Effect of variety and stage of maturity at harvest on nutrient and neutral detergent fiber digestibility of forage barley grown in western Canada
Bibliographic record
Abstract
This study evaluated the effect of variety (V; CDC Cowboy, CDC Copeland, and Xena) and stage of harvest maturity (M; milk, early-, mid-, and hard-dough) on nutrient and neutral detergent fiber digestibility (NDFD) characteristics of barley forage using a randomized complete block design with 3 × 4 factorial treatment arrangement. Barley varieties had similar crude protein, but CDC Cowboy had greater (P < 0.01) acid detergent fiber (ADF), neutral detergent fiber (NDF), and lignin, and lower (P < 0.01) total digestible nutrient (TDN) content relative to Xena. Starch content of CDC Cowboy was lower (P < 0.01) than Xena at all stages of maturity with CDC Copeland intermediate at early- and mid-dough stages. Crude protein, ADF, NDF, and lignin content decreased (P < 0.01) while starch and TDN content increased (P < 0.01) with advancing maturity. Xena had greater (P < 0.01) NDFD, as determined by 6 h in vitro incubation using DaisyII system (NDFD6h), at milk, mid- and hard-dough stages of maturity than CDC Cowboy with CDC Copeland intermediate at mid-dough. However, CDC Cowboy had greater (P < 0.01) NDFD, as determined by 30 h in vitro incubation using DaisyII system (NDFD30h), at early-dough stage than Xena and greater NDFD30h at hard-dough stage than CDC Copeland. Xena had the lowest (P < 0.01) indigestible NDF based on 288 h ruminal in situ incubation (INDF288h), relative to CDC Copeland. These results indicate that to optimize NDFD30h, variety should be considered when deciding the timing of harvest.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".