Perfluorooctanoic acid (PFOA), the most environmentally ubiquitous representative of per- and polyfluoroalkyl substances (PFAS), has posed global environmental and health risks due to its persistence. To address the challenges of insufficient adsorption, low intrinsic Raman activity and poor specific recognition of PFOA, this study designed a multifunctional surface-enhanced Raman scattering (SERS) platform based on hollow bowl-like fluorinated covalent organic framework with in-situ grown gold nanoparticles (F-BHCOF/AuNPs) at molecular, interfacial and electronic levels. This material was synthesized via an “amorphous-to-crystalline induced transformation” method. First, fluorinated monomers achieve fluorination at the molecular level. Moreover, the controllably synthesized hollow bowl-like structure, at the interfacial level, not only utilizes the “eddy effect” to enhance mass transfer at low concentrations, but also synergistically enhances the electromagnetic field via dual “confinement effects” throughout the structure. Combined with the “polarization induction” mechanism at the electronic level to mediate photoinduced charge transfer, this platform achieves nearly complete adsorption and specific, direct SERS detection of PFOA at environmentally relevant concentrations, with a detection limit of 1.6 ng/L. This platform can be further extended to the rapid screening and exposure risk assessment of PFOA in environmental water samples and daily consumer products including non-stick pan coatings and waterproof outdoor jackets. Furthermore, this work provides a paradigm for the tailored design of functional materials and for overcoming the technical bottleneck of simultaneous adsorption and detection of PFOA and other similar trace-level pollutants with weak response.

The ability to detect pesticide residues at trace levels is crucial for ensuring consumer health and complying with regulatory standards. Herein, we constructed a hydrophobic layer SERS substrate of silver nanoparticles on the glass surface, utilizing Lewis bases to enhance the interaction between the pesticide and the substrate. This facile method enables the ultrasensitive detection of 6-benzylaminopurine (6-BA), with the lowest detection limit decreasing from 0.01 mg/L to 5´10^-5 mg/L. More importantly, the detection limit of 6-BA in bean sprouts reached 5´10^-4 mg/kg, which is 20 times lower than the allowable residue level (0.01 mg/kg) in legumes set by the EU. Furthermore, the SERS signals of several pesticides, including kinetin, carbendazim, and imidacloprid, can also be enhanced by an order of magnitude. We believe that this method expands the applicability of SERS technology for practical pesticide residue detection, offering a simpler and more sensitive means for analyzing various pesticide contaminants.

This study proposed a non-destructive method for rapid freshness evaluation of green bean based on Raman spectroscopy. The Raman spectra of green bean with different storage times were collected, its physicochemical indicators reflecting changes in freshness including mass loss rate, total color difference (∆E), hardness, ascorbic acid content and chlorophyll content were measured, and chemometrics methods were used to associate the spectral data with the physicochemical data. The effectiveness of different spectral pretreatments such as baseline correction (BL), Gaussian filter (GF), normalization (NL) and standard normal variable (SNV) was compared, and partial least squares regression (PLSR) and principal component regression (PCR) were used individually to establish freshness prediction models will all or selected wavenumbers. Moreover, the regression coefficient (RC) method was used to select the characteristic Raman wavenumbers. The simplified PLSR model for each freshness indicator showed a correlation coefficient of calibration set (r_c) of greater than 0.92, a correlation coefficient of prediction set (r_p) of greater than 0.89, and a residual predictive deviation (RPD) of greater than 2.0. The r_c and r_p of the PCR model were greater than 0.79 and 0.73, respectively. Therefore, the results of this study indicate that Raman spectroscopy allows non-destructive and rapid detection of the freshness of green bean.

Plant-derived essential oils have excellent antifungal effects and can be used for the preservation of fresh foods such as fruits and vegetables, but the detailed mechanism has not been fully elucidated. In this study, we investigated the inhibitory effects of trans-cinnamaldehyde on Penicillium italicum, a common pollution fungus in citrus, and explored the antifungal mechanism of trans-cinnamaldehyde by detecting fungal oxidative damage, mitochondrial metabolism, and cell apoptosis. These results showed that trans-cinnamaldehyde made the carboxylic acid cycle deregulated by altering the related enzyme activities (succinate dehydrogenase, malate dehydrogenase) and mid product. Moreover, the level of reactive oxygen species rose sharply while the redox level was out of regulation. The mitochondrial membrane potential collapsed, leading to the leakage of cytochrome c, and then triggering the activation of apoptotic protease, which was further confirmed by the significant increase in caspase-3 activity from (3.6 ± 0.6) U to (8.8 ± 1.1) U (P < 0.05). The cytochrome c in mitochondria was detected by confocal Raman microspectroscopy, the characteristic intensity index (I₇₅₀/I₂₉₄₄) was decreased, indicating that the cytochrome c in mitochondria was reduced and leakage. Besides, the strong negative correlation between Raman intensity and the amount of cytochrome c leakage was established with the correlation coefficient of -0.9817. This study revealed that destroying the integrity of the mitochondrial membrane, activating the mitochondrial-mediated apoptosis pathway was the in-depth antifungal mechanism of trans-cinnamaldehyde; and Raman spectroscopy technology provided new ideas to study this process with high sensitivity determination of cytochrome c.