Computational insights into the structure and decomposition behaviors of 2,4,6-triamino-5-nitropyrimidine-1,3-dioxide under high pressure up to 10 GPa.

CONTEXT: Inspired by the recent successful synthesis of the energetic compound 2,4,6-triamino-5-nitropyrimidine-1,3-dioxide (ICM-102), which displayed a good balance between high energy and sensitivity, the response of the structure and decomposition behaviors of ICM-102 to high pressure was systematically investigated using first principle calculations. ICM-102 exhibited a graphite-like layer structure, with the c-axis and the a-axis mainly contributing to the distance between the molecular planes. As the pressure increased from 1 atm to 10 GPa, this distance decreased from 3.166 to 2.689 Ǻ. The hydrogen bonds had the most contribution to the non-covalent interactions within the same molecular planes, resulting in the b-axis discontinuity. However, van der Waals interactions gradually appeared between molecular planes as the pressure increased to 2.5 GPa. Based on the analysis of crystal orbitals, the distribution of π bonds and the Laplacian bond order (LBO), it was determined that the generation mechanism of H2O molecules involved the cleavage of N-Oc (coordinated oxygen atoms), followed by intermolecular hydrogen transfer reactions, and ultimately the formation of H2O molecules through competition with H atoms in the amino groups within the same molecules. More importantly, the pressure dependence of LBO values for N-Oc revealed that high pressure could inhibit the ICM-102 decomposition process due to reinforcing hydrogen bonds and van der Waals interactions. This work will deepen our understanding of the stability of ICM-102 under high pressure and provide a helpful reference for its potential detonation applications. METHODS: All simulations, including geometry optimization and vibration analysis under quasi-hydrostatic pressure, were conducted using the CP2K code. The PBE function and the Goldk-Teter-Hutter (GTH) pseudopotential with the double-ζ-with-polarization (DZVP) basis set were employed. Additionally, the semiempirical dispersion correction D3 (BJ) was used to account for the intermolecular dispersion force. The simulations were performed under periodic boundary conditions, with a finest grid level cutoff set to 400 Ry for the Γ point. The Broyden-Flecher-Goldfarb-Shanno (BFGS) optimization method was used, with tighter convergence criteria applied for the subsequent calculations of infrared spectra. Finally, the wave-function analysis, such as non-covalent interaction and LBO, was conducted using the Multiwfn and VMD packages.

SERS aptasensor for simultaneous detection of ochratoxin A and zearalenone utilizing a rigid enhanced substrate (ITO/AuNPs/GO) combined with Au@AgNPs.

The contamination of mycotoxins poses a serious threat to global food security, hence the urgent need for simultaneous detection of multiple mycotoxins. Herein, two SERS nanoprobes were synthesized by embedded SERS tags (4-mercaptopyridine, 4MPy; 4-mercaptobenzonitrile, TBN) into the Au and Ag core-shell structure, and each was coupled with the aptamers specific to ochratoxin A (OTA) and zearalenone (ZEN). Meanwhile, a rigid enhanced substrate Indium tin oxide glass/AuNPs/Graphene oxide (ITO/AuNPs/GO) was combined with aptamer functionalized Au@AgNPs via π-π stacking interactions between the aptamer and GO to construct a surface-enhanced Raman spectroscopy (SERS) aptasensor, thereby inducing a SERS enhancement effect for the effective and swift simultaneous detection of both OTA and ZEN. The presence of OTA and ZEN caused signal probes dissociation, resulting in an inverse correlation between Raman signal intensity (1005 cm-1 and 2227 cm-1) and the concentrations of OTA and ZEN, respectively. The SERS aptasensor exhibited wide linear detection ranges of 0.001-20 ng/mL for OTA and 0.1-100 ng/mL for ZEN, with low detection limits (LOD) of 0.94 pg/mL for OTA and 59 pg/mL for ZEN. Furthermore, the developed SERS aptasensor demonstrated feasible applicability in the detection of OTA and ZEN in maize, showcasing its substantial potential for practical implementation.

Role of big data and technological advancements in monitoring and development of smart cities.

