Effect of harvest date and ripening degree on quality and shelf life of Hass avocado in Mexico
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction. Canada is an important avocado importer from Mexico. For most of the harvest season, fruit reach adequate pulp dry matter content, ripen properly and, consequently, quality and shelf life are excellent. However, after January, fruit dry matter content increases and blackened skin occurs. Shipments to Canada containing blackened fruit are rejected because this characteristic is wrongly associated with low pulp firmness and short shelf life. The objective of our research was to determine the effect of harvest time and ripening degree on initial quality and shelf life of Hass avocado. Materials and methods. Fruit were harvested from October 2007 to April 2008, and grouped into five ripening categories according to the degree of blackened skin. Fruit were then refrigerated for 7 d to simulate shipment to Canada. Thereafter, fruit were stored under simulated market conditions until they reached the edible ripening stage. Dry matter content was calculated only at the beginning of the storage period while quantification of weight loss, fruit with blackened skin, pulp firmness, and pulp color was done at the beginning of the storage period, at the end of the refrigeration period, and every three days during market conditions. Results and discussion. Dry matter content, skin color and pulp hue angle significantly increased with harvest date and ripening degree. Weight loss decreased with harvest date but increased with ripening degree, while firmness was affected by harvest date but was not associated with ripening degree. Conclusion. There is no reason to reject or downgrade blackened fruit, since quality and shelf life are not affected.
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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 | 0.002 | 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) | 0.000 | 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 it