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Record W2809955679 · doi:10.1002/ejlt.201800086

Nanoliposomes Containing Pistachio Green Hull's Phenolic Compounds as Natural Bio‐Preservatives for Mayonnaise

2018· article· en· W2809955679 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Lipid Science and Technology · 2018
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsInstitut National de la Recherche Scientifique
FundersTarbiat Modares University
KeywordsPreservativeFood scienceChemistryThiobarbituric acidAntioxidantPeroxide valueButylated hydroxyanisoleLipid oxidationPhenolsShelf lifeFood preservationPopulationLactic acidOrganic chemistryLipid peroxidationBacteriaBiology

Abstract

fetched live from OpenAlex

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 O 2 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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.287
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it