Pesticides are applied to promote performances in the agricultural field, sustaining crop productivity by counteracting the damages induced by pests and weeds. Under conditions of uncontrolled application, their negative influences exerted on soil, water and biodiversity mean contamination of food and impact on human health. The reactive oxygen species generation induced by pesticides impair the antioxidant protective ability. For humans, pesticides can have cytotoxic, carcinogenic, and mutagenic potential. They can be classified relying on the chemical structure or on the targeted organism. Optical sensors are based on UV-Vis absorption, fluorescence, chemiluminescence, surface plasmon resonance or Raman scattering. Based on their coloring features, nanomaterials are used in optical sensing platforms. They impart high specific surface area, small sizes, facility of surface modification by biorecognition elements (enzyme, antibody, aptamer, molecularly-imprinted polymer) and promote sensitivity and selectivity in biosensing platforms. The present paper highlights the performances of the optical sensing platforms in pesticide assay. Relevant novel applications are discussed critically, following the attempts to improve analytical features of chemical and biochemical sensors. Critical comparison of the techniques is performed in the last section. Advances in nanofabrication like the inclusion of novel nanomaterials and optimizing data interpretation by integration of algorithms can further enhance performances.

Emerging deep eutectic solvents for organic contaminant analysis in food and environmental matrices: A review

Miniature mass spectrometry in drug and food analysis: Bridging laboratory and field applications

Dispersibility-optimized carbon-based nanozymes via precursor morphology regulation: Dual-enzyme mimetic activity for ascorbic acid and nitrite detection.

Computer-aided fabrication of molecularly imprinted COFs for enantioselective extraction of dihydroquercetin from vine tea.

Smart caffeine sensing: an e-MIP-based screen-printed voltammetric cell for beverage quality control.

This article presents a highly sensitive sensor for real permittivity measurement, based on a single transmission line where the differential line method is applied to extract the differential phase. In this transmission line configuration, the material under test (MUT) can be positioned between the signal trace and the ground plane, enhancing the interaction between the MUT and the electromagnetic fields. In this study, the method is validated using known commercial substrates, and its application is demonstrated in detecting sugar adulteration in freeze-dried fruits. The method was validated within a measurement range of 0.6 GHz–5.8 GHz. Additionally, the reference substrate can be adjusted according to the permittivity range required for the specific application. The sensor exhibits superior performance compared to traditional phase-variation methods in transmission lines and is proposed as an alternative to conventional permittivity measurement techniques used in food analysis.

Pt/Au-decorated Fe-N-C nanozyme sensor array for discrimination of tea polyphenol monomers.

Objective: To perform microbiological analysis of food and non-alcoholic beverages sold at the Maranhense Waterway Terminal in order to contribute to a safe and sustainable food environment. Theoretical Framework: Framework: Food safety is governed by a set of standards aimed at preventing microbiological contamination and ensuring the quality of products offered to consumers. The National Health Surveillance Agency establishes specific microbiological parameters for different food categories aligned with international standards. In food retail environments, the application of these parameters assumes strategic relevance, especially considering the diversity of foods and beverages sold and the number of consumers served. Method: The study was conducted at the Maranhense Waterway Terminal with the collection of 20 solid food items and 12 non-alcoholic beverages. In a laboratory setting, the presence of Salmonella sp. and E. coli was investigated; Enumeration of enterobacteria, coagulase-positive staphylococci, Bacillus cereus, and molds and yeasts using traditional microbiological techniques, followed by identification of enterobacteria and filamentous fungi. Results and Discussion: Of the samples analyzed, 100% were in compliance with Brazilian legislation for the parameters Salmonella sp., E. coli, and B. cereus. However, high populations of enterobacteria and molds and yeasts were evidenced in non-alcoholic beverages. In the evaluated foods, 15% and 20% exceeded the limits for coagulase-positive staphylococci and molds and yeasts. High counts of coagulase-negative staphylococci were also identified, in addition to the presence of eight different species of enterobacteria, notably Klebsiella pneumoniae, Serratia sp., and Shimwellia blattae, and the filamentous fungus Aspergillus sp. Research Implications: The results offer scientific information for the development of technical actions aimed at managing the quality of food and non-alcoholic beverages offered, integrated with sustainable practices at the food sales point, such as water potability, integrated pest control, and proper disposal of generated waste. Originality/Value: First research to address the microbiological quality of food and non-alcoholic beverages sold at the Maranhense Waterway Terminal. Highlighting the importance of the study, it is based on the premise that food safety is an important protective factor against foodborne illnesses. Furthermore, the studied theme involves the third Sustainable Development Goal (SDG), proposed by the United Nations, of which Brazil is a signatory.

