POSTHARVEST DIPS TO CONTROL BLACK SPECK AND SCAR DISCOLORATION IN STORED BROCCOLI
Bibliographic record
Abstract
ABSTRACT The overall objective of this study was to evaluate the effects of postharvest dips on black speck development and scar discoloration in broccoli. Postharvest chlorine dips of 100, 200 or 300ppm for 5 or 10 min consistently reduced black speck development and scar discoloration in broccoli stored 4 weeks in air at 1C. Concentrations of 200 and 300ppm chlorine were also effective at reducing black speck and scar discoloration, respectively, in broccoli stored 4 weeks in controlled atmosphere (CA, 1% O2 and 12% CO2) at 1C. Citric (1%) and ascorbic (1%) acids, on the other hand, increased both black speck and scar discoloration, while L‐cysteine (0.01%) and combinations of citric (1 or 2%) and ascorbic (1 %) acids had no effect.
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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".