Real Fish Research Articles

Neural Network for Underwater Fish Image Segmentation Using an Enhanced Feature Pyramid Convolutional Architecture

Underwater fish image segmentation is a crucial technique in marine fish monitoring. However, typical underwater fish images often suffer from issues such as color distortion, low contrast, and blurriness, primarily due to the complex and dynamic nature of the marine environment. To enhance the accuracy of underwater fish image segmentation, this paper introduces an innovative neural network model that combines the attention mechanism with a feature pyramid module. After the backbone network processes the input image through convolution, the data pass through the enhanced feature pyramid module, where it is iteratively processed by multiple weighted branches. Unlike conventional methods, the multi-scale feature extraction module that we designed not only improves the extraction of high-level semantic features but also optimizes the distribution of low-level shape feature weights through the synergistic interactions of the branches, all while preserving the inherent properties of the image. This novel architecture significantly boosts segmentation accuracy, offering a new solution for fish image segmentation tasks. To further enhance the model’s robustness, the Mix-up and CutMix data augmentation techniques were employed. The model was validated using the Fish4Knowledge dataset, and the experimental results demonstrate that the model achieves a Mean Intersection over Union (MIoU) of 95.1%, with improvements of 1.3%, 1.5%, and 1.7% in the MIoU, Mean Pixel Accuracy (PA), and F1 score, respectively, compared to traditional segmentation methods. Additionally, a real fish image dataset captured in deep-sea environments was constructed to verify the practical applicability of the proposed algorithm.

A Fish-Counting Method Using Fusion of Spatial Sensing and Temporal Information

In modern aquaculture, accurate and efficient fish counting is crucial for the optimization of resource management and the enhancement of production profitability. Acoustic methods, known for their low energy consumption and extensive detection range, are widely utilized for underwater fish counting. However, traditional acoustic echo methods heavily rely on prior knowledge of fish schools and specific distribution models, leading to complexity and limited adaptability in practical applications. This paper introduces a fish-counting approach that integrates spatial sensing with temporal information. Initially, a spatial sensing matrix is constructed using ultrasonic Frequency-Modulated Continuous Wave (FMCW) technology, which facilitates the extraction of multidimensional features from fish echoes and reduces reliance on prior knowledge of fish schools. Subsequently, temporal information is extracted from echo signals using a Long Short-Term Memory (LSTM) network model, preventing missed detections caused by obstructions in single fish echoes during echo sessions. Finally, by fusing spatial and temporal feature information and employing a data-driven approach, we achieve fish counting while avoiding potential issues arising from improper selection of statistical distribution models. Tests on real fish datasets show that our proposed method consistently outperforms conventional statistical echo methods across all metrics, demonstrating its effectiveness in accurate fish counting.

Simultaneous Determination of 12 Disinfection By‐Products in Fish Muscles by Solvent Extraction Coupled With Gas Chromatography Equipped With an Electron Capture Detector

ABSTRACTDisinfection by‐products (DBPs) have received considerable focus due to potential teratogenic, carcinogenic, and mutagenic effects; however, there is an evident gap in the availability of analytical methodologies for the simultaneous determination of DBPs in fish, especially iodinated DBPs. This paper developed an innovative analytical method for the simultaneous determination of 12 DBPs, including four trihalomethanes (THMs), three haloacetonitriles, and five iodinated THMs (I‐THMs), in fish muscle, utilizing solvent extraction followed by gas chromatography with electron capture detection. The method incorporates tert‐butyl methyl ether as an extraction solvent, performing efficient vortex mixing, extraction, and centrifugation under reduced temperature conditions to facilitate the processing of physically disrupted fish tissues. It demonstrates sensitivity with detection limits from 0.21 to 4.02 ng/g, with recoveries from 58.7% to 129.7%. Applied to real fish samples, including bass (n = 7) and carp (n = 7), all contained detectable DBPs, with concentrations between 8.2 and 275.25 ng/g. Significantly, bass from aquaculture facility exhibited the highest contamination, particularly with chlorodiiodomethane at 194.57 ng/g. I‐THMs present in all fish samples. Notably, this is the first paper about the analytical protocol of I‐THMs in biological matrices. This developed method will facilitate further research on human exposure assessment of DBPs through consumption of fish.

Edible Coatings for Fish Preservation: Literature Data on Storage Temperature, Product Requirements, Antioxidant Activity, and Coating Performance-A Review.

