(469) Replacing Cantaloupe with Orange-fleshed Honeydew Melon: Antioxidant Metabolism
Bibliographic record
Abstract
Consumption of phytochemicals has been associated with reduced risks of human health dysfunctions such as cancers and heart disease. Such information has led to increased sales of fruits and vegetables. For example, in the United States, an estimated 23% increase in melon consumption (up to 13.2 lbs/capita/annum) has been recorded over 16 years. However, some health issues have been attributed to cantaloupe due to bacteria such as Salmonella attaching to inaccessible sites, such as the rind netting. Honeydew melons do not have a netted rind. The purpose of this study was to compare concentrations of antioxidants between cantaloupe and both green- and orange-fleshed honeydew melons during 14 days of storage to determine if orange-fleshed honeydew melon would represent a feasible alterative to cantaloupe to the increasingly health/food safety-conscious consumer. Cantaloupe (`Cruiser'; C), green-fleshed Honeydew (`HoneyBrew'; HB), and orange-fleshed Honeydew (`OrangeDew'; OD) melons were harvested in Texas at the beginning and at the end of the production season. β-carotene content was highest in OD, followed by C; no β-carotene was detected in HB. β-carotene levels did not change during storage. Phenolic levels increased in all three melon species during storage, whereas total ascorbate content declined in OD and in early harvest HB. Ascorbate peroxidase activities were lowest in OD, perhaps due to the lower ascorbate levels; little difference between the melon species in activities of the other ascorbate-associated enzymes were observed. Based on the phytochemicals measured in this study, choosing non-netted OD over netted C in order to reduce potential exposure to pathogens would not represent a less healthy food choice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".