Driven by rapid advancements in technology and data science, a revolutionary transformation is sweeping across environmentally friendly cities worldwide. This surge stems from a pressing need to tackle the intricate complexities of urban sustainability, encompassing everything from infrastructure and governance to fragmented design and technological solutions. To effectively manage these complexities and accurately measure, assess, and optimize their sustainability performance, sustainable communities are increasingly tapping into the potential of smart city technologies, particularly big data and its fictionalized applications. This trend culminates in the emergence of smart cities. This article delves into the current state of research surrounding data-driven, environmentally conscious smart cities, aiming to assess the extent to which these two concepts are currently being integrated and identify potential gaps in this field. Through a strong emphasis on evidence-based research, the study underscores the potential of big data technologies to offer innovative approaches for monitoring, comprehending, evaluating, and ultimately managing sustainable urban development. It further highlights the crucial role of data-driven advancements in formulating strategic development policies and operational management procedures, ensuring that environmentally conscious cities can continue to contribute to sustainability goals even amidst rapid urbanization.

Sustainability in the green engineering of nanocomposites based on marine-derived polysaccharides and collagens: A review.

Nanocomposites are sophisticated materials that incorporate nanostructures into matrix materials, such as polymers, ceramics and metals. Generally, the marine ecosystem exhibits severe variability in terms of light, temperature, pressure, and nutrient status, forcing the marine organisms to develop variable, complex and unique chemical structures to boost their competitiveness and chances of survival. Polymers sourced from marine creatures, such as chitin, chitosan, alginate, sugars, proteins, and collagen play a crucial role in the bioengineering field, contributing significantly to the development of nanostructures like nanoparticles, nanocomposites, nanotubes, quantum dots, etc. These nanostructures offer a wide array of features involving mechanical strength, thermal stability, electrical conductivity, barrier and optical characteristics compared to traditional composites. Notably, marine nanocomposites have distinctive roles in a wide spectrum of applications, among them anti-cancer, anti-microbial, antioxidant, cytotoxic, food packing, tissue engineering and catalytic actions. Sol-gel, hot pressing, chemical vapor deposition, catalytic decomposition, dispersion, melt intercalation, in situ intercalative polymerization, high-energy ball milling and template synthesis are common processes utilized in engineering nanocomposites. According to our literature survey and the Web of Science, chitosan, followed by cellulose, chitin and MAPs emerge as the most significant marine polymers utilized in the construction of nanocomposites. Taken together, the current manuscript underscores the biogenesis of nanocomposites, employing marine polymers using eco-friendly processes. Furthermore, significant emphasis in this area is needed to fully explore their capabilities and potential benefits. To the best of our knowledge, this manuscript stands as the first comprehensive review that discusses the role of marine-derived polymers in engineering nanocomposites for various applications.

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.

Dynamic Nondestructive Detection Models of Apple Quality in Critical Harvest Period Based on Near-Infrared Spectroscopy and Intelligent Algorithms.

Apples are usually bagged during the growing process, which can effectively improve the quality. Establishing an in situ nondestructive testing model for in-tree apples is very important for fruit companies in selecting raw apple materials for valuation. Low-maturity apples and high-maturity apples were acquired separately by a handheld tester for the internal quality assessment of apples developed by our group, and the effects of the two maturity levels on the soluble solids content (SSC) detection of apples were compared. Four feature selection algorithms, like ant colony optimization (ACO), were used to reduce the spectral complexity and improve the apple SSC detection accuracy. The comparison showed that the diffuse reflectance spectra of high-maturity apples better reflected the internal SSC information of the apples. The diffuse reflectance spectra of the high-maturity apples combined with the ACO algorithm achieved the best results for SSC prediction, with a prediction correlation coefficient (Rp) of 0.88, a root mean square error of prediction (RMSEP) of 0.5678 °Brix, and a residual prediction deviation (RPD) value of 2.466. Additionally, the fruit maturity was predicted using PLS-LDA based on color data, achieveing accuracies of 99.03% and 99.35% for low- and high-maturity fruits, respectively. These results suggest that in-tree apple in situ detection has great potential to enable improved robustness and accuracy in modeling apple quality.

Ag-coated tetrapod gold nanostars (Au@AgNSs) for acetamiprid determination in tea using SERS combined with microfluidics.

