Food safety assessment of last mile delivery as an alternative food distribution system for ready-to-eat multi-ingredient salad bowls.

Screening and validation of Lacticaseibacillus paracasei F50 as a potential biocontrol agent to inhibit Aspergillus flavus in maize: New insights into biocontrol efficacy and mechanisms.

Plant essential oil nanocarriers: Preparation strategies, antibacterial mechanisms and food preservation applications.

Advanced LC‒MS/MS method for the precise detection of dinocap phenol isomers in 23 plant-derived foods for ensuring food safety and sustainability

Partial ligand-exchange synthesis of Pt/ZIF with superior oxidase-mimicking activity for dual-modal colorimetric/fluorescent detection of adenosine triphosphate in bacteria and pleural effusion.

Brominated flame retardants (BFRs) and perfluoroalkyl substances (PFASs) in Italian coastal mussels: Implications for environmental surveillance and food safety.

In-situ surface-enhanced Raman spectroscopy monitoring of rhodamine 6G degradation in agricultural products by TiO2@COF@Au multifunctional photocatalyst.

PCR-free singlet oxygen-mediated photoelectrochemical detection of the Escherichia coli gadA gene.

The persistent threat of foodborne pathogens, despite safety measures, underscores the urgent need for highly sensitive and rapid sensing technologies to prevent outbreaks and mitigate their devastating health and economic impacts. The evolution of sensing technologies, from enzyme-based biosensors to advanced immuno-based methods, highlights a continuous drive to improve sensitivity, speed, and feasibility in pathogen detection. Immuno-based biosensors have revolutionized pathogen detection by advancements in miniaturization, offering swift, sensitive, and cost-effective alternatives to traditional methods. Mainly, two categories of immuno-based biosensors have become largely demanding for POC; signal transduction-based, such as electrochemical, optical, and quartz crystal microbalance technologies, have significantly advanced pathogen detection by offering real-time, hyper-sensitive, and prompt monitoring capabilities, making them promising tools for field-deployable diagnostics. The second category, platform design-based immuno-based biosensors, such as lateral flow assays, microfluidic paper-based devices, and microchip-based devices, offer cost-effective, facile, and precise pathogen detection for use in food safety and outbreak prediction analysis. Nevertheless, numerous other biosensor types exist, but this review will focus on a few selective ones to enhance clarity and readability. The review shall summarize the state-of-the-art advancements in food pathogen sensing by immuno-based biosensors, their effectiveness, progress, and categories. Racing from qualification to quantification, the discussion will cover the challenges encountered and loopholes in the developed immuno-biosensing methodologies, including material-related issues (e.g., batch variability of nanomaterials, single-use paper substrates) and assay design (e.g., complex microfluidic architectures and multi-step protocols) that affect reproducibility, waste generation, and dependence on trained operators. It will reflect on a comparative study between the most recent emerging works based on good linear range, limit of detections (LODs), types of real samples utilized and short detection time for addressing their impact as POC devices. Unlike previous reviews that typically focus on isolated sensing mechanisms, this article provides a comparative analysis of both signal-transduction-based and platform-design-based immuno-biosensors, coupled with emphasis on recent advances relevant to point-of-care food pathogen detection.

SPIRAL: A probabilistic deep learning framework for Chinese liquor (Baijiu) classification via near-infrared hyperspectral imaging.

Machine learning-assisted multimodal lateral flow immunoassay based on urchin-like Au@Pt nanoparticles for quantitative determination of febuxostat in functional foods.

Deep learning-assisted Ce/Zr-MOF nanozyme hydrogel sensor for colorimetric/photothermal dual-mode detection of glyphosate.

Metal nanoclusters and hydrogel composites for biosensing: A decade of advances and future perspectives.

Emerging strategies for food contaminant detection via DNAzyme-driven DNA walker platforms: Strategies, applications, and future perspectives.

Upcycling shaddock peel waste into a Fe/Fe3C@porous carbon sensor for ultrasensitive electrochemical detection of carbendazim.

Bio-inspired fluorescent agent derived from Mucuna pruriens for PeT-mediated sensitive detection of Cu(II) ions in environmental water.

Organic polymeric probes for formaldehyde detection: Fundamental chemistry, mechanistic insights, and translational sensor technologies.

To ensure food and fruit safety, it is essential to use accurate and appropriate techniques that allow irradiated products to be identified and labelled, thereby preventing their adulteration and that of their derivatives. In this context, in this study, we evaluated the physicochemical properties of γ-irradiated red pitaya peel flour from lab-prepared (PT) and commercial (PC) samples, using X-ray fluorescence (XRF), X-ray diffraction (XRD), Fourier transform infrared (FT-IR), Raman, and electron paramagnetic resonance (EPR) spectroscopic techniques, as well as thermal analysis (TGA/DSC). The moisture content ranged from 8.01% to 16.38%, with the highest values being 16.38% for the PC sample at 3.5kGy and 10.56% for the PT sample at 7.5kGy. FT-IR and Raman spectroscopy revealed differences in betalain concentrations, indicating that irradiation did not significantly alter the spectral profiles. However, chemical changes were detected in the PC sample compared to the PT sample. In the PT sample, at least three distinct paramagnetic centers were identified. A six-line EPR spectrum was assigned to Mn2+ ions (center I). Center II arises from at least two radical species, with the dominant radical exhibiting hyperfine interaction with one α-type and two nearly equivalent β-type protons and characterized by a g-value of 2.0023. The cellulosic component of the pitaya contributes to the formation of center III, which exhibits a g-value of 2.0027. In the PC sample, only center III was detected, with no evidence of Mn2+ signals.

A novel near-infrared-emitting selenolactone-cyanine chemosensor platform for ultra-trace mercury (II) detection in environmental, food and living cell samples.

Protein-polyphenol conjugates and complexes for multifunctional food packaging.