The large molecular weight and high viscosity of natural konjac glucomannan (KGM) limit its industrial application. Microbial degradation of low-molecular-weight KGM has health benefits and various biological functions; however, the available KGM strains used in the industry have microbial contamination and low degradation efficiencies. Therefore, exploring novelly adaptable strains is critical for industrial processes. Here, the Bacillus licheniformis Z7-1 strain isolated from decaying konjac showed high efficiency for KGM degradation. The monosaccharide composition of the degradation products had a reduced molar ratio of mannose to glucose, indicating that Z7-1 preferentially degraded glucose in KGM. The degraded component was further characterized by ESI-MS, Fourier-transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM), and it also exhibited good antibacterial activity against various food-spoilage bacteria. Genome sequencing and zymolytic analysis revealed that abundant carbohydrate-active enzymes exist in the Z7-1 genome, with at least five types of extracellular enzymes responsible for KGM degradation, manifesting multi-enzyme synergetic action. The extracellular enzymes had significant thermal stability, indicating their potential application in industry. This study provides an alternative method for obtaining low-molecular-weight KGM with antibacterial functions and supports foundational knowledge for its development as a biocatalyst for the direct conversion of biomass polysaccharides into functional components.

Hafnia sp. was one of the specific spoilage bacteria in aquatic products, and the aim of the study was to investigate the inhibition ability of the silver nanoparticles (AgNPs) biosynthesis by an aqueous extract of Prunus persica leaves toward the spoilage-related virulence factors of Hafnia sp. The synthesized P-AgNPs were spherical, with a mean particle size of 36.3 nm and zeta potential of 21.8 ± 1.33 mV. In addition, the inhibition effects of P-AgNPs on the growth of two Hafnia sp. strains and their quorum sensing regulated virulence factors, such as the formation of biofilm, secretion of N-acetyl-homoserine lactone (AHLs), proteases, and exopolysaccharides, as well as their swarming and swimming motilities were evaluated. P-AgNPs had a minimum inhibitory concentration (MIC) of 64 μg ml-1 against the two Hafnia sp. strains. When the concentration of P-AgNPs was below MIC, it could inhibit the formation of biofilms by Hafnia sp at 8-32 μg ml-1, but it promoted the formation of biofilms by Hafnia sp at 0.5-4 μg ml-1. P-AgNPs exhibited diverse inhibiting effects on AHLs and protease production, swimming, and swarming motilities at various concentrations.

As a representative gas of food spoilage, the development of rapid hydrogen sulfide (H2S) analysis strategies for food safety control is in great demand. Despite traditional methods for H2S detection possessing great achievements, they are still incapable of meeting the requirement of portability and quantitative detection at the same time. Herein, a nanozyme catalysis pressure-powered sensing platform that enables visual quantification with the naked eye is proposed. In this methodology, Pt nanozyme inherits the catalase-like activity to facilitate the decomposition of H2O2 to O2, which can significantly improve the pressure in the closed container, further pushing the movement of indicator dye. Furthermore, H2S was found to effectively inhibit the catalytic activity of Pt nanozyme, indicating that the catalase-like activity of PtNPs may be regulated by varying concentrations of H2S. Therefore, by utilizing a self-designed pressure-powered microchannel device, the concentration of H2S was successfully converted into a distinct signal variation in distance. The effectiveness of the as-designed sensor in assessing the spoilage of red wine by H2S determination has been demonstrated. It exhibits a strong correlation between the change in dye distance and H2S concentration within the range of 1-250 μM, with a detection limit of 0.17 μM. This method is advantageous as it enhances the quantitative detection of H2S with the naked eye based on the portable pressure-powered sensing platform, as compared to traditional H2S biosensors. Such a pressure-powered distance variation platform would greatly broaden the application of H2S-based detection in food spoilage management.

