscopy (THz-TDS) combined with a convolutional neural network (CNN) to identify PCR samples stored from 1 to 20 years. The absorption coefficient and refractive index spectra in the range of 0.2-1.5 THz were acquired. Partial least squares discriminant analysis, random forest, least squares support vector machines, and CNN were used to establish discriminant models, showing better performance of the CNN model than the others. In addition, the output data points of the CNN intermediate layer were visualized, illustrating gradual changes in these points from overlapping to clear separation. Overall, THz-TDS combined with CNN models could realize rapid identification of different year PCRs, thus providing an efficient alternative method for PCR quality inspection.

A SERS-Fluorescence dual-signal aptasensor for sensitive and robust determination of AFB1 in nut samples based on Apt-Cy5 and MNP@Ag-PEI

Food aflatoxin B1 (AFB1) contamination greatly threatens human health and its sensitive determination is imperative. In this study, a surface-enhanced Raman scattering (SERS) and fluorescence dual-signal aptasensor was constructed for sensitive AFB1 detection in peanuts, walnuts, and almonds samples. Fluorescent dye cy5 was used as fluorophore and Raman reporter, while polyethyleneimine modified Ag coating magnetic nanoparticles (MNP@Ag-PEI) were utilized to absorb the cy5 modified aptamer (apt-cy5). Results indicated that linear ranges of 0.001-1000 ng/mL and 0.2-20,000 ng/mL with detection limits of 0.45 pg/mL and 0.135 ng/mL for the SERS and fluorescence methods were obtained, respectively, and AFB1 detection in the nut samples using the aptasensor achieved satisfactory recoveries of 95.2%-108.6% for SERS and 94.7%-109.7% for fluorescence. Compared with other mono signal detection, the established aptasensor facilely fused the merits of the two signals and improved the detection accuracy and flexibility.

Analysis and detection using novel terahertz spectroscopy technique in dietary carbohydrate-related research: Principles and application advances

As one of the main functional substances, carbohydrates account for a large proportion of the human diet. Conventional analysis and detection methods of dietary carbohydrates and related products are destructive, time-consuming, and labor-intensive. In order to improve the efficiency of measurement and ensure food nutrition and consumer health, rapid and nondestructive quality evaluation techniques are needed. In recent years, terahertz (THz) spectroscopy, as a novel detection technology with dual characteristics of microwave and infrared, has shown great potential in dietary carbohydrate analysis. The current review aims to provide an up-to-date overview of research advances in using the THz spectroscopy technique in analysis and detection applications related to dietary carbohydrates. In the review, the principles of the THz spectroscopy technique are introduced. Advances in THz spectroscopy for quantitative and qualitative analysis and detection in dietary carbohydrate-related research studies from 2013 to 2022 are discussed, which include analysis of carbohydrate concentrations in liquid and powdery foods, detection of foreign body and chemical residues in carbohydrate food products, authentication of natural carbohydrate produce, monitoring of the fermentation process in carbohydrate food production and examination of crystallinity in carbohydrate polymers. In addition, applications in dietary carbohydrate-related detection research using other spectroscopic techniques are also briefed for comparison, and future development trends of THz spectroscopy in this field are finally highlighted.

Synthesis of recyclable SERS platform based on MoS2@TiO2@Au heterojunction for photodegradation and identification of fungicides

Surface-enhanced Raman spectroscopy (SERS) substrates based on metal/semiconductors have attracted much attention due to their excellent photocatalytic activity and SERS performance. However, they generally exhibit low light utilization and photocatalytic efficiencies. Herein, molybdenum disulfide coated titanium dioxide modified with gold nanoparticles (MoS₂@TiO₂@Au) as a heterojunction-based recyclable SERS platform was fabricated for the efficient determination of fungicides. Results showed that the MoS₂@TiO₂@Au platform could rapidly degrade 90.7% crystal violet in 120 min under solar light irradiation and enable reproducible and sensitive SERS analysis of three fungicides (methylene blue, malachite green, and crystal violet) and in-situ monitor of the photodegradation process. The platform could also be reused five times due to the unique integrated merits of the MoS₂@TiO₂@Au heterojunction. Meanwhile, experiments in determining methylene blue in prawn protein solution achieved a limit of detection of 1.509 μg/L. Therefore, it is hoped that this work could expand detection applications of photocatalytic materials.