Fresh fish is among the most nutritive foodstuffs, but it is also the most perishable one. Therefore, huge efforts have been made to find the most suitable tools to deliver fish of the highest quality to exigent consumers. Scientific studies help the industry to exploit the newest findings to scale up emerging industrial technologies. In this review article, the focus is on the latest scientific findings on edible films used for fish coatings and storage. Since today's packaging processing and economy are governed by sustainability, naturality underpins packaging science. The synthesis of edible coatings, their components, processing advantages, and disadvantages are outlined with respect to the preservation requirements for sensitive fish. The requirements of coating properties are underlined for specific scenarios distinguishing cold and freezing conditions. This review raises the importance of antioxidants and their role in fish storage and preservation. A summary of their impact on physical, chemical, microbiological, and sensory alterations upon application in real fish is given. Studies on their influence on product stability, including pro-oxidant activity and the prevention of the autolysis of fish muscle, are given. Examples of lipid oxidation and its inhibition by the antioxidants embedded in edible coatings are given together with the relationship to the development of off-odors and other unwanted impacts. This review selects the most significant and valuable work performed in the past decade in the field of edible coatings whose development is on the global rise and adheres to food waste and sustainable development goals 2 (zero hunger), 3 (good health and well-being), and 12 (responsible consumption and production).

Novel optical optode for selective detection and removal of ultra-trace level of mercury ions in different environmental real samples

Owing to the high cost and unavailability of different analytical techniques, there is an urgent need to develop new techniques not only for detecting but also removing mercury ions in real samples. Thus, an optical chemical sensor based on the anchoring of phenanthraquinone monophenylthiosemicarbazone in a plasticized cellulose triacetate membrane was fabricated and applied to the recognition and removal of mercury ions from aqueous solutions. The synthesized optode was characterized by FT-IR, SEM, AFM, and thermal analysis. Several parameters, including the pH, temperature, contact time, washing solvent, and washing time, were optimized. Under optimal conditions, a promising optode film platform was utilized for sensing mercury ions, and the concentrations were calculated based on colorimetric analysis (Histogram, RGB) of digital images, visualization, and spectrophotometry. Also, an optical optode was used for complete adsorption of mercury ions from aqueous solutions. In addition, the regeneration of the synthesized optode was evaluated using 0.1 mol L− 1 nitric acid, which effectively removed all adsorbed mercury ions. The obtained data indicated good linearity in the sensing and adsorption of Hg2+ over a concentration range of 0.005–5000 µgL− 1 with a low limit of detection (LOD = 0.066 µgL− 1) and limit of quantification (LOQ, 0.22 µgL− 1). Furthermore, it showed good distinctions in the presence of coexisting ions, high stability (five months), good applicability, and reproducibility (RSD = 1.31%), making it a promising sensor for Hg2+ detection. On the other hand, the kinetic studies revealed that the pseudo-second-order was the best model for describing the adsorption behavior of mercury ions on the optode surface. Also, the thermodynamic parameters indicate spontaneous (ΔG0 < 0) and endothermic (ΔH0 < 0) reactions. Also, the maximum adsorption capacity was found to be 73.2 mg g− 1. Thus, the optodes were successfully applied for the detection and/or removal of Hg2+ in different real samples, including cucumber, fish, soil, and water samples, with excellent recoveries of 98.1–99.5%.

Agile robotic fish based on direct drive of continuum body

Fish-like agile movements, such as fast swimming and rapid turning, are essential for biomimetic underwater robots but challenging to achieve simultaneously. We present a self-contained robotic fish capable of swimming at a speed of 6.3 body length per second and pivot turning at an angular speed of 1450° per second. These fast motions, comparable to real fish, are realized by directly oscillating a flexible body using an electromagnetic motor, eliminating the need for transmission parts and simplifying the structure. This direct-drive (DD) method improves mechanical robustness and generates fish-like deformations and subsequent rapid swimming. The Strouhal and swimming numbers of the robot match typical values observed in nature. Moreover, the observed frequency peaks in swimming are similar to computed values using a model, which guides the design of the robot. These results illustrate the DD method as a promising framework for the creation of highly versatile biomimetic underwater robots.

