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PubMed2026

Selective and sensitive colorimetric sensing of carbosulfan based on BiO2-x/Bi2O2.75 nanosheets with excellent haloperoxidase-like activity.

The development of colorimetric methods based on directly inhibiting nanozyme activity for pesticide detection has attracted considerable attention. In this study, we report a novel colorimetric sensing strategy utilizing BiO2-x/Bi2O2.75 nanosheets (BiO2-x/Bi2O2.75 NSs) with haloperoxidase (HPO)-like activity for the rapid and sensitive detection of carbosulfan (CBS) in foods. Oxygen-vacancy-rich BiO2-x/Bi2O2.75 NSs with HPO-like activity were rationally constructed. Kinetic studies revealed a remarkable Michaelis-Menten constant (Km) of 0.014 mM for I-, indicating a higher affinity for iodide ions than other reported HPO-like nanozymes, as evidenced by its lower Km. Under acidic conditions, CBS tends to be hydrolyzed to produce reductive sulfide species, which directly inhibit the iodoperoxidase-like activity of BiO2-x/Bi2O2.75 NSs, enabling selective detection with a limit of detection (LOD) of 0.18 μg/mL and a linear range of 0.20-100 μg/mL. When the concentration of interfering pesticides and substances was 5 times that of CBS, the sensor remained unaffected, exhibiting excellent stability and specificity. This work contributes to the detection of CBS in complex food matrices, bridging the application gap of HPO-like nanozymes in pesticide detection and providing a promising method for food safety detection.

Colorimetry↗
PubMed2026

Morphology-Encoded Colorimetric Hydrogen Sensing Using Embedded Reactive Pd Absorbers in Fabry-Perot Cavities.

Chemical reactions offer a powerful strategy for generating visible optical responses through localized changes in absorption, dielectric environment, and interfacial wetting. A palladium (Pd)-embedded Fabry-Perot cavity is introduced as a reaction-active optical platform in which structural color is governed by intracavity absorption coupled with reaction-induced dielectric perturbation. Positioning Pd within the dielectric spacer creates a spatially controllable reactive absorber whose vertical location relative to the standing-wave field dictates wavelength-selective absorption within the cavity. The morphology of the embedded Pd layer provides an additional design parameter by modulating both optical loss and interfacial wetting. Under hydrogen exposure in the presence of oxygen, catalytic water formation at the Pd/polymer interface generates localized dielectric heterogeneity and interfacial water droplets, thereby perturbing the optical path length and amplifying the visible response. As a result, the cavity exhibits pronounced, morphology-dependent color transitions that are inaccessible through dielectric-layer engineering or Pd/PdH refractive-index changes alone, enabling direct visual hydrogen sensing under ambient light, as well as flexible optical devices capable of large-area patterning. These findings establish a design framework for reaction-active optical cavities that translate localized chemistry into a colorimetric hydrogen sensing mechanism.

Fabry–Perot resonator↗
PubMed2026

Colorimetric gold nanosensors for monitoring protein aggregation: implications for Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. It remains a major public health challenge due to the lack of early diagnostic tools and effective disease-modifying therapies. Molecularly, AD is characterized by extracellular amyloid-β (Aβ) plaques and intracellular Tau tangles, as well as soluble oligomers that are likely the neurotoxic species. However, the transient and heterogeneous nature of these oligomers makes them difficult to detect using conventional biosensing approaches. Nanomaterial-based colorimetric biosensors have emerged as promising platforms for detecting protein aggregates and discovering aggregation inhibitors. Specifically, the localized surface plasmon resonance properties of metallic nanomaterials can enable rapid, label-free, and visually detectable colorimetric sensing of molecular interactions. These features can be leveraged to monitor protein aggregation processes in real time and achieve high-throughput screening of aggregation inhibitors, which may collectively enable early detection and timely intervention of AD progression. This Review Article presents the design and engineering of gold-nanomaterial-based colorimetric biosensors for monitoring protein aggregation and highlights the current challenges and emerging opportunities for applying these nanosensors to combat AD.

Journal Article↗
PubMed2026

PdIr bimetallic nanozyme engineered metal-organic frameworks integrated dual-mode sensor toward Stx2 detection in food.