Mesoporous silica coated core-shell nanoparticles substrate for size-selective SERS detection of chloramphenicol

With the growing popularity of the non-destructive technique, surface-enhanced Raman spectroscopy (SERS) demands a highly sensitive and reproducible plasmonic nanoparticles substrate. In this study, a novel bimetallic core-shell nanoparticles (Au@Ag@mSiO₂NP) substrate consisting of a gold core, silver shell, and a mesoporous silica coating was synthesized. The mesoporous coating structure was created by employing template molecules such as surfactant and their subsequent removal allowing selective screening based on the size of analyte molecules. Results showed that the plasmonic substrate could selectively enhance small molecules by preventing large macromolecules to reach the exciting zone of the substrate core, achieving the detection of chloramphenicol in milk samples with a detection limit of 6.68 × 10^-8 M. Moreover, the mesoporous coating provided additional stability to the Au@Ag nanoparticles, leading to the reusability of the substrate. Thus, this work offered a simple and smart Au@Ag@mSiO₂NP substrate for effective SERS detection of analytes.

Blood-Coagulation-Inspired Dynamic Bridging Strategy for the Fabrication of Multiscale-Assembled Hierarchical Porous Material

Porous materials, from macroscopic bulk materials (MBs) with (sub-)millimeter-scale pores to tiny particles (TPs) with (sub-)nanometer-scale pores, have attracted ever-growing interest in various fields. However, the integration of multi-scale pores in one composite is promising but challenging, owing to the considerable gap in the scale of the pores. Inspired by blood coagulation, a fibrin-based dynamic bridging strategy is developed to fabricate a multiscale-assembled hierarchical porous material (MHPM), in which fibrin formed as the sub-framework for the weaving-narrow of MBs and the enwinding-load of TPs. The bio-polymerization nature makes the fabrication rapid, facile, and universal for the customizable integration of seven kinds of TPs and four kinds of MBs. Besides, the integration is controllable with high load capacity of TPs and is stable against external shock forces. The unique multi-level structure endows the MHPM with large and accessible surface area, and efficient mass transfer pathways, synergistically leading to high adsorption capacity and rapid kinetics in multiple adsorption models. This work suggests a strategy for the rational multi-level design and fabrication of hierarchical porous architectures.

Rational Synthesis of a Stable Rod MOF for Ultrasensitive Detection of Nitenpyram and Nitrofurazone in Natural Water Systems

Overuse of nitenpyram and nitrofurazone in agricultural products poses enormous risks to ecosystems, and effective detection and quantification of these residual pollutants are of great concern. Although several strategies have been established for detecting nitenpyram and nitrofurazone in water, searching for a new sensor material with great sensitivity, selectivity, and recyclability remains challenging. Here, we design and synthesize a stable metal-organic framework (MOF) (Zn-CPTA) by employing an organic linker based on the coordination features of benzene-1,4-dicarboxylate and picolinic acid. Zn-CPTA is a 3D framework built from Zn-O-Zn chains called rod secondary building units, which contains 1D open channels modified by uncoordinated carboxyl O atoms and exhibits impressive chemical stability in aqueous solutions within a pH range from 2 to 12. Especially, fluorescent Zn-CPTA can quickly and sensitively detect nitenpyram and nitrofurazone in aqueous solutions with a high quenching constant and low detection limit (LOD) (K_SV values for nitenpyram and nitrofurazone are 1.67 × 10⁴ and 1.02 × 10⁵ M^-1 with LOD of 0.625 and 0.126 μM, respectively), as well as outstanding selectivity and recyclability. Notably, the LOD value is the lowest among the reported MOFs used for nitrofurazone detection. Besides, experiments and density functional theory calculations are combined to explain the quenching mechanism. Finally, the practical application of Zn-CPTA was further explored in real environment samples with satisfactory recoveries.

