Evaluation of two biodegradable coatings on corn silage quality
Bibliographic record
Abstract
Abstract This experiment was performed to assess two different biodegradable coating formulations for the preservation of corn silage quality. Soy‐ and casein‐based biodegradable coatings were evaluated for their ability to exclude oxygen and preserve corn silage. Experiments were conducted under natural conditions outdoors. The effect of the coating composition on silage quality was compared with the quality of silage covered with a plastic (0.15 mm) (positive control) and uncovered (negative control) after 4 and 8 week periods. The results showed that the two biodegradable coatings offered the same level of silage protection during the overall experiment (8 weeks). As compared with the negative control, the two formulations prevented deterioration associated with air infiltration (heating, mold growth and dry matter losses) and limited the decrease in nutritive value. Also, the pH of the coated silage was significantly lower (P ≤ 0.05) than the negative control after 4 weeks of storage. Silage coated with the biodegradable coatings was able to maintain the pH below 4.5 during the first 4 weeks of storage. The decline in lactic acid concentration seems to have been initiated by the lactate‐utilizing yeasts, responsible for the increase in the silage pH. No visual growth of mold was observed in silage sealed with biodegradable coatings. This study showed that biodegradable coatings were able to protect the quality of silage during 4 weeks but the biodegradable coatings were not as good as plastic at preserving silage after 8 weeks of storage. Copyright © 2005 Society of Chemical Industry
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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 | 0.001 |
| 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 | 0.000 | 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".