Acetamiprid is an organic and highly toxic compound. Despite being widely used as a pesticide agent on a large scale, acetamiprid poses numerous health risks to living organisms, particularly humans. Herein, a strategy for the detection of acetamiprid in tea employing surface-enhanced Raman scattering (SERS) technology incorporated with a microfluidic chip was developed. Significantly, a seed-mediated growth approach was utilized to engineer Ag-coated tetrapod gold nanostars (core-shell Au@AgNSs) with four sharp tips. The synthesized Au@AgNSs showed an enhancement factor of 7.2 × 106. Solid works was used to figure out the two-channel microfluidic chip featuring four circular split hybrid structures, and COMSOL (Software for Multiphysics Simulation) was utilized to model the fusion effect between the substrate (Au@AgNSs) and the sample (acetamiprid). For the first time, the core-shell Au@AgNSs and acetamiprid were fused in the microfluidic channel to facilitate the detection of acetamiprid using SERS. The outcomes pointed out that the standard curve correlation coefficient between SERS intensity (876 cm-1) and the concentration of acetamiprid in tea specimens was calculated as 0.991, while the limit of detection (LOD) was 0.048 ng mL-1, which is well below the minimum limit set by the European Union (10 ng mL-1). Thus, the developed technique combining SERS and microfluidics demonstrated high potential for the rapid and efficient detection of acetamiprid in tea.

Recent and emerging trends of metal-organic frameworks (MOFs)-based sensors for detecting food contaminants: A critical and comprehensive review.

Interest in the use of sensors based on metal-organic frameworks (MOFs) to detect food pollutants has been growing recently due to the desirable characteristics of MOFs, including uniform structures, large surface area, ultrahigh porosity and easy-to-functionalize surface. Fundamentally, this review offers an excellent solution using MOFs-based sensors (e.g., fluorescent, electrochemical, electrochemiluminescence, surface-enhanced Raman spectroscopy, and colorimetric sensors) to detect food contaminants such as pesticide residues, mycotoxins, antibiotics, food additives, and other hazardous candidates. More importantly, their application scenarios and advantages in food detection are also introduced in more detail. Therefore, this systematic review analyzes detection limits, linear ranges, the role of functionalities, and immobilized nanoparticles utilized in preparing MOFs-based sensors. Additionally, the main limitations of each sensing type, along with the enhancement mechanisms of MOFs in addressing efficient sensing are discussed. Finally, the limitations and potential trends of MOFs-based materials in food contaminant detection are also highlighted.

Resistance model of an active capsule endoscope in a peristaltic intestine.

In the past studies, the resistance of magnetically controlled capsules running through the small intestine has been modeled assuming that the small intestine was a circular tube with a constant diameter. Peristalsis is an important character of the human gastrointestinal system, and it would result in some changes in the diameter of the intestine, meaning that the existing resistance models would no longer be applicable. In this paper, based on the assumption that intestinal peristalsis is actually a sinusoidal wave, a resistance model of the capsule running in the peristaltic intestine is established, and then it is validated experimentally. The model provides a realistic foundation for the optimization and control of the magnetically controlled endoscopy.

Exploring the Therapeutic Potential of Royal Jelly in Metabolic Disorders and Gastrointestinal Diseases.

Metabolic disorders, encompassing diabetes mellitus, cardiovascular diseases, gastrointestinal disorders, etc., pose a substantial global health threat, with rising morbidity and mortality rates. Addressing these disorders is crucial, as conventional drugs often come with high costs and adverse effects. This review explores the potential of royal jelly (RJ), a natural bee product rich in bioactive components, as an alternative strategy for managing metabolic diseases. RJ exhibits diverse therapeutic properties, including antimicrobial, estrogen-like, anti-inflammatory, hypotensive, anticancer, and antioxidant effects. This review's focus is on investigating how RJ and its components impact conditions like diabetes mellitus, cardiovascular disease, and gastrointestinal illnesses. Evidence suggests that RJ serves as a complementary treatment for various health issues, notably demonstrating cholesterol- and glucose-lowering effects in diabetic rats. Specific RJ-derived metabolites, such as 10-hydroxy-2-decenoic acid (10-HDA), also known as the "Queen bee acid," show promise in reducing insulin resistance and hyperglycemia. Recent research highlights RJ's role in modulating immune responses, enhancing anti-inflammatory cytokines, and suppressing key inflammatory mediators. Despite these promising findings, further research is needed to comprehensively understand the mechanisms underlying RJ's therapeutic effects.

