Association between Fruit Characteristics and Postharvest Stability of Different Pumpkin (Cucurbita) Species
Bibliographic record
Abstract
This study aimed at understanding peel and flesh characteristics of Cucurbita maxima Duchesne subsp maxima, Cucurbita pepo L var. fastigata and Cucurbita moschata Decne pumpkin varieties and how the fruit characteristics relate to its postharvest stability. Mature fruits were stored at ambient conditions (28oC and 78% Relative humidity) for eight months. Cell microscopic structure, intercellular space size, sugars, starch, cellulose, hemicellulose, lignin, degree of esterification of pectin, polygalacturonase activity, and cumulative moisture lost were determined monthly. Sucrose, starch, cellulose and hemicellulose content and degree of esterification of pectin of different varieties decreased with storage. Glucose and fructose content increased to a maximum and then reduced. Polygalacturonase activity and lignin generally increased with storage time. Size of intercellular spaces, and cumulative moisture lost from both flesh and peel increased with storage. Sucrose breakdown was key during 0 to 3 months, while moisture loss was important at 4 months of storage. Polygalacturonase activity became paramount from 7th month of storage. Postharvest stability of pumpkins is determined by an interplay of factors. The deterministic factor changes with time. Pumpkin varieties with more lignified peel had lower rates of sucrose breakdown and moisture loss and tended to be more stable postharvest. Varieties with low level of hemicellulose had their cell walls degrade early, while deterioration of pumpkins with highly esterified pectin and closely packed cells was delayed.
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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".