Quantifying hydrocooling water infiltration in ‘Palmer’ mangoes following hot-air quarantine treatment
Bibliographic record
Abstract
Around the world hot-air heating is used as a quarantine treatment to control fruit fly larvae in mangoes. To simulate hydrocooling water absorption in mangoes subjected to hot-air heating quarantine treatment, the internalization of acid blue 9 dye was tested. Hot-air heating fruits (45 °C) had higher acid blue 9 dye infiltration (2.26 %) compared to untreated control fruits (0.72 %). Higher dye infiltration was observed in heated fruits (2.97 %) after 15 min of cold-water immersion than the 60 min required for 1.84 % infiltration in unheated fruits. Regardless of treatment, dye infiltration occurred uniformly through the lenticels on the pericarp and occasionally through the stem into the mesocarp. Thus, hot-air heating treatment followed by immersion in cold water results in fast water infiltration, potentially allowing the internalization of food-borne pathogens if the cooling water is not properly treated. • Hydrocooling can lead to the internalization of food-borne pathogens. • Heating the mangoes for 15 min was sufficient for maximum blue acid dye 9 absorption. • Dye absorption occurred uniformly through the lenticels on the skin. • Dye absorption occurred occasionally through the stem into the mesocarp. • Hydrocooling water needs to be treated with disinfectants to prevent pathogen internalization.
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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".