Recent Progress in Nanotechnology-Based Approaches for Food Monitoring

Throughout the food supply chain, including production, storage, and distribution, food can be contaminated by harmful chemicals and microorganisms, resulting in a severe threat to human health. In recent years, the rapid advancement and development of nanotechnology proposed revolutionary solutions to solve several problems in scientific and industrial areas, including food monitoring. Nanotechnology can be incorporated into chemical and biological sensors to improve analytical performance, such as response time, sensitivity, selectivity, reliability, and accuracy. Based on the characteristics of the contaminants and the detection methods, nanotechnology can be applied in different ways in order to improve conventional techniques. Nanomaterials such as nanoparticles, nanorods, nanosheets, nanocomposites, nanotubes, and nanowires provide various functions for the immobilization and labeling of contaminants in electrochemical and optical detection. This review summarizes the recent advances in nanotechnology for detecting chemical and biological contaminations in the food supply chain.

Surface-enhanced Raman spectroscopy combined with stable isotope probing to assess the metabolic activity of Escherichia coli cells in chicken carcass wash water

Rapid evaluation of the metabolic activity of microorganisms is crucial in the assessment of the disinfection ability of various antimicrobial agents in the food industry. In this study, surface-enhanced Raman spectroscopy combined with isotope probing was employed for the analysis of the disinfection of single bacterial cells in the chicken carcass wash water. The Raman signals from single Escherichia coli O157:H7 cells were enhanced by in situ synthesis of silver nanoparticles. The ΔCD of the cells grown in presence of 0.5% hydrogen peroxide and 50 ppm chlorine was 5.86 ± 1.86% and 5.1 ± 2.3%, respectively, which showed significant reduction compared with cells grown in the absence of disinfecting agents (19.86 ± 2.51%) after 2 h of incubation. The study proved that the proposed method had the potential to assess the metabolic activity of microorganisms in other food products and optimize the disinfection process.

Crystal structure of dichlorido-tetra((E)-(RS)-1-(2,4-dichlorophenyl)-4,4-dimethyl-2-(1,2,4-triazol-1-yl)pent-1-en-3-ol-κ1 N)zinc(II), C60H68O4N12Cl10Zn

C60H68O4N12Cl10Zn, triclinic, P 1 ‾ $\overline{1}$ (no. 2), a = 8.816 (2) Å, b = 13.688 (4) Å, c = 15.169 (4) Å, α = 91.085 (5)°, β = 98.609 (4)°, γ = 106.874 (5)°, V = 1728.2 (8) A3, Z = 1, Rgt (F) = 0.0615, wR ref (F 2) = 0.1709, T = 296 (2) K.

Halloysite Nanotube-Based Pesticide Formulations with Enhanced Rain Erosion Resistance, Foliar Adhesion, and Insecticidal Effect

The incorporation of green and sustainable nanomaterials in pesticide formation is an effective method to lower the use of conventional pesticides without adverse effects on productivity. Here pesticide Pickering emulsions stabilized by halloysite nanotubes (HNTs) were developed for low cost, less environmental pollution, low toxic effects, and better emulsion stability. HNTs were added to chlorantraniliprole (CAP) emulsions, and good stability was exhibited due to the adsorption and aggregation of HNTs at the interface of CAP oil droplets, forming a three-dimensional network structure that prevented the emulsion from aggregation. In addition, Spodoptera frugiperda was used as a pest model and corn was used as a plant model to explore the washout resistance, insecticidal effect, and biological safety of HNTs-CAP emulsion. After spraying emulsion on corn leaves and washing for 10 min, the HNTs-CAP emulsion (5 wt % HNTs) pesticide residue rate was 2.7 times that of pristine CAP emulsion. When the HNT dispersion concentration was 2 wt %, the larva mortality was 83%, which was 1.5 times that of the CAP emulsion group. These results demonstrated that HNTs-CAP emulsion showed good foliar adhesion, rainfall resistance, and insecticidal effect. The tubular clay-based nanopesticide formulations show potential applications in the control of crop pests with modern agriculture technology.

