Garlic and Chitosan Improve the Microbial Quality of Hummus and Reduce Lipid Oxidation
Bibliographic record
Abstract
This study investigated the antimicrobial and antioxidant effects of garlic and chitosan on hummus. Hummus was prepared by using 0.5% or 1% (w/w) chitosan, with or without 1% (w/w) garlic, and samples were stored at 4, 10, or 25 °C for 28, 21, or 7 d, respectively. The behavior of lactic acid bacteria (LAB), Pseudomonas spp., aerobic bacteria, and yeasts and molds was then investigated. Color, pH, TBARS, and rheological properties were also measured. In hummus, both with and without garlic, chitosan added at 0.5% and 1% w/w significantly (p < 0.05) decreased LAB, aerobic bacteria, yeasts, and molds, and Pseudomonas spp., at 4 °C. However, at 10 °C, adding chitosan at 1% w/w significantly reduced only aerobic bacteria (2.2 log cfu/g) and Pseudomonas spp. (1.0 log cfu/g). The pH values (regardless of treatment) decreased upon storage. The addition of garlic or chitosan did not significantly affect the lightness (L*) or yellowness (b*). However, garlic, regardless of chitosan concentration, notably reduced lipid oxidation (0.8–1.4 MDA Eq/kg of sample) and had a greater impact on the sensory properties compared to chitosan. The results of this study will encourage producers to produce hummus that has a better flavor due to garlic with enhanced microbial quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".