Postharvest of ‘Tommy Atkins’ Mango Submitted to Coating of Chlorella sp.
Bibliographic record
Abstract
The use of natural products as coatings to preserve the fruit quality during storage is an important step to maintain food safety for consumer health. The use of microalgae in coatings, therefore, may be promising in the preservation of mango. The present work had the objective to evaluate the effect of coatings based on Chlorella sp. on the postharvest preservation of ‘Tommy Atkins’ mango during storage at room temperature (23 °C). We carried out a completely randomized design experiment consisting of 0%, 1%, 2%, 3% and 4% of Chlorella sp., using 10 fruits per treatment (n = 10). Analyzing the L*, a* and, b* indices, in the peel and the pulp of the mango fruit, we observed a delay in the ripening with the increase of the biofilm concentration. The firmness of the pulp and maintenance of the organic acids of the fruits were higher in the treatments with a large amount of Chlorella sp. The use of biofilm with Chlorella sp. at 2% preserved the quality of ‘Tommy Atkins’ mango until ten days of storage, at 23 °C and 42% RH.
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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 | 0.001 |
| 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".