Progress in Hybridization of Covalent Organic Frameworks and Metal-Organic Frameworks

Metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) hybrid materials are a class of porous crystalline materials that integrate MOFs and COFs with hierarchical pore structures. As an emerging porous frame material platform, MOF/COF hybrid materials have attracted tremendous attention, and the field is advancing rapidly and extending into more diverse fields. Extensive studies have shown that a broad variety of MOF/COF hybrid materials with different structures and specific properties can be synthesized from diverse building blocks via different chemical reactions, driving the rapid growth of the field. The allowed complementary utilization of π-conjugated skeletons and nanopores for functional exploration has endowed these hybrid materials with great potential in challenging energy and environmental issues. It is necessary to prepare a "family tree" to accurately trace the developments in the study of MOF/COF hybrid materials. This review comprehensively summarizes the latest achievements and advancements in the design and synthesis of MOF/COF hybrid materials, including COFs covalently bonded to the surface functional groups of MOFs (MOF@COF), MOFs grown on the surface of COFs (COF@MOF), bridge reaction between COF and MOF (MOF+COF), and their various applications in catalysis, energy storage, pollutant adsorption, gas separation, chemical sensing, and biomedicine. It concludes with remarks concerning the trend from the structural design to functional exploration and potential applications of MOF/COF hybrid materials.

Visualization and quantification of content and hydrogen bonding state of water in apple and potato cells by confocal Raman microscopy: A comparison study

Water is the most abundant component in fresh fruit and vegetables and its distribution and hydrogen bonding state in cells has a significant influence on food processing. In the current study, an improved method based on our earlier studies was developed to directly visualize the spatial distribution of content and hydrogen bonding state of water in apple and potato cells for the first time and the difference in water distribution in these cells was compared. Additionally, based on the distribution images of content and hydrogen bonding state of water in different regions in apple and potato tissues, the total water and free water contents, and the hydrogen bonding state of free water were quantified and compared with those obtained by nuclear magnetic resonance and Marinchik methods, demonstrating that the method could be successfully used for quantifying the content and hydrogen bonding state of water in fruit and vegetable cells.

Analyzing macromolecular composition of E. Coli O157:H7 using Raman-stable isotope probing

Metabolic dynamics of bacterial cells is needed for understanding the correlation between changes in environmental conditions and cell metabolic activity. In this study, Raman spectroscopy combined with deuterium labelling was used to analyze the metabolic activity of a single Escherichia coli O157:H7 cell. The incorporation of deuterium from heavy water into cellular biomolecules resulted in the formation of carbon-deuterium (CD) peaks in the Raman spectra, indicating the cell metabolic activity. The broad vibrational peaks corresponding to CD and CH peaks encompassed different specific shifts of macromolecules such as protein, lipids, and nucleic acid. The utilization of tryptophan and oleic acid by the cell as the sole carbon source led to changes in cell lipid composition, as indicated by new peaks in the second derivative spectra. Thus, the proposed method could semi-quantitatively determine total metabolic activity, macromolecule specific identification, and lipid and protein metabolism in a single cell.

Detection of Bioactive Metabolites in Escherichia Coli Cultures Using Surface-Enhanced Raman Spectroscopy

Detection of bioactive metabolites produced by bacteria is important for identifying biomarkers for infectious diseases. In this study, a surface-enhanced Raman spectroscopy (SERS)-based technique was developed for the detection of bioactive metabolite indole produced by Escherichia coli (E. coli) in biological media. The use of highly sensitive Au@Ag core-shell nanoparticles resulted in the detection of indole concentration as low as 0.0886 mM in standard solution. The supplementation of growth media with 5 mM of exogenous tryptophan resulted in the production of a maximum yield of indole of 3.139 mM by E. coli O157:H7 at 37 °C. The growth of bacterial cells was reduced from 47.73 × 10⁸ to 1.033 × 10⁶ CFU/mL when the cells were grown in 0 and 10 mM exogenous tryptophan, respectively. The amount of indole in the Luria-Bertani (LB) media had an inverse correlation with the growth of cells, which resulted in a three-log reduction in the colony-forming unit when the indole concentration in the media was 20 times higher than normal. This work demonstrates that SERS is an effective and highly sensitive method for rapid detection of bioactive metabolites in biological matrix.

