Development of a mango pulp and the acceptability and storability of the product
Bibliographic record
Abstract
Mango, the king of tropical fruits had a great potential for value added products due to its greater impact on human health. Mango pulp is a preservation technique that overcomes the postharvest losses during the seasons. The current study was focused to develop a pulp from Karthakolomban mango cultivar and evaluate its physical, biochemical, microbial properties, acceptability and storability. Mango pulp was prepared after steam blanching of fruits for 15 min to preserve the colour at storage time. Developed mango pulp contains 0.58 mg carotene/100 g, 4.83 mg gallic acid/g, 245.9 mg ascorbic acid/100 g and 374.4 µM Trolox/100 g, as antioxidant. Microbial counts were less than the standard maximum limits for the mango pulp throughout the 3 months storage period. TSS and the titratable acidity were significantly increased (p<0.05) and pH, colour change and moisture were not significantly different during the three-month storage period. However, pH of the pulp was slightly reduced at the time and carotenoid, phenol, ascorbic contents and antioxidant activity were not significantly different and not observed gradual increases or decreases. Sensory evaluation revealed that jam prepared from developed mango pulp at initial stage and two months after storage were significantly different from control for the colour, taste, odor, consistency and overall acceptability. The developed mango pulp is successfully accepted by the people. Karthakolomban mango pulp had superior properties for adding value to the fruit without any preservatives and retained antioxidant properties up to three months.
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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".