This study aimed to evaluate the response efficiency of colorimetric indicator films based on carboxymethyl cellulose (CMC) incorporated with different anthocyanins [Karanda alone (CMC/AK), butterfly pea alone (CMC/AB), and a mixture of anthocyanins from Karanda and butterfly pea (CMC/AK75/AB25)] for tracking shrimp freshness during storage at different temperatures and times (4 °C for 8 days and 25 °C for 30 h). The mathematical models were also applied to predict their freshness and shelf life. The CMC/AK75/AB25 indicator film was the most sensitive and clearly changed color, which could be distinguished by the naked eye. Color changes indicated the shrimp deterioration processes: dark purple (fresh), purplish gray or gray (semi-fresh), and olive green or brown (spoilage). During shrimp storage at temperatures of 4 and 25 °C, the pH reached 7.52 and 8.14, TVB-N 35.98 and 72.72 mg/100 g, and TVC 5.75 and 7.88 log CFU/g, respectively, indicating shrimp had completely deteriorated. Furthermore, there was a positive correlation between the ΔE value of the indicator film and both TVB-N and TVC. These findings suggest that the CMC/AK75/AB25 indicator film could serve as a real-time visual indicator for tracking shrimp freshness and could enhance the guarantee of shrimp safety.

A reversible optoelectronic nose is presented consisting of ten acid-base indicators incorporated into a starch-based film, covering a wide pH range. The starch substrate is odorless, biocompatible, flexible, and exhibits high tensile resistance. This optical artificial olfaction system was used to detect the early stages of food decomposition by exposing it to the volatile compounds produced during the spoialge process of three food products (beef, chicken, and pork). A smartphone was used to capture the color changes caused by intermolecular interactions between each dye and the emitted volatiles over time. Digital images were processed to generate a differential color map, which uses the observed color shifts to create a unique signature for each food product. To effectively discriminate among different samples and exposure times, we employed chemometric tools, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). This approach detects food deterioration in a practical, cost-effective, and user-friendly manner, making it suitable for smart packaging. Additionally, the use of starch-based films in the food industry is preferable due to their biocompatibility and biodegradability characteristics.

Flow cytometry (FCM) provides unique information on bacterial viability and physiology, allowing a real-time early warning antimicrobial and antibiofilm monitoring system for preventing the spread risk of foodborne disease. The present work used a combined culture-based and FCM approach to assess the in vitro efficacy of essential oils (EOs) from condiment plants commonly used in Mediterranean Europe (i.e., thyme EO, oregano EO, basil EO, and lemon EO) against planktonic and sessile cells of food-pathogenic Listeria monocytogenes 56 LY, and contaminant and alterative species Escherichia coli ATCC 25922 and Pseudomonas fluorescens ATCC 13525. Evaluation of the bacterial response to the increasing concentrations of natural compounds posed FCM as a crucial technique for the quantification of the live/dead, and viable but non-culturable (VBNC) cells when antimicrobial agents exert no real bactericidal action. Furthermore, the FCM results displayed higher numbers of viable bacteria expressed as Active Fluorescent Units (AFUs) with a greater level of repeatability compared with outcomes of the plate-count method. Overall, accurate counting of viable microbial cells is a critically important parameter in food microbiology, and flow cytometry provides an innovative approach with high-throughput potential for applications in the food industry as \"flow microbiology\".

Alicyclobacillus spp. is the cause of great concern for the food industry due to their spores\' resistance (thermal and chemical) and the spoilage potential of some species. Despite this, not all Alicyclobacillus strains can spoil fruit juices. Thus, this study aimed to identify Alicyclobacillus spp. strains isolated from fruit-based products produced in Argentina, Brazil, and Italy by DNA sequencing. All Alicyclobacillus isolates were tested for guaiacol production by the peroxidase method. Positive strains for guaiacol production were individually inoculated at concentration of 103 CFU/mL in 10 mL of orange (pH 3.90) and apple (pH 3.50) juices adjusted to 11°Brix, following incubation at 45 °C for at least 5 days to induce the production of the following spoilage compounds: Guaiacol, 2,6-dichlorophenol (2,6-DCP) and 2,6-dibromophenol (2,6-DBP). The techniques of micro-solid phase extraction by headspace (HS-SPME) and gas-chromatography with mass spectrometry (GC-MS) were used to identify and quantify the spoilage compounds. All GC-MS data was analyzed by principal component analysis (PCA). The effects of different thermal shock conditions on the recovery of Alicyclobacillus spores inoculated in orange and apple juice (11°Brix) were also tested. A total of 484 strains were isolated from 48 brands, and the species A. acidocaldarius and A. acidoterrestris were the most found among all samples analyzed. In some samples from Argentina, the species A. vulcanalis and A. mali were also identified. The incidence of these two main species of Alicyclobacillus in this study was mainly in products from pear (n = 108; 22.3 %), peach (n = 99; 20.5 %), apple (n = 86; 17.8 %), and tomato (n = 63; 13 %). The results indicated that from the total isolates from Argentina (n = 414), Brazil (n = 54) and Italy (n = 16) were able to produce guaiacol: 107 (25.8 %), 33 (61.1 %) and 13 (81.2 %) isolates from each country, respectively. The PCA score plot indicated that the Argentina and Brazil isolates correlate with higher production of guaiacol and 2,6-DCP/2,6-DBP, respectively. Heatmaps of cell survival after heat shock demonstrated that strains with different levels of guaiacol production present different resistances according to spoilage ability. None of the Alicyclobacillus isolates survived heat shocks at 120 °C for 3 min. This work provides insights into the incidence, spoilage potential, and thermal shock resistance of Alicyclobacillus strains isolated from fruit-based products.