LUO-V2 and MSPerception: A multi-fin co-drive robotic fish and its multi-sensor-based experimental system

Experimental systems for analyzing robotic fish swimming play a crucial role in optimizing robotic fish, which prompted us to design an experimental system that combines information from multiple sensors to address the shortcomings of current experimental systems with a single measurement. Furthermore, we are interested in a multi-fin co-drive robotic fish. This paper presents the design of a robotic fish, LUO-V2, and an experimental system, MSPerception. The LUO-V2 represents a novel solution for developing multi-fin co-drive robotic fish. It also provides a controller for LUO-V2, which can synchronously control the multi-fin of the robotic fish. Furthermore, the MSPerception system has been designed based on the fusion of multi-sensor information, which can sense the average thrust, swimming speed, and flow field, which provides an effective tool for studying robotic fish swimming. MSPerception was employed to investigate the factors influencing the swimming performance of LUO-V2 and to compare it with the flow field around the caudal fin of a real fish. The experimental results demonstrated that the multi-fin co-drive significantly enhanced the robotic fish’s performance. This research can provide a theoretical foundation for developing multi-fin co-drive robotic fish and experimental systems.

Fabrication of dual-functional smart materials: 2D-WO3/rGO nanocomposite for electrochemical detection and photocatalytic degradation of tetracycline

The extensive utilization of the antibacterial agent tetracycline (TC) in pharmaceuticals and livestock farming has sparked considerable health apprehensions for the welfare of both animals and humans. The presence of TC drug residues in soil, rivers, lakes, and groundwater further exacerbates these concerns. To address these issues, we synthesized WO3/rGO nanocomposites using a simple hydrothermal method and explored their bifunctional catalyst properties for the first time. These nanocomposites were investigated for their potential applications in electrochemical sensing and photocatalytic degradation of TC drug. The electrocatalytic oxidation of TC drug using the WO3/rGO/Glassy Carbon Electrode (GCE) nanocomposites demonstrated good sensitivity, low detection limit, low quantification limit and wide linear range of 1.708 µA µM−1 cm−2, 202 nM, 0.202 µM and 0.1–400 µM, respectively. Moreover, we assessed the WO3/rGO/GCE nanocomposites effectiveness in detecting TC drug in real samples, including milk, lake water, fish, and tap water, and found the recovery results to be satisfactory. Additionally, the nanocomposites displayed noteworthy photocatalytic activity in degrading the TC drug. The as-prepared WO3/rGO nanocomposites exhibited an impressive degradation efficiency of 87.5 % over 120 minutes under UV–visible light irradiation. Radical trapping tests confirmed that the *OH- radicals played a significant role in the degradation process. Our study highlights the outstanding electrochemical and photocatalytic properties of WO3/rGO nanocomposites, positioning them as highly promising materials for future biomedical and environmental applications.

Quantifying the biomimicry gap in biohybrid robot-fish pairs

Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from simulations to reality, using robotics to validate the modeling hypotheses. This challenge arises in bridging what we term the ‘biomimicry gap’, which is caused by imperfect robotic replicas, communication cues and physics constraints not incorporated in the simulations, that may elicit unrealistic behavioral responses in animals. In this work, we used a biomimetic lure of a rummy-nose tetra fish (Hemigrammus rhodostomus) and a neural network (NN) model for generating biomimetic social interactions. Through experiments with a biohybrid pair comprising a fish and the robotic lure, a pair of real fish, and simulations of pairs of fish, we demonstrate that our biohybrid system generates social interactions mirroring those of genuine fish pairs. Our analyses highlight that: 1) the lure and NN maintain minimal deviation in real-world interactions compared to simulations and fish-only experiments, 2) our NN controls the robot efficiently in real-time, and 3) a comprehensive validation is crucial to bridge the biomimicry gap, ensuring realistic biohybrid systems.

A ratiometric fluorescent sensor based on S-doped BCNO quantum dots and Au nanoclusters combined with 3D-printing portable device for the detection of malachite green.

Sulfur-doped BCNO quantum dots (S-BCNO QDs) emitting green fluorescence were prepared by elemental doping method. The ratiometric fluorescence probe with dual emissions was simply established by mixed S-BCNO QDs with gold nanoclusters (GSH-Au NCs). Because the emission spectrum of Au NCs (donor) at 615nm overlapped well with the ultraviolet absorption of malachite green (MG), fluorescence resonance energy transfer (FRET) can be achieved. When the concentration of MG increased, the fluorescence intensity (F495) of S-BCNO QDs decreased slowly, while the fluorescence intensity (F615) of Au NCs decreased sharply.The fluorescence intensity ratio of F615/F495 decreased with the increase of MG. By plotting the F615/F495 values against MG concentration, a sensitive and rapid detection of MG was possible with a wide detection range (0.1-50 µM) and a low detection limit of 10 nM. Due to the accompanying fluorescence color change from pink to blue-green, it can be used for visual detection. A three dimensional-printing device utilizing digital image colorimetry to capture color changes through the built-in camera, enables quantitative detection of MG with a good linearity between the values of red/green ratioand MG concentrations at the range 1-50 µM. This sensing platform had a range of advantages, including high cost-effectiveness, portability, ease of operation, and high sensitivity. Furthermore, the sensing platform was successfully applied tothe detection of MG in real water sample and fish samples, thereby verifying the reliability and effectiveness of this sensing platform in water quality monitoring and food safety.