Chitosan-based organic/inorganic composite engineered for UV light-controlled smart pH-responsive pesticide through in situ photo-induced generation of acid

BACKGROUND

Confined by the volatile property, pesticides are overused and lost significantly during and after spraying, weakening the ecological microbalance among different species of lives. Acid-responsive pesticide is a type of smartly engineered pesticides that contribute to the improvement of utilization efficiency of pesticidal active ingredients in acid-controlled manner, whilst the implementation of acidic solutions may disturb the balance of microenvironment surrounding targeted plants or cause secondary pollution, underscoring the input of acid in a more precise strategy.

RESULTS

Chitosan was chemically modified with a photoacid generator (2-nitrobenzaldehyde) serving as a light-maneuvered acid self-supplier, based on which a smart pesticide was formulated by the integration of attapulgite and organophosphate insecticide chlorpyrifos. Under the irradiation of UV light (365 nm), the modified chitosan would undergo a photolytic reaction to generate an acid and pristine chitosan, which seized the labile protons and facilitated the release of chlorpyrifos based on its inherent pH-responsive flexibility. According to the pesticide release performance, the release rate of chlorpyrifos under UV light (27.2 mW/cm² ) reached 78%, significantly higher than those under sunlight (22%, 4.2 mW/cm² ) and in the dark (20%) within the same time, consistent with the pH reduction to 5.3 under UV light and no obvious pH change for the two other situations, exhibiting an attractive UV light-controlled, acid-propelled release behavior.

CONCLUSION

Compared to direct acid spray approach, the proposed in situ photo-induced generation of acid locally on the spots of applied pesticide circumvents the problem of acid contamination to nontargets, demonstrating higher efficiency and biocompatibility for the controlled delivery of acid-responsive pesticides and pest management. © 2022 Society of Chemical Industry.

Gas sensing based on metal-organic frameworks: Concepts, functions, and developments

Effective detection of pollutant gases is vital for protection of natural environment and human health. There is an increasing demand for sensing devices that are equipped with high sensitivity, fast response/recovery speed, and remarkable selectivity. Particularly, attention is given to the designability of sensing materials with porous structures. Among diverse kinds of porous materials, metal-organic frameworks (MOFs) exhibit high porosity, high degree of crystallinity and exceptional chemical activity. Their strong host-guest interactions with guest molecules facilitate the application of MOFs in adsorption, catalysis and sensing systems. In particular, the tailorable framework/composition and potential for post-synthetic modification of MOFs endow them with widely promising application in gas sensing devices. In this review, we outlined the fundamental aspects and applications of MOFs for gas sensors, and discussed various techniques of monitoring gases based on MOFs as functional materials. Insights and perspectives for further challenges faced by MOFs are discussed in the end.

Photosensitized Peroxidase Mimicry at the Hierarchical 0D/2D Heterojunction-Like Quasi Metal-Organic Framework Interface for Boosting Biocatalytic Disinfection

Metal-organic frameworks (MOFs) are a versatile toolbox for the bioinspired design of nanozymes for antibacterial applications and beyond, however, designing a nanozyme by the hierarchical quasi-MOF scheme remains largely unpracticed. This work exemplifies the preferential structure-activity correlation of a bimetallic quasi-MOF (Q-MOF_Ce0.5 ) among three series of MOF-derived peroxidase (POD) mimics. The biomimetic quasi-MOF_Ce0.5 nanosheets accommodate both oxygen vacancy-coupled multivalent redox cycles and photosensitive energy band layout, benefiting from the hierarchical heterojunction-like 0D/2D interface featuring isolated nodes-derived CeOCu sites upon the 2D decarboxylated MOF scaffold. These integrated unique merits enable the POD-like Q-MOF_Ce0.5 to generate sustained reactive oxygen species to effectively eradicate the surface-adhered bacteria under visible light, resulting in significant inactivation of Escherichia coli (99.74 %) and Staphylococcus aureus (99.35%) in vitro, and potent disinfection of skin wounds in vivo in safe and on-demand manners. It is hoped that this work can intensify the interventions of MOF nanozymes against the microbial world.