Hydrogen sulfide (H2S) is a common toxic gas that threatens the quality and safety of environmental water and food. Herein, a new near-infrared fluorescent probe DTCM was synthesized and characterized by single crystal X-ray diffraction for sensing H2S. It exhibited a remarkable \"turn-on\" near-infrared (NIR) emission response at 665 nm with a remarkably massive Stokes shift of 175 nm, super-rapid detection ability (within 30 s), excellent photostability, high selectivity and sensitivity (limit of detection, LOD = 58 nM). Additionally, the probe was successfully utilized for the detection of H2S in environmental water samples. The DTCM-loaded test papers enabled convenient and real-time monitoring of H2S produced by food spoilage.

This is a comparative study to evaluate the effectiveness of six pomegranate peel extracts (PPEs) as antibacterial and antiproliferative agents. The Six PPEs were prepared using four solvent systems and each filtrate was concentrated to a gummy material to be used in the evaluation. The well-diffusion method was used to evaluate their antimicrobial activity against bacteria typically associated with food spoilage: Escherichia coli, Pseudomonas aeruginosa, Salmonella typhimurium, Listeria monocytogenes, Staphylococcus epidermidis, Staphylococcus aureus, and three Bacillus species. The 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTT) was used to evaluate the cytotoxicity against colorectal carcinoma cells (HCT116), prostate adenocarcinoma (PC3), ovarian cancer cells (SKOV-3), and fibroblasts (MRC-5). The antioxidant evaluation was done using the 2,2-diphenyl-1-picrylhydrazyl-hydrate (DPPH) assay. The pH of the water-containing extracts was acidic and almost the same over 6 weeks. The six PPEs inhibited the bacterial growth in a comparable level to standard antibiotics. The effectiveness of each extract was dependent on the bacterial strain, and the Listeria showed a remarkable inhibition when exposed to the aqueous extract prepared at room temperature (RT). The aqueous (RT) and methanol PPEs had a significant antioxidant scavenging capability and a remarkable cytotoxic activity against the PC3 with half maximal inhibitory concentration (IC50) of 0.1 μg/mL. The boiled aqueous extract exhibited antiproliferative activity against HCT116 with an IC50 of 21.45 μg/mL. The effect on SKOV-3 and fibroblasts was insignificant. With the exception of butanol, the antioxidant screening shows an inverse correlation between the polarity of the extraction solvent and the IC50 exhibited by the PPEs. The variation in the effectiveness of PPEs is suggested to be due to variable soluble bioactive compounds that may interact differently with different cells, though water-containing extracts are promising antibacterial agents. The findings clearly show that pomegranate peel possessed the potential to be an eco-friendly novel source for natural compounds that can be implemented in the food industry as a natural antimicrobial and natural food additive to prevent foodborne illnesses.

At least 10 million tons of seafood products are spoiled or damaged during transportation or storage every year worldwide. Monitoring the freshness of seafood in real time has become especially important. In this study, four machine learning algorithms were used for the first time to develop a multi-objective model that can simultaneously predict the shelf-life of five marine fish species at multiple storage temperatures using 14 features such as species, temperature, total viable count, K-value, total volatile basic‑nitrogen, sensory and E-nose-GC-Ms/Ms. as inputs. Among them, the radial basis function model performed the best, and the absolute errors of all test samples were <0.5. With the optimal model as the base layer, a real-time prediction platform was developed to meet the needs of practical applications. This study successfully realized multi-objective real-time prediction with accurate prediction results, providing scientific basis and technical support for food safety and quality.