Adaptive density guided network with CNN and Transformer for underwater fish counting

Accurate assessment of high-density underwater fish resources is vital to the aquaculture industry. It is directly related to the formulation of fishery insurance strategies and the implementation of breeding plans. However, accurately counting fish in high-density environments becomes challenging due to the uneven distribution of fish density and individual fish’s different sizes and postures. To break through this technical bottleneck, we developed an advanced adaptive density-guided high-density fish counting network. In detail, first of all, the network adopts a multi-layer feature fusion structure similar to UNet, which significantly enhances the matching between fish targets of different scales and feature pyramid levels, effectively alleviating the problems caused by scale changes and morphological deformations. Secondly, the network also introduces a density-guided adaptive selection module, which can intelligently judge the applicability of Convolutional Neural Network and Transformer blocks in different density areas, thereby achieving robust information transfer and interaction between blocks. Finally, to verify the effectiveness of this method, we also specially constructed two high-density data sets: a simulated high-density underwater fish image data set (SHUFD) and a real high-density underwater fish image data set (RHUFD). The proposed method has significant improvements over the state-of-the-art method (CUT) on SHUFD and RHUFD datasets, with the mean absolute error, mean square error, background region bias, foreground region bias and density map bias indicators improving by 3.44% and 6.47%, 11.43% and 4.41%, 23.91% and 29.48%, 4.43% and 10.33%, 8.3% and 13.14%, respectively.

Suitability of 2D depth-averaged simulations to support predictions of cyprinids passage through Vertical Slot Fishways

Fishways are a key measure to recover longitudinal connectivity. Among them, Vertical Slot Fishways (VSFs) have undergone extensive studies. However, very few numerical studies have included coupled hydrodynamics and ecological simulations. We investigated the impact of using three-dimensional (3D RANS) and two-dimensional (2D SWE) flow simulations in a Eulerian Lagrangian Agent-based Model (ELAM) for VSFs. Spatial distribution of turbulent kinetic energy ( k ), velocity magnitude ( | u i | ) , and velocity strain rate ( S ij ) were evaluated. While the | u i | was consistent across simulations, k was overestimated by the 2D SWE simulations. The frequency of S ij highest values was different between 3D RANS and 2D SWE. Also, the influence of these variables on the agent’s cognitive response was inconsistent. 2D SWE displayed an influence of around 0%, 35%, and 25% for k , | u i | and S ij , respectively. 3D RANS resulted in percentages of around 80% of k , 10–20% of | u i | and 0–10% of S ij . All cases were validated, demonstrating that both approaches are suitable to reproduce experimental observations. We demonstrated that the 2D SWE might serve as a good input to simulate fish movement in VSF. Nonetheless, hydrodynamic variables’ influence on agents’ decision making might be biased from real fish experience.

Development of a chemiluminescence detection technique for malachite green

AbstractMalachite green (MG), a triphenylmethane dye is often used as a fungicide and preservative in fisheries due to its effectiveness against water molds in fish and fish eggs. However, excessive inhalation can be hazardous to human health. To quantify the MG concentration, we created and evaluated a 96‐well plate‐based chemiluminescence immunoassay (CLIA). This method used provided readings in &lt;30 min, with an optimal incubation time of 15 min and a limit of detection of 0.20 ng·ml−1. The strong correlation (R2 &gt;0.99) between the measured values of real fish samples examined using the method and the high‐performance liquid chromatography results confirmed the accurate quantitative detection of MG. In this study, CLIA was also used in conjunction with point‐of‐care testing (POCT) to greatly improve the efficiency of the experiments. Thus, a quantitative detection method based on MG plate chemiluminescence was established herein, with performance indexes that meet the requirements of on‐site detection. This approach is also applicable to the detection of small molecule compounds such as chloramphenicol and sulfadiazine pyrimethamine, providing a new direction in the field of food safety detection.