Raman spectroscopy-based microfluidic platforms: A promising tool for detection of foodborne pathogens in food products.

Rapid and sensitive detection of foodborne pathogens in food products is paramount for ensuring food safety and public health. In the ongoing effort to tackle this issue, detection methods are continually researched and upgraded to achieve rapidity, sensitivity, portability, and cost-effectiveness. This review addresses the critical need for improved technique by focusing on Raman spectroscopy-based microfluidic platforms, which have shown potential in revolutionizing the field of foodborne pathogen analysis offering point-of-care diagnosis and multiplex detection. The key problem lies in the persistent threat of compromised food quality and public health due to inadequate pathogen detection. The review elucidates the various trapping strategies employed in a microfluidic platform, including optical trapping, electrical trapping, mechanical trapping, and acoustic trapping for the capture of microbial cells. Subsequently, the review delves into the key aspects of the application of microbial detection in food products, highlighting recent advances and challenges in the field. The integrated technique allows point-of-care application assessment, which is an attractive quality for in-line and real-time detection of foodborne pathogens. However, the application of the technique in food products is limited and requires further research to combat the complexity of the food matrix, reduced costs of production, and ensure real-time use for diverse pathogens. Ultimately, this review aims to propel advancements in microbial detection, thus promoting enhanced food safety through state-of-the-art technologies.

Exploring the Chemical Constituents and Nutritive Potential of Bee Drone (Apilarnil): Emphasis on Antioxidant Properties.

A lesser-known bee product called drone brood homogenate (DBH, apilarnil) has recently attracted scientific interest for its chemical and biological properties. It contains pharmacologically active compounds that may have neuroprotective, antioxidant, fertility-enhancing, and antiviral effects. Unlike other bee products, the chemical composition of bee drone larva is poorly studied. This study analyzed the chemical compostion of apilarnil using several methods. These included liquid chromatography-mass spectrometry (LC-MS/MS) and a combination of gas chromatography/mass spectrometry with solid phase micro-extraction (SPME/GC-MS). Additionally, antioxidant activity of the apilarnil was assessed using 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. A chemical assessment of apilarnil showed that it has 6.3±0.00, 74.67±0.10 %, 3.65±0.32 %, 8.80±1.01 %, 13.16±0.94 %, and 8.79±0.49 % of pH, moisture, total lipids, proteins, flavonoids, and carbohydrates, respectively. LC-MS/MS analysis and molecular networking (GNPS) of apilarnil exhibited 44 compounds, including fatty acids, flavonoids, glycerophospholipids, alcohols, sugars, amino acids, and steroids. GC-MS detected 30 volatile compounds in apilarnil, mainly esters (24 %), ketones (23.84 %), ethers (15.05 %), alcohols (11.41 %), fatty acids (10.06), aldehydes (6.73 %), amines (5.46), and alkene (5.53 %). The antioxidant activity of apilarnil was measured using DPPH with an IC50 of 179.93±2.46 µg/ml.

A film-like SERS aptasensor for sensitive detection of patulin based on GO@Au nanosheets.

Patulin (PAT) commonly contaminates fruits, posing a significant risk to human health. Therefore, a highly effective and sensitive approach in identifying PAT is warranted. Herein, a SERS aptasensor was constructed based on a two-dimensional film-like structure. GO@Au nanosheets modified with SH-cDNA were employed as capture probes, while core-shell Au@Ag nanoparticles modified with 4-MBA and SH-Apt were utilized as signal probes. Through the interaction between capture probes and signal probes, adjustable hotspots were formed, yielding a significant Raman signal. During sensing, the GO@Au-cDNA competitively attached to Au@AgNPs@MBA-Apt, resulting in an inverse relationship between PAT levels and SERS intensity. The acquired results exhibited linear responses to PAT within the range of 1-70 ng/mL, with a calculated limit of detection of 0.46 ng/mL. In addition, the SERS aptasensor exhibited satisfactory recoveries in apple samples, which aligned closely with HPLC. With high sensitivity and specificity, this method holds significant potential for PAT detection.

Magnetic nanoparticle-based immunosensors and aptasensors for mycotoxin detection in foodstuffs: An update.