Shiga toxin II (Stx2) has attracted extensive attention due to its toxicity and pathogenicity, making the development of sensitive detection methods urgent. This study constructed a dual-mode sensing platform for the sensitive detection of Stx2 in food. Composite material UIO-66@PdIr with peroxidase-like activity and fluorescent properties was synthesized and combined with cDNA as the signal probe, while aptamer-modified magnetic beads served as the capture probe. Specific binding of Stx2 to the aptamer triggered the release of the signal probe, enabling colorimetric and fluorescence signal readout. The colorimetric mode showed a linear range of 0.05-100 ng/mL with an LOD of 0.039 ng/mL, and the fluorescence mode exhibited 0.01-1000 ng/mL with an LOD of 0.0097 ng/mL. Additionally, this method was successfully applied to the detection of Stx2 in food, and the recovery rates were 94.33% ∼ 102.20%. It indicated that the constructed sensor holds great practical potential for Stx2 detection.

Food Contamination↗
PubMed2026

Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584 mM (OXD) and 0.1498 mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10 ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines↗
PubMed2026

ZrO₂@C-based colorimetric/photothermal dual-mode immunosensor coupled with a novel monoclonal antibody for quantification of Aspergillus ochraceus biomass.

Aspergillus ochraceus contaminates agricultural products and produces nephrotoxic, carcinogenic ochratoxin A (OTA), posing severe food safety hazards. A dual-signal lateral flow immunochromatographic assay (dLFIA) based on ZrO₂@C nanoprobes was established for quantitative detection of A. ochraceus biomass. A novel monoclonal antibody (mAb 4B4) was prepared as the capture antibody to immobilize A. ochraceus mycelial lysate antigen on the test line, and a rabbit polyclonal antibody (pAb G2801) as the detection antibody to modify ZrO₂@C composites (synthesized via UiO-66 pyrolysis) into 200 nm colorimetric/photothermal nanoprobes. This dLFIA achieved limits of detection of 0.164 μg/mL (colorimetric) and 0.517 μg/mL (photothermal). This efficient and reliable method allows quantitative analysis of A. ochraceus biomass, which is suitable for routine monitoring of fungal contamination in agro-food matrices.

Antibodies, Monoclonal↗
PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗
PubMed2026

Dual signal-enhanced immunochromatographic test strip based on Au@PtNPs: From sensitive detection of thiamethoxam to multiplex pesticide screening in vegetables.

Immunochromatographic test strip (ICTS) is a rapid analytical technique widely used in environmental and food detection owing to its merits of simple operation and short analysis time. Herein, three-dimensional nanoflower-structured gold‑platinum nanoparticles (Au@PtNPs) were synthesized via a seed-growth method. Compared with conventional gold nanoparticles (AuNPs), Au@PtNPs exhibited stronger signal intensity, excellent catalytic performance, and efficient antibody binding efficiency. Colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS were developed for the sensitive detection of thiamethoxam (THI) in vegetables. The limits of detection (LODs) for colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS quantitative analysis were 0.18 ng/mL and 0.093 ng/mL, respectively, representing approximately 3-fold and 6-fold improvement compared to AuNPs-ICTS (0.56 ng/mL). Furthermore, highly sensitive detection of multiple pesticide residues (chlorpyrifos, acetamiprid, and imidacloprid) was achieved by replacing the corresponding target antigens and antibodies, which further verified the universality of this immunochromatographic strategy.

Thiamethoxam↗
PubMed2026

Social Isolation and Loneliness Among Older Asian Immigrants Through the Lens of Sense of Coherence: Systematic Review of Qualitative Studies.

AIM: To explore the meaning older Asian immigrants attribute to social isolation and loneliness, their management strategies, utilisation of resources and impact on health. DESIGN: Systematic review of qualitative studies. DATA SOURCES: AgeLine, CINAHL, MEDLINE, ProQuest, PsycINFO, Scopus, and Web of Science databases were searched in September 2024. METHODS: Inclusion criteria: participants were Asian immigrants to Western countries aged 65 and over, community-living and experiencing social isolation and loneliness. Antonovsky's Sense of Coherence was used to frame the thematic analysis. RESULTS: Ten papers were included and analysed deductively using elements of the sense of coherence framework: • Comprehensibility: Social isolation and loneliness are viewed as multifaceted, influenced by cultural and environmental dislocation, language barriers, intergenerational conflicts, deteriorating health and mobility, and socioeconomic challenges. • Manageability: included engaging in culture-specific community programs, family and ethnic community support and living within ethnic enclaves mitigated isolation and loneliness. • Meaningfulness: Strong family ties, active community involvement, spirituality, volunteerism, and cultural practices fostered resilience. However, accepting the changing values of their new world, living independently, and carving their own niche provided meaning to their transformed reality. CONCLUSION: Older Asian immigrants experience social isolation and loneliness through a cultural lens, shaped by migration experiences, language barriers, and shifting family dynamics. Cultural roots, family ties, spirituality, community, acceptance, and independence enhance sense of coherence. Recognising the dynamic interplay between cultural identity, resilience, and adaptation is key to understanding their lived experience. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: This review informs culturally sensitive interventions, guiding healthcare, community services, and policy to support social participation, mitigate loneliness through ethno-specific activities, and improve the quality of life for aging immigrant populations in Western countries. REPORTING METHOD: The review was undertaken and reported using the PRISMA guidelines. PATIENT OR PUBLIC INVOLVEMENT: None. PROTOCOL REGISTRATION: PROSPERO (CRD42023425752).