Development of novel fish-inspired robot with variable stiffness

In nature, real fish can adjust stiffness to improve their swimming speed and efficiency, which prompted us to apply the variable stiffness mode to a fish-inspired robot. In this paper, we adopt a mechanically adjustable compliance and controllable equilibrium position actuator (MACCEPA) to achieve a wide range of rotational stiffness change of the robotic fish body. Fish-inspired robots with offline/online variable stiffness mechanisms are developed. Then, swimming experiments are carried out to study the effect of the rotational stiffness of robot body on the swimming performance. Experimental data are processed using the undulatory reconfiguration technique. The offline variable stiffness fish-inspired robot achieved a maximum stride length of 0.7 BL/cycle (body length per cycle), which is basically equal to that of real fish. Experimental results revealed that in addition to the rotational stiffness of caudal fin, the rotational stiffness of fish body is also important and should increase with the driving frequency to achieve a better swimming performance. The rotational stiffness of fish body is the key factor for keeping the stride length stable, which offers a new insight for performance improvement of the high-frequency fish-inspired robot. The findings of this study are beneficial to the design of variable-stiffness fish-inspired robots.

Tailbeat perturbations improve swimming efficiency in self-propelled flapping foils

Recent studies have shown that superimposing rhythmic perturbations to oscillating tailbeats could simultaneously enhance both the thrust and efficiency (Lehn et al., Phys. Rev. Fluids, vol. 2, 2017, p. 023101; Chao et al., PNAS Nexus, vol. 3, 2024, p. 073). However, these investigations were conducted with a tethered flapping foil, overlooking the self-propulsion intrinsic to real swimming fish. Here, we investigate how the high-frequency, low-amplitude superimposed rhythmic perturbations impact the self-propelled pitching and heaving swimming of a rigid foil. The swimming-speed-based Reynolds number ranges from 1400 to 2700 in our study, depending on superimposed perturbations and swimming modes. Numerical results reveal that perturbations significantly increase swimming speeds in both pitching and heaving motions, while enhancing efficiency exclusively in the heaving motion. Further derived scaling laws elucidate the relationships of perturbations with speeds, power costs and efficiency, respectively. These findings not only hypothesise the potential advantages of perturbations in biological systems, but also inspire designs and controls in biomimetic propulsion and manoeuvring within aquatic environments.

Motofish and Trashfish: Food values and rifts at the agrarian frontier

At the resource frontier of Prey Lang Forest in Cambodia, a new food regime marks multiple rifts in the social fabric. As the forest gives way to rural road development, migrant incursions, and cash cropping, long-term residents lament the paucity of available food. At the same time, new migrants suggest that there is now more food than ever. Based on how food is defined, we find one food, motofish, that emerged as a significant semiotic sign. It is a fish, regardless of species, that is farm-raised and carried from the market to the village by motorbike. It is opposed to a real fish that grows by itself in a river or stream. Long-term Kuy and Khmer residents of the forest see the fish as a sign of destruction and loss, because there are so few fish in the rivers and streams. New migrants see motofish as part of a new abundance coming to this remote corner of the world where there used to be no food. This abundance is facilitated by Cambodia's growing fish farming industry, fed by wild-harvested 'trashfish' and subsidized soy pellets. Motofish is more than a sign of gastropolitics, as it marks a rift in the semiotic landscape through which individual and collective worlds emerge. We use this worldmaking fish to launch a discussion of both the epistemic and metabolic rifts of agrarian transformation and how these rifts are interpreted by different actors in the same landscape: One that recognizes the metabolic rift and the other that carries with them its epistemic cleansing.

A self-calibrating flexible SERS substrate incorporating PB@Au assemblies for reliable and reproducible detection.

The precise quantitative analysis using surface-enhanced Raman spectroscopy (SERS) in an uncontrollable environment still faces a significant obstacle due to the poor reproducibility of Raman signals. Herein, we propose a facile method to fabricate a self-calibrating substrate based on a flexible polyvinyl alcohol (PVA) film comprising assemblies of Prussian blue (PB) and Au NPs (PB@Au) for reliable detection. PB cores were coated with an Au shell through simple electrostatic interaction, forming core-shell nanostructure PB@Au assemblies within the PVA film. The outer Au layer provided identical trends in enhancement for both the PB core and neighboring targets while PB cores served as an internal standard (IS) to correct signal fluctuations. The prevention of competitive adsorption on the metal surface between targets and ISs was achieved. The proposed PVA/PB@Au film exhibited enhanced stability of Raman signals after IS correction, resulting in improved spot-to-spot and batch-to-batch reproducibility with significantly reduced standard deviation (RSD) values from 11.42% and 25.02% to 4.43% and 9.39%, respectively. Simultaneously, a higher accuracy in the quantitative analysis of 4-mercaptobenzoic acid (4-MBA) and malachite green (MG) was achieved with fitting coefficient (R2) values improving from 0.9675 and 0.9418 to 0.9974 and 0.9832, respectively. Moreover, the PVA/PB@Au film was successfully applied to detect residual MG in real fish samples. This work opens up an avenue to improve the reproducibility of Raman signals for flexible SERS substrates in the detection of residues under various complex conditions.