Mycotoxin contamination of food crops is a global challenge due to their unpredictable occurrence and severe adverse health effects on humans. Therefore, it is of great importance to develop effective tools to prevent the accumulation of mycotoxins through the food chain. The use of magnetic nanoparticle (MNP)-assisted biosensors for detecting mycotoxin in complex foodstuffs has garnered great interest due to the significantly enhanced sensitivity and accuracy. Within such a context, this review includes the fundamentals and recent advances (2020-2023) in the area of mycotoxin monitoring in food matrices using MNP-based aptasensors and immunosensors. In this review, we start by providing a comprehensive introduction to the design of immunosensors (natural antibody or nanobody, random or site-oriented immobilization) and aptasensors (techniques for aptamer selection, characterization, and truncation). Meanwhile, special attention is paid to the multifunctionalities of MNPs (recoverable adsorbent, versatile carrier, and signal indicator) in preparing mycotoxin-specific biosensors. Further, the contribution of MNPs to the multiplexing determination of various mycotoxins is summarized. Finally, challenges and future perspectives for the practical applications of MNP-assisted biosensors are also discussed. The progress and updates of MNP-based biosensors shown in this review are expected to offer readers valuable insights about the design of MNP-based tools for the effective detection of mycotoxins in practical applications.

Significance of the antibody orientation for the lateral flow immunoassays: A mini-review.

Lateral flow immunoassays (LFIAs) are well-established and broadly commercialized tools in the field of point-of-care testing due to their simplicity, rapidity, cost-effectiveness, and low requirements for users and equipment. However, the insensitivity and the possibility of producing inaccurate results associated with conventional LFIAs have impeded their wide-ranging implementation, especially for monitoring ultra-trace level of analytes. Moreover, the heterogeneous distribution of amino acids on the surface of antibody (Ab) results in a lack of precise control over their orientation, which ultimately leads to unsatisfactory detection performance. To address those concerns, herein we provide an overview of the emerging efforts to prepare well-established LFIAs from the perspective of orientation manipulation of immobilized Abs on the nanoprobes or membranes. The preparation of excellent nanoprobes with Abs being oriented immobilized, consisting of the nanoprobe types, Ab types, and their conjugation chemistries, are reviewed. Followed by the introduction of efforts highlight the importance of directionally immobilized Ab on the membrane. The effects of Ab orientation on the analytical performance of LFIA platforms in terms of sensitivity, specificity, rapidity, reliability, cost-effectiveness, and stability are also summarized. Finally, the future development and challenges of Ab-oriented immobilization-assisted LFIAs are also discussed.

Nitrogen deposition raises temperature sensitivity of soil organic matter decomposition in subtropical forest.

Subtropical ecosystems are strongly affected by nitrogen (N) deposition, impacting soil organic matter (SOM) availability and stocks. Here we aimed to reveal the effects of N deposition on i) the structure and functioning of microbial communities and ii) the temperature sensitivity (Q10) of SOM decomposition. Phosphorus (P) limited evergreen forest in Guangdong Province, southeastern China, was selected, and N deposition (factor level: N (100 kg N ha-1 y-1 (NH4NO3)) and control (water), arranged into randomized complete block design (n = 3)) was performed during 2.5 y. After that soils from 0 to 20 cm were collected, analyzed for the set of parameters and incubated at 15, and 25, and 35 °C for 112 days. N deposition increased the microbial biomass N and the content of fungal and Gram-positive bacterial biomarkers; activities of beta-glucosidase (BG) and acid phosphatase (ACP) also increased showing the intensification of SOM decomposition. The Q10 of SOM decomposition under N deposition was 1.66 and increased by 1.4 times than under control. Xylosidase (BX), BG, and ACP activities increased with temperature under N but decreased with the incubation duration, indicating either low production and/or decomposition of enzymes. Activities of polyphenol-(PPO) and peroxidases (POD) were higher under N than in the control soil and were constant during the incubation showing the intensification of recalcitrant SOM decomposition. At the early incubation stage (10 days), the increase of Q10 of CO2 efflux was explained by the activities of BX, BQ, ACP, and POD and the quality of the available dissolved organic matter pool. At the later incubation stages (112 days), the drop of Q10 of CO2 efflux was due to the depletion of the labile organic substances and the shift of microbial community structure to K-strategists. Thus, N deposition decoupled the effects of extracellular enzyme activities from microbial community structure on Q10 of SOM decomposition in the subtropical forest soil.

