(30) Edaphic Factors on Crack Development of Cut and Peel Carrots
Bibliographic record
Abstract
The quick-frozen (QF) cut and peel processing industry is growing and has significant economical importance. Crack development formation (CDF) and enhancement is a major obstacle in QF carrot processing since it lowers product quality, profitability and consumer preference. Studies were initiated to determine the role of edaphic factors on crack development. Carrot samples (var. Sugarsnax) were collected from nine different fields before processing, after processing, and after 8 weeks of -8 °C freezer storage. Samples were tested for the percent cracked; the length, width, and depth of cracks; and membrane stability using electrical conductivity per gram (EC/g). Membrane injury index (MII) was also analyzed on freezer-stored samples. Very few cracks and low EC readings were observed in treatments prior to processing, with the exception of field VC38. Samples taken at the end of the processing line had a higher percentage of visual cracks and significant differences were found between fields in EC/g and length, but not in width or depth of cracks. Freezer-stored samples had significant differences in all parameters, including EC/g, MII, crack length, width, and depth, indicating that the length of freezer storage time can increase the potential for crack development. Samples from V49 cracked heavily during 8 weeks in freezer storage compared to the samples from other fields. A significant interaction between field and time was also observed in processed samples, indicating that CDF is dependent on both field parameters and freezer storage time. Significant differences were observed among different fields in terms of crack morphology, especially after 8 weeks in freezer storage.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".