Humans↗
PubMed2026

Inhibitory mechanism of phloretin on the AgrA LytTR domain-agr operon complex formation and its application in beef.

Staphylococcus aureus (S. aureus) represents a major foodborne pathogen whose enterotoxin production poses significant challenges to food safety due to its high environmental resistance and limited efficacy of conventional sterilization. Since the expression of enterotoxins is predominantly governed by the agr quorum sensing system, targeting this regulatory pathway has become a strategic choice for virulence control. This study elucidated the mechanism by which phloretin, a potential quorum sensing inhibitor, interferes with the agr system to attenuate virulence. To achieve this, the recombinant AgrA LytTR domain was expressed and purified, and its interaction with phloretin was characterized using thermal shift assays (TSA), electrophoretic mobility shift assays (EMSA), and molecular dynamics (MD) simulations. The results showed that phloretin specifically binds to the AgrA LytTR domain, enhancing its thermal stability and disrupting AgrA LytTR-agr operon binding by reducing the free energy of interaction between them, without causing significant structural rearrangement. Mechanistic analysis indicated that phloretin sterically hinders key β-sheet turn residues (HIS169, ASN201, ARG233), thereby impairing DNA recognition, downregulating RNAIII transcription, and inhibiting agr signaling. In cooked beef, phloretin significantly inhibited the secretion of enterotoxins and α-hemolysin, while delaying lipid oxidation and protein degradation, and maintaining the meat texture. These findings suggested that phloretin is a multifunctional substance with anti-virulence, antioxidant, and preservative properties, demonstrating its potential as a natural food preservative.

Phloretin↗
PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗
PubMed2026

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants↗
PubMed2026

Acetylcholine signaling regulates osmotic stress adaptation in the phytopathogen Dickeya solani.

Plants impose strong selective pressures that shape both the composition and functional potential of plant microbiomes. The adaptation of plant-associated bacteria to their hosts relies on an extensive repertoire of signal transduction systems that sense plant-derived molecules and dynamically adjust bacterial physiology and metabolism within the holobiont. These signals include key plant signaling compounds that regulate processes essential for plant-microbe interactions. Among them, acetylcholine is emerging as an important signaling molecule in both plants and bacteria. Here, we demonstrate that acetylcholine regulates the expression of the osmotic stress response betIBA gene cluster in the important phytopathogen Dickeya solani, where it plays an important role in osmoprotection. We show that the TetR-family transcriptional regulator associated with this pathway, BetIDs, recognizes acetylcholine as well as choline and trimethylamine. These three ligands differentially induce betIBA transcription in a manner that correlates with their binding affinities. Ligand binding does not affect BetIDs binding to the bet promoter or its oligomeric state. Instead, it induces pronounced changes in the secondary structure of BetIDs, with the magnitude of these conformational changes being ligand-dependent. We further show that quorum sensing modulates osmotic stress tolerance in D. solani by regulating the expression of the Bet pathway. The Bet system is required for the full virulence of D. solani, particularly in chemically complex plant tissues. Phylogenetic analyses reveal that the BetIBA system is widely distributed among plant-associated Pseudomonadota, collectively supporting its importance for bacterial survival and adaptation in plant-related environments.

Osmotic Pressure↗
PubMed2026

An RPA-assisted homogeneous electrochemical DNA sensor for on-site eDNA detection toward early warning of crown-of-thorns starfish outbreaks.

