Synergistic Effect of Gamma-Irradiation and Microencapsualted Anticrobials agaist Listeria Monocytogenes on Ready-to-Eat (RTE) Meat
Bibliographic record
Abstract
This study focused on the antimicrobial efficiency of micro encapsulated nisin/essential oil (EO) nanocomposite bead systems against Listeria monocytogenesin ready-to-eat (RTE) meat for in situfood applications. For the evaluation of nisin/EO microbeads, a preliminary study in vitrowas undertaken to develop nisin/EO-microencapsulated edible beads in order to inhibit the growth of L. monocytogenes in RTE ham. Different concentrations of nisin (16, 31 and 63 μg/mL) were encapsulated into alginate-cellulose nanocrystals (CNC) beads. Microencapsulation kept the available nisin (63 μg/mL) content 20 times more than free nisin during 28 days of storage at 4 °C, by exhibiting 31 μg/mL of availability.Cooked ham slices were coated by nisin beads, inoculated with L. monocytogenes (3 log CFU/g) and stored at 4 °C under vacuum packaging for 28 days. The beads containing 16, 31 and 63 μg/mL of nisin significantly (P≤ 0.05) reduced the bacterial counts by 2.6, 1.5 and 3.0 log CFU/g after storage compared to free nisin, without changing the physicochemical properties (pH and color) of RTE ham. A second microencapsulation study was to compare oregano essential EO (Origanum compactum; 0.025% w/v), cinnamon EO (Cinnamomum cassia; 0.025%) and nisin (0.25% or 16 μg/mL), used alone or in combination with γ-irradiation, to evaluate their in situinhibiting capacity against the growth of L. monocytogenes in RTE ham. Microencapsulation of these formulations allowed verifying the potential of the polymer to protect their antimicrobial efficiency during storage time. Combined treatments of antimicrobial formulations with γ-irradiation were also carried out to determine synergistic antimicrobial effects. Microencapsulatedcinnamon EO/nisin combined with γ-irradiation (1.5 kGy) showed 0.03 log CFU/g/day growth rate of bacteria compared to 0.17 log CFU/g/day for non-encapsulated counterpart. Microencapsulation also showed a significant improvement of bacterial radiosentivity(P≤ 0.05). Microencapsulated oregano EO/nisin and cinnamon EO/nisin combinations showed the highest bacterial radiosensitization with relative sensitivities of 3.4 and 6.9 respectively. Finally, microencapsulation can protect the bioactivity of the antimicrobial compounds during irradiation and the both process act in synergy to eliminate pathogens in food.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".