Effects of cashew (Anacardium occidentale L.) gum and chitosan coating on the physico-functional properties and shelf life of chicken eggs stored at room temperature
Bibliographic record
Abstract
To investigate how cashew gum and chitosan coatings influence shelf life and the physico-functional properties of chicken eggs stored at room temperature (29 °C), compared with uncoated eggs. A total of 960 eggs (52-week-old Shaver Brown) were randomly assigned to four treatments: chitosan, cashew gum, mineral oil (positive control), and uncoated (negative control). Eggs were stored at 29 °C, and internal quality parameters (weight loss, Haugh unit, yolk index, yolk color, air cell depth, albumen pH, yolk pH), functional properties (gelling, foaming, rheology), and microbiological safety (total viable aerobic plate count) were assessed weekly for six weeks. Data were analyzed using a Completely Randomized Design, with means compared by Least Square Means Test (α = 0.05). Coated eggs exhibited better preservation of internal quality compared to uncoated eggs. Mineral oil performed the best while cashew gum and chitosan coatings performed closest to it, maintaining higher Haugh unit, yolk index, and yolk color values. Uncoated eggs showed the highest weight loss and air cell depth while the lowest weight loss was recorded by mineral oil coated eggs. No significant differences (P > 0.05) were observed in functional properties among treatments. Microbiological analysis confirmed all coated eggs remained safe for consumption throughout storage. Sensory evaluation indicated comparable acceptability, except for surface glossiness in cashew gum-coated eggs. Cashew gum (CG) is an effective, low-cost alternative to mineral oil (MO) for preserving egg quality during room-temperature storage, performing comparably to MO and superior to chitosan (CH) and uncoated treatments.
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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".