Hybrid Power Source in Fish Farming With Help of IoT Technology

Fish farming is a difficult, task that involves growing fish without risk. Maintaining the pond's water quality allows for safe fish production. This will go over the creation of a real-time water quality system to monitor fish farms. The water quality monitoring system includes a dissolved oxygen sensor, a pH sensor, and a water temperature sensor. The Arduino Nano microcontroller is linked with the Internet of Things (IoT) platform to provide real-time remote water monitoring. The system is intended to efficiently monitor water quality in freshwater fish farms, specifically water parameters suitable for fish. Instead of testing the system in the real fish farm, it is tested using water that is simulated to the water quality for the fish farm. If the water was above and below the fixed parameter it gives us an alert and water exchange mechanism get started by remove the dirty water from the pond through the solenoid valve and provide the fresh water into the pond. By measuring the dissolved oxygen level if is any deviation occurs water circulation mechanism should be established and circulate the water for increasing the oxygen level by using the padding wheel which all these done automatically. It also done the automatic food feeding at the periodic interval time without the manual involvement sometimes it may cause a manual error such as underfeeding and overfeeding which may affect the fish health to reduce such stuffs we use this automatic food feeding system. Keywords: Fish farming; IoT; Solar energy; Solar PV.

Complex Modal Characteristic Analysis of a Tensegrity Robotic Fish's Body Waves.

A bionic robotic fish based on compliant structure can excite the natural modes of vibration, thereby mimicking the body waves of real fish to generate thrust and realize undulate propulsion. The fish body wave is a result of the fish body's mechanical characteristics interacting with the surrounding fluid. Thoroughly analyzing the complex modal characteristics in such robotic fish contributes to a better understanding of the locomotion behavior, consequently enhancing the swimming performance. Therefore, the complex orthogonal decomposition (COD) method is used in this article. The traveling index is used to quantitatively describe the difference between the real and imaginary modes of the fish body wave. It is defined as the reciprocal of the condition number between the real and imaginary components. After introducing the BCF (body and/or caudal fin) the fish's body wave curves and the COD method, the structural design and parameter configuration of the tensegrity robotic fish are introduced. The complex modal characteristics of the tensegrity robotic fish and real fish are analyzed. The results show that their traveling indexes are close, with two similar complex mode shapes. Subsequently, the relationship between the traveling index and swimming performance is expressed using indicators reflecting linear correlation (correlation coefficient (Rc) and p value). Based on this correlation, a preliminary optimization strategy for the traveling index is proposed, with the potential to improve the swimming performance of the robotic fish.

Au@Ag@MPBA tags assisted surface-enhanced raman spectroscopy for pathogens detection based on bacteria inhibiting salt-induced aggregation

In this work, a highly structured SERS tags assisted bacteria inhibiting salt-induced aggregation platform was proposed for screening foodborne pathogens. Initially, gold and silver core–shell nanoparticles (Au@Ag NPs) were synthesized by forming an Ag shell on an Au core in situ and employed as SERS substrate. The Au@Ag@MPBA tags were prepared by chemically joining Au@Ag NPs and 4-mercaptophenylboronic acid (4-MPBA) via sulfhydryl groups. 4-MPBA functioned as a bacterial recognition element as well as a Raman reporter molecule. Through the reversible recognition relationship between a boronic acid group of 4-MPBA and bacterial peptidoglycan, multiple types of bacteria were collected by Au@Ag@MPBA tags. Plotting the SERS intensity of the tags against the logarithmic concentration of pathogens (56 ∼ 56 × 105 cfu/mL) revealed an ultra-low detection sensitivity of 16 cfu/mL. Bacteria were determined in real fish samples with satisfactory recoveries (94.26 %∼104.37 %) and validation results (p > 0.05). Thus, the comprehensive bacteria-inhibiting salt-induced aggregation SERS-system offered speedy and accurate pathogenic bacteria screening in actual settings.