Fast Nondestructive Detection Technology and Equipment for Food Quality and Safety.

Fast nondestructive detection technology in food quality and safety evaluation is a powerful support tool that fosters informatization and intelligence in the food industry, characterized by its rapid processing, convenient operation, and seamless online inspection [...].

Review of Marine Cyanobacteria and the Aspects Related to Their Roles: Chemical, Biological Properties, Nitrogen Fixation and Climate Change.

Marine cyanobacteria are an ancient group of photosynthetic microbes dating back to 3.5 million years ago. They are prolific producers of bioactive secondary metabolites. Over millions of years, natural selection has optimized their metabolites to possess activities impacting various biological targets. This paper discusses the historical and existential records of cyanobacteria, and their role in understanding the evolution of marine cyanobacteria through the ages. Recent advancements have focused on isolating and screening bioactive compounds and their respective medicinal properties, and we also discuss chemical property space and clinical trials, where compounds with potential pharmacological effects, such as cytotoxicity, anticancer, and antiparasitic properties, are highlighted. The data have shown that about 43% of the compounds investigated have cytotoxic effects, and around 8% have anti-trypanosome activity. We discussed the role of different marine cyanobacteria groups in fixing nitrogen percentages on Earth and their outcomes in fish productivity by entering food webs and enhancing productivity in different agricultural and ecological fields. The role of marine cyanobacteria in the carbon cycle and their outcomes in improving the efficiency of photosynthetic CO2 fixation in the chloroplasts of crop plants, thus enhancing the crop plant's yield, was highlighted. Ultimately, climate changes have a significant impact on marine cyanobacteria where the temperature rises, and CO2 improves the cyanobacterial nitrogen fixation.

Spoilage Monitoring and Early Warning for Apples in Storage Using Gas Sensors and Chemometrics.

In the process of storage and cold chain logistics, apples are prone to physical bumps or microbial infection, which easily leads to spoilage in the micro-environment, resulting in widespread infection and serious post-harvest economic losses. Thus, development of methods for monitoring apple spoilage and providing early warning of spoilage has become the focus for post-harvest loss reduction. Thus, in this study, a spoilage monitoring and early warning system was developed by measuring volatile component production during apple spoilage combined with chemometric analysis. An apple spoilage monitoring prototype was designed to include a gas monitoring array capable of measuring volatile organic compounds, such as CO2, O2 and C2H4, integrated with the temperature and humidity sensor. The sensor information from a simulated apple warehouse was obtained by the prototype, and a multi-factor fusion early warning model of apple spoilage was established based on various modeling methods. Simulated annealing-partial least squares (SA-PLS) was the optimal model with the correlation coefficient of prediction set (Rp) and root mean square error of prediction (RMSEP) of 0.936 and 0.828, respectively. The real-time evaluation of the spoilage was successfully obtained by loading an optimal monitoring and warning model into the microcontroller. An apple remote monitoring and early warning platform was built to visualize the apple warehouse's sensors data and spoilage level. The results demonstrated that the prototype based on characteristic gas sensor array could effectively monitor and warn apple spoilage.

Determination of Dicofol in Tea Using Surface-Enhanced Raman Spectroscopy Coupled Chemometrics.

Dicofol is a highly toxic residual pesticide in tea, which seriously endangers human health. A method for detecting dicofol in tea by combining stoichiometry with surface-enhanced Raman spectroscopy (SERS) technology was proposed in this study. AuNPs were prepared, and silver shells were grown on the surface of AuNPs to obtain core-shell Au@AgNPs. Then, the core-shell Au@AgNPs were attached to the surface of a PDMS membrane by physical deposition to obtain a Au@AgNPs/PDMS substrate. The limit of detection (LOD) of this substrate for 4-ATP is as low as 0.28 × 10-11 mol/L, and the LOD of dicofol in tea is 0.32 ng/kg, showing high sensitivity. By comparing the modeling effects of preprocessing and variable selection algorithms, it is concluded that the modeling effect of Savitzky-Golay combined with competitive adaptive reweighted sampling-partial least squares regression is the best (Rp = 0.9964, RPD = 10.6145). SERS technology combined with stoichiometry is expected to rapidly detect dicofol in tea without labels.