A dual signal (Raman/electrochemical) and selective assay for determination of histamine (HA)was developed by leveraging the surface-enhanced Raman and electrochemical enhancement effects of gold nanomaterials and the high specificity of aptamers. Gold nanorods probes co-modified with the Raman reporter molecule 4-MBA and HA aptamers were prepared. Simultaneously, gold nanoparticles were electrodeposited onto ITO, and complementary DNA strands were immobilized to form an electrochemical signal substrate. The two parts assembled based on complementary base pairing. With the addition of HA, aptamers preferentially combined to HA and the assembly disrupted, leading to synchronous decreases in Raman and electrochemical signals. The results demonstrated a linear relationship between the logarithmic values of HA concentration (0.1-1000mg/L) and the dual signals, with a detection limit as low as 0.015mg/L. Furthermore, its application in fish yielded satisfactory spiked recoveries (92.6%-94.5%), confirming its reliability in real food analysis. The method not only enhances detection reliability and anti-interference capabilities but also enables precise identification of trace HA. Potential applications of the method extend beyond HA detection, offering a versatile platform for food safety monitoring and public health protection.

Automated sample preparation systems for food analysis: A mini-review.

Metabolomics plays a vital role in analyzing small molecule dynamics, disease diagnosis, and biomarker identification within biological systems. However, challenges persist including low detection sensitivity for low-abundance metabolites, imprecise identification, and inadequate data standardization. The High-Performance Chemical Isotope Labeling (HP-CIL) technique employs a dual 12C/13C labeling strategy with targeted derivatization reagents to chemically modify functional groups such as amino groups, phenolic groups, and carboxyl groups. This approach not only optimizes chromatographic separation efficiency but also enhances electrospray ionization signals, achieving 10 to 1000-fold improvements in the detection sensitivity of polar metabolites. The technology effectively addresses the issues of ion suppression and quantitative instability inherent in traditional methods. HP-CIL technology, leveraging isotope internal standard correction (with a quantitative error ≤ 5%) and three-tier database integration, enables precise qualitative and quantitative analysis of trace samples in complex matrices. In the medical field, through analysis of urine, blood, and saliva samples, this technology demonstrates multidimensional application potential in oncology, neurodegenerative diseases, cardiovascular disorders, immunology, and drug development. In sports science, it can decipher the dynamic changes in the tricarboxylic acid cycle during endurance exercise. For fermented food analysis, it aids in optimizing low-salt fermentation processes. In gut microbiota research, it detects short-chain fatty acids overlooked by traditional methods, revealing the correlation between dietary fiber intervention and host health. Moving forward, through deep integration with multi-omics technologies like genomics and transcriptomics, HP-CIL will drive precision medicine toward dynamic health management and personalized treatment plans, becoming a core technological bridge connecting basic research and clinical practice.

A novel fluorescent probe for sensitive detection copper in food samples and in vivo.

Nanozyme biosensors: Catalytic mechanism, activity regulation, signal amplification and application in food analysis.

A sensitive photoelectrochemical aptasensor based on Bi/Bi2MoO6-modified phosphorus-doped ultrathin g-C3N4 formed Z-scheme heterojunction for tetracycline detection.

Natural-derived sorbents: Application of biochar materials as green extractive approach in food analysis.

Development and applications of carbon paste and Sonogel-Carbon electrodes modified with nanomaterials: Perspectives in pharmaceutical, biological, environmental and food analysis: A review

The growing concern about chemical contaminants in food has increased the need for a rapid, selective, and cost-efficient sensing technology. Molecularly imprinted polymers (MIPs) have emerged as potential artificial sensing elements owing to their high sensitivity, stability, selectivity, and reproducibility. Recent advances further highlight the growing role of computational tools, including molecular docking, molecular dynamics (MD), quantum chemical calculations (QC), and molecular mechanics (MM), in rational MIP design. These methods guide the rational selection of monomers, solvents, and cross-linkers by predicting their effects on template interactions, solvent polarity, and cavity stability, thereby minimizing trial and error in MIP design. This review presents a comprehensive overview of recent progress in MIP-based sensors for the detection of chemical contaminants in food, emphasizing experimental and computational perspectives. In addition, this review covers chromatography-integrated MIP systems, where imprinted polymers are used as selective recognition elements within separation-based methods for food contaminant analysis. The reviewed platforms enable not only sensitive detection but also reliable quantification of food contaminants across diverse matrices. Special focus is given to case studies that demonstrate the applications of MIPs in food analysis and the role of in silico strategies in optimizing sensor performance. By bridging experimental innovation with a computational design, this review aims to provide researchers with an integrated framework for developing next-generation sensing platforms that are selective, sensitive, and practical for real-world food safety monitoring.

Current advances in LC-MS/MS and GC-MS/MS coupled with chemometrics for integrated food analysis and quality control.

Preparation of a novel hollow-shaped carboxyl-functionalized microporous organic network for efficient solid-phase extraction of indoleamines from fruit juice samples.