MOF Hybrid for Long-Term Pest Management and Micronutrient Supply Triggered with Protease

Advanced intelligent systems for delivery of pesticides or fertilizers require formulations that allow for long-term efficacy. In this work, a metal-organic framework (MOF) hybrid was developed for long-term pest management and micronutrient supply. Zeolitic imidazolate framework-8 was fabricated for crop micronutrients (Zn²⁺) supply and insecticide dinotefuran (DNF) encapsulation. Polymethylmethacrylate was polymerized in situ to impart the MOF hybrid with sustained cargo delivery. Then, zein was introduced to facilitate protease-triggered cargo release associated with the microenvironment of pests and targeted release. The resulting MOF hybrid exhibited stimulus-responsive, slow-release behaviors. Sustained DNF delivery was achieved over a period of at least 32 days in soil. Compared with that of free DNF, the UV resistance of DNF in the MOF hybrid increased by nearly 10 times, and the insecticidal efficiency increased 33.3% with leaching treatment and 40.1% after incubating in a greenhouse for 14 days. This MOF hybrid provides a controlled, targeted, and sustained delivery formulation for long-term pest management and crop micronutrient supply and has huge application prospects in sustainable agriculture.

Indole/Tetrahydroquinoline as Renewable Natural Resource-Inspired Scaffolds in the Devising and Preparation of Potential Fungicide Candidates

As a continuous effort toward developing novel and highly efficient agrochemicals for integrated management of crop pathogens, two series of oxime ester derivatives from indole and tetrahydroquinoline natural scaffolds were prepared. Guided by the preliminary inhibition rates against ubiquitous and representative fungi, the antifungal profile of the target compounds against Valsa mali was intensively and extensively studied. The tetrahydroquinoline-based derivatives 12a-12r exerted a promising inhibition effect, especially against V. mali. The remarkable compounds 12p (R = 4-OCF₃) and 12r (R = 4-OBn) with EC₅₀ values of 0.81 and 0.47 μg/mL, respectively, have a far more prominent activity than commercial fungicide trifloxystrobin. The biochemistry and physiology responses of V. mali after treatment with target compound 12p was examined, and the fruit body production, hyphae morphology, and organelles were profoundly affected. Moreover, the curative effects of compound 12p on apple detached branches and leaves were 57.69 and 64.84% at 100 μg/mL, respectively, which were even superior to that of trifloxystrobin. Meanwhile, the three-dimensional quantitative structure-activity relationship model [comparative molecular field analysis (CoMFA): q² = 0.823, r² = 0.924, F = 189.781, and standard error of estimation (SEE) = 0.138 and comparative molecular similarity index analysis (CoMSIA): q² = 0.795, r² = 0.904, F = 145.644, and SEE = 0.156] indicated that the antifungal activity of target compounds was facilitated by crucial structural factors, which would render inspiration for further design and discovery of novel fungicidal candidates.

A fluorescence aptasensor based on carbon quantum dots and magnetic Fe3O4 nanoparticles for highly sensitive detection of 17β-estradiol

Trace amounts of 17β-estradiol (E2) in food and the environment poses a threat to human health, which has created the demand for sensitive analytical methods to detect E2. In this study, a novel fluorescent aptasensor was developed for sensitive detection of E2 based on double-chain hybridization between carbon quantum dots-labelled with E2 aptamer (CQDs-aptamer) and Fe₃O₄ nanoparticles modified by complementary DNA (Fe₃O₄-cDNA). Under the optimal conditions, the aptasensor displayed a good linear range of 10^-11-10^-6 M for E2 with the coefficient of determination (R²) of 0.996, and a low detection limit of 3.48 × 10^-12 M was obtained. Besides, the aptasensor showed high selectivity and good reproducibility for E2 detection, which was successfully applied to the sensitive detection of E2 in milk as compared with tap water and lake water with satisfactory recoveries from 85.21% to 114.80%, suggesting the great significance of this aptasensor for detecting food contaminants in the food industry.