Crown-of-thorns starfish (COTS) outbreaks seriously threaten coral reef ecosystems, while conventional monitoring approaches are time-consuming and often lack sufficient sensitivity for early warning. Existing electrochemical DNA sensors usually require complex electrode-surface immobilization procedures, which can lead to uneven probe distribution, significant steric hindrance, and poor stability. Meanwhile, the low concentration of environmental DNA (eDNA) in marine environments further complicates detection. To overcome these challenges, this study developed a homogeneous electrochemical DNA sensor assisted by recombinase polymerase amplification (RPA) for COTS eDNA detection. Target DNA was first amplified by RPA, and the amplification products were then hybridized in solution with capture probe (CP)-modified magnetic beads (MB) and biotin-labeled signal probe (SP) to form sandwich-structured MB complexes. These complexes were subsequently magnetically enriched and immobilized on the electrode surface for electrochemical signal readout. Under optimized conditions, the sensor displayed a linear response to COTS genomic DNA from 3.77 fg/μL to 1 ng/μL, with an LOD of 2.02 fg/μL and an LOQ of 3.77 fg/μL. The sensor was applied to Xisha Islands samples, and the results agreed with droplet digital PCR (ddPCR) (P > 0.05), demonstrating its potential for sensitive and reliable on-site COTS eDNA detection.

Animals↗
PubMed2026

Boosting domestic wastewater treatment with quorum signal-augmented heterotrophic nitrification-aerobic denitrification bacterial-algal aerobic granular sludge.

The aerobic bacterial-algal granular sludge (ABGS) enhanced with heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria, as a novel symbiotic technology, exhibits fluctuating treatment efficiency and unstable performance primarily due to the unstable symbiotic relationship. This study proposes an innovative approach to strengthening the bacteria-algae symbiosis by introducing exogenous signaling molecules. Concurrently, high-throughput, correlation analysis of environmental factors and metagenomic sequencing techniques are employed to elucidate the enhancement mechanisms of the signaling molecules. The results demonstrate that signaling molecule enhancement boosted total nitrogen (TN) removal efficiency by 24.51 % in the bacteria-algae symbiotic system (X1). Scanning electron microscopy (SEM) characterization revealed that the addition of signaling molecules resulted in more compact aerobic granular sludge (AGS) and markedly improved stability. High-throughput sequencing showed signaling molecules enriched denitrifying bacteria (Hydrogenophaga, Pseudoxanthomonas, Thauera, Zoogloea) and organic-degrading Desulfomicrobium, optimizing microbial diversity and enhancing nitrogen/organic removal. Correlation analysis of environmental factors indicate that the addition of C8-HSL facilitates the enrichment and functional activation of specific genera. Metagenomic analysis revealed that signaling molecules enhanced the system's denitrification performance by modulating gene expression and associated metabolic pathways. Quantitative polymerase chain reaction (qPCR) analysis further confirmed that the signaling molecules upregulated the expression of the napA, nirK, and nirS genes. An increased abundance of the napA gene facilitated aerobic denitrification (NO₃⁻-N→NO₂⁻-N), while upregulated abundance of the nirK and nirS genes accelerated nitrite reduction (NO₂⁻-N→N₂). This study aims to provide theoretical and practical foundations for implementing advanced bacteria-algae symbiotic technologies.

Denitrification↗
PubMed2026

Recent advances in electrode materials for electrochemical detection of zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin commonly found in cereals, animal feed, and processed foods, making it an important concern for food safety and public health. Conventional chromatographic and immunological methods can detect ZEN; however, they often require expensive instruments, lengthy sample preparation, and skilled personnel, which restrict their use for rapid and on-site testing. Electrochemical sensors have attracted enormous interest of the scientific community because of their high sensitivity, rapid response, low cost, miniaturization potential, and compatibility with portable systems. The analytical performance of the electrochemical sensors is strongly influenced by electrode materials, morphology, conductivity, porosity, surface functionality, and the efficiency of bioreceptor immobilization. Despite several reviews on mycotoxin detection, a systematic assessment connecting electrode-material design, modification strategies, sensing mechanisms, and electroanalytical performance specifically for ZEN sensing remain limited. This review critically evaluates recent advances in metal oxides, carbon-based materials, metal-organic- and covalent organic frameworks, MXenes, polymers, and hybrid composites for electrochemical ZEN detection. Particular attention has been given to their roles in electron transfer, analyte enrichment, selectivity, and real-sample analysis. The review also compares the major limitations of current sensing systems, including complex fabrication, matrix interference, insufficient long-term stability, poor inter-electrode reproducibility, and limited scalability. Finally, future directions for developing robust, cost-effective, portable, and commercially viable ZEN sensors are discussed.

Journal Article↗
PubMed2026

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii↗
PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