Bactericidal Efficacy and Mechanisms of Non-Electrolytic Slightly Acidic Hypochlorous Water on Pseudomonas fragi and Pseudomonas fluorescens.

Chilled pork is frequently contaminated with Pseudomonas fragi and Pseudomonas fluorescens. In this study, the bactericidal efficacy and mechanisms of non-electrolytic slightly acidic hypochlorous water (NE-SAHW) against two strains of these two species were evaluated. The results showed that the antibacterial efficacy of NE-SAHW was positively correlated with the concentration level of NE-SAHW and negatively correlated with the initial populations of the strains. The strains of small populations were completely inhibited when provided with each level of NE-SAHW. The killed cells of P. fragi were 0.94, 1.39, 4.02, and 5.60 log10 CFU/mL, respectively, and of P. fluorescens they were 1.21, 1.52, 4.14, and 5.74 log10 CFU/mL, respectively, when the initial populations of the strains were at high levels (about 7 log10 CFU/mL). Both strains were completely killed within 12 s with the available chlorine concentration (ACC) of 50 mg/L of NE-SAHW. Morphological changes in both cells were observed by using a Scanning Electron Microscope (SEM) and it was discovered that the cell membranes were damaged, which led to the leakage of the intracellular substances, including K+, nucleic acid, and protein. In terms of the Fourier Transform Infrared Spectroscopy (FTIR) results, NE-SAHW destroyed the structures of membrane proteins and cell structure proteins, and influenced the composition of polysaccharides. The bacteria were definitely dead after treatment by NE-SAHW compared to the control according to the results of flow cytometry. These results demonstrated the potential bactericidal property of NE-SAHW when applied to the meat and other food sterilization industries.

Polypropylene/Poly(butylene adipate-co-terephthalate) Breathing Film for Inhibiting Pseudomonas and Maintaining Microbial Communities and Postharvest Quality of Allium mongolicum Regel during Storage.

Allium mongolicum Regel (A. mongolicum) is a healthy edible plant but highly perishable with a short shelf life of 1-2 d. Modified atmosphere packaging (MAP) could inhibit the postharvest senescence and decay of the vegetables. Thus, the aim of this study was to apply MAP with different gas permeabilities to the storage of A. mongolicum and evaluate its effects on maintaining microbial communities and the postharvest quality of A. mongolicum. The results showed that polypropylene/poly(butylene adipate-co-terephthalate) (PP/PBAT, abbreviated as PAT) MAP was suitable for the storage of A. mongolicum by establishing an optimal atmosphere of 0.5-0.6% O2 and 6.2-7.1% CO2 in the bag. It could delay the postharvest senescence of A. mongolicum and maintain its quality by slowing down its respiration rate and weight loss, reducing cell membrane permeability and lipid peroxidation, maintaining the cell wall, and reducing infection and the growth of microorganisms. However, A. mongolicum in HPT was more perishable than that in PAT during storage. Pseudomonas was found to be the main spoilage bacteria, and they could also be effectively inhibited by PAT-MAP. The next-generation sequencing results also showed the growth of Escherichia-Shigella, Clostridium sensu stricto 1, Streptococcus, Aureobasidium, Didymella, and Fusarium, responsible for A. mongolicum decay or human disease, was well inhibited by PAT-MAP. The results suggested that PAT-MAP could be used to maintain microbial diversity and the postharvest quality of A. mongolicum under cold storage conditions. It provided a feasible solution for the preservation, food quality, and safety control of A. mongolicum.

Construction of gas permeable channel in poly(l-lactic acid) membrane and its control of the micro atmosphere in okra packaging.

An atmosphere within a package affects the metabolic process of food and the microbial growth of fresh products and has a vital role in preserving food. It depends on the membrane's specific gas permeability and selectivity to generate a desirable atmosphere for storage. In this study, triblock poly(l-lactic acid­d-ɛ-caprolactone) (PLDC) copolymers and three-arm poly(l-lactic acid-g-ɛ-caprolactone) (PLGC) star copolymers were synthesized, in which a microphase-separated morphology of sea-island structure was established in PLGC membrane as a gas "fast permeation channel" for regulating CO2 and O2 permeability and CO2/O2 selectivity. AFM observation revealed different well-defined micro phase-separated structures of PLGC with size ranges of 200- 300 nm. Comparing PLGC membrane with PLLA, CO2 and O2 transmission rates increased by 416.9 % and 132.7 %, while H2O transport rates increased by 245.6 %. Mechanical testing shows that the PLGC membrane exhibits 40.8-fold elongation at break compared to PLLA, showing excellent flexibility. Moreover, okra's equilibrium-modified atmosphere packaging was designed based on a theoretically derived model. Preservation results suggested that the PLGC packaging membrane could generate an ideal high 8.7- 9.2 % CO2 and low 2.3- 2.7 % O2 atmosphere for okra preservation, delaying the discoloring and rotting of okra.

Multivariate-Time-Series-Driven Real-time Anomaly Detection Based on Bayesian Network.

Anomaly detection is an important research direction, which takes the real-time information system from different sensors and conditional information sources into consideration. Based on this, we can detect possible anomalies expected of the devices and components. One of the challenges is anomaly detection in multivariate-sensing time-series in this paper. Based on this situation, we propose RADM, a real-time anomaly detection algorithm based on Hierarchical Temporal Memory (HTM) and Bayesian Network (BN). First of all, we use HTM model to evaluate the real-time anomalies of each univariate-sensing time-series. Secondly, a model of anomalous state detection in multivariate-sensing time-series based on Naive Bayesian is designed to analyze the validity of the above time-series. Lastly, considering the real-time monitoring cases of the system states of terminal nodes in Cloud Platform, the effectiveness of the methodology is demonstrated using a simulated example. Extensive simulation results show that using RADM in multivariate-sensing time-series is able to detect more abnormal, and thus can remarkably improve the performance of real-time anomaly detection.