This study examined the efficacy and mechanisms of action of the antimicrobial peptide BP15 and its lipopeptides, HBP15 and LBP15, against Penicillium digitatum, the primary causative agent of green mold in citrus fruits. The findings revealed that all three antimicrobial peptides markedly inhibited the spore germination and mycelial growth of P. digitatum, with minimum inhibitory concentrations (MICs) of 3.12 μM for BP15, HBP15, and LBP15. The peptides induced morphological alterations in hyphae and elevated intracellular Sytox Green (SG) fluorescence signals, which is indicative of increased cell membrane permeability and disruption. This membrane damage was further supported by the heightened extracellular conductivity and the release of intracellular nucleic acid and protein. A gel retardation assay demonstrated that the peptides showed significant DNA binding and retardation effects. Furthermore, the peptides exhibited significantly lower hemolytic activity (p < 0.05) compared to commercial prochloraz in normal mammalian erythrocytes (sheep erythrocytes) at the tested concentrations. Therefore, BP15 and its lipopeptides, HBP15 and LBP15, show potential as effective agents for preventing green mold in citrus fruits.

Enzymatic browning affects potato quality and commodity value during processing and storage. γ‐Aminobutyric acid (GABA) was proved to enhance the tolerance to biological and abiotic stresses in plants. However, the mechanism by which GABA regulates enzymatic browning in potato remains largely unclear. Therewith, an integrated approach of transcriptomics and physiological analyses was utilized to investigate the mechanism of GABA‐regulated browning. The findings showed that GABA significantly retarded the browning of fresh‐cut potatoes. Transcriptome analysis indicated that the alteration of endogenous GABA content significantly changed the level of 3625 genes, observably enriched in phenylpropanoid biosynthesis, amino acid metabolism, and hormone signaling. Further studies showed that GABA increased the content of total phenols through changing the activities of phenylalanine ammonia‐lyase (PAL), polyphenol oxidase (PPO) and peroxidase (POD), and the expression of genes related to phenol metabolism. Meanwhile, GABA application activated superoxide dismutase (SOD) and catalase (CAT), decreased the content of H ₂ O ₂ and O ₂ ⁻ , and enhanced membrane integrity. Moreover, GABA increased the content of 11 amino acids including aspartic acid, threonine, glutamic acid, phenylalanine, isoleucine, cysteine, glycine, tyrosine, proline, serine, and arginine. Additionally, GABA negatively regulated the synthesis and signaling of ethylene, brassinosteroids, and gibberellin, while positively regulated the synthesis and signaling of auxin and abscisic acid at the level of transcription. Therefore, GABA can inhibit potato browning mainly through promoting the accumulation of total phenols and free amino acids and regulating reactive oxygen metabolism and hormone signaling, which provides a more comprehensive insight into the inhibitory mechanism of GABA on browning in fresh‐cut potatoes.

This study systematically investigated differences in volatile flavor profiles among fermented green plum wines by integrating gas chromatography–mass spectrometry (GC–MS), sensory evaluation, and odor activity value (OAV) analysis with machine learning and SHapley Additive exPlanations (SHAP) based feature interpretation. The primary objective was to evaluate the applicability of machine learning algorithms for flavor profiling of green plum wine. The results indicated that floral and fruity aromas were predominant in samples NG9, YM7, and YM9. Most green plum wines contained high levels of esters, with ethyl benzoate (up to 4820.53 μg/L), ethyl octanoate (up to 2640.83 μg/L), and benzenecarbaldehyde (up to 3432.96 μg/L) being the major contributors. Among the six classification algorithms compared, fuzzy c-means clustering provided the most distinct clustering structure, identifying three distinct flavor categories. Six machine learning models were subsequently established, of which the decision tree (DT) model exhibited the highest performance, with an accuracy of 95.13%. SHAP analysis further revealed that ethyl octanoate, benzyl ethanoate, and 2-phenylethyl ethanoate exerted the greatest influence on model predictions. Overall, these findings highlight the effectiveness of machine learning as a robust tool for the classification and interpretation of flavor characteristics in fermented fruit wines, with broad applicability in flavor science.

Citrus postharvest blue mold caused by Penicillium italicum and green mold caused by P. digitatum are major diseases responsible for fruit decay and economic losses. Increasing fungicide resistance and concerns regarding the safety of chemical fungicides have created an urgent need for alternative control strategies. In this study, selenium microparticles (SeMPs) were biosynthesized by Lysinibacillus sphaericus N30 and characterized by scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS), X-ray diffraction (XRD), Raman spectroscopy, and dynamic light scattering (DLS). The control efficacy of N30-derived SeMPs against citrus postharvest diseases was evaluated using a 6-h post-inoculation treatment and a co-inoculation treatment, and their antifungal effects were further investigated by assessing reactive oxygen species (ROS) accumulation, membrane integrity, extracellular conductivity, and leakage of intracellular macromolecules. The N30-derived SeMPs were predominantly spherical and exhibited a Z-average hydrodynamic diameter of 656.5 nm with a PDI of 0.274. EDS identified Se as the predominant element, while XRD and Raman analyses supported the formation of predominantly amorphous elemental selenium. In vivo assays showed that 640 mg·L⁻¹ SeMPs completely prevented blue mold incidence in the P. italicum co-inoculation treatment, whereas 1280 mg·L⁻¹ completely suppressed blue mold under both application modes. Green mold caused by P. digitatum was completely suppressed at 1280–2560 mg·L⁻¹, with co-inoculation treatment generally showing greater efficacy than post-inoculation treatment. SeMP exposure was associated with increased intracellular ROS accumulation, loss of membrane integrity, increased extracellular conductivity, and leakage of intracellular macromolecules in both pathogens. P. italicum showed greater susceptibility to SeMPs-associated membrane perturbation than P. digitatum, consistent with its higher sensitivity in the fruit assays. These findings indicate that biogenic SeMPs produced by L. sphaericus N30 have potential as selenium-based antifungal materials for the management of citrus postharvest blue and green molds.