Nanoliposomes Containing Pistachio Green Hull's Phenolic Compounds as Natural Bio‐Preservatives for Mayonnaise
Bibliographic record
Abstract
In this study, encapsulation of pistachio green hull extract (PGHE) into nanoliposomes (NLs) is carried out. Then, different concentrations of free and incorporated phenolic compounds of (500 and 1000 mg kg−1) are added to freshly prepared mayonnaise and samples are evaluated in terms of physicochemical, sensory, and microbial properties during 4 months of storage at 25 °C. The results indicate that the samples containing NLs produced by 2% lecithin and 1000 mg kg−1 of phenolic compounds have the lowest peroxide value (23.23 ± 2.61 meq O2 kg−1 oil) and thiobarbituric acid value (0.92 ± 0.07 mg malondialdehyde kg−1 oil). Free and incorporated phenolic compounds (1000 mg kg−1) exhibit higher antioxidant activity than 200 mg kg−1 of butylated hydroxy toluene (BHT). Free phenolic compounds (EXs) cause significant changes in color parameters (L*, a*, and b*). Regarding sensory evaluation, the samples containing NLs are the most preferred ones. Additionally, NLs having 1000 mg kg−1 of phenolic compounds have the highest inhibitory efficiency on total viable and fungal counts. NLs and EXs have equal effect on Enterobacteriaceae and lactic acid bacteria. Similar to samples containing 1000 mg kg−1 of sodium benzoate, microbial population in samples treated with phenolic compounds is within permissible level after 4 months of storage. Practical applications: The promising results prove that PGHE can be recommended as a natural source of antioxidants and bio‐preservatives instead of synthetic agents to increase the shelf life and safety of mayonnaise. Additionally, NLs enhance stability and solubility of entrapped phenolic compounds of PGHE and decease adverse effects of free ones on sensory properties of mayonnaise. Therefore, incorporation of phenolic compounds of PGHE in the liposomal carrier is a promising method to defeat the limitations of their direct addition to food systems and NLs containing phenolic compounds and plant extracts can also be applied to present novel functional foods. As nanoliposomes are produced by soybean lecithin as an inexpensive, safe and natural source of phospholipids in nanometric particle size, they can be considered for large‐scale use and promotion of biofunctional activities of phenolic compounds in food, pharmaceutical, and cosmetics applications. Firstly, pistachio green hull extract (PGHE) is prepared. Then, different concentrations of phenolic compounds of PGHE are added and blended with the lecithin/water mixture. Lastly, the suspensions are extruded by a mini extruder for producing large unilamellar vesicles. In the next step, liposome‐encapsulated and free phenolic compounds of PGHE are individually added to mayonnaise samples. Based on these findings, incorporation of phenolic compounds of PGHE in liposomal systems can be an appropriate alternative to improve the oxidative and microbial stability of mayonnaise sauce along with minimal effects on sensory attributes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".