Short Communication: The effect of seed hardness and malting characteristics on in situ dry matter digestibility of barley grain in beef heifers
Bibliographic record
Abstract
Ding, S., Oba, M., Swift, M. L., Edney, M., O'Donovan, J. T., McAllister, T. A. and Yang, W. Z. 2015. Short Communication: The effect of seed hardness and malting characteristics on in situ dry matter digestibility of barley grain in beef heifers. Can. J. Anim. Sci. 95: 299–303. An in situ study was conducted to evaluate the relationship between ruminal dry matter digestibility (DMD) and seed hardness or malting characteristics of barley grain. Samples were selected for low and high values of seed hardness index (53 vs. 65; N = 18), beta-glucan content in wort (122 vs. 316 ppm; N = 18), diastatic power (146 vs. 203°L; N = 18), and friability (46 vs. 81%; N = 18) in malt, and incubated in the rumen of three beef heifers for 4, 12 and 48 h. In situ DMD did not vary with beta-glucan concentration or friability. However, barley grain with low seed hardness had lower (P = 0.02) in situ DMD than those with high seed hardness after 4 h of incubation. The barley samples with low diastatic power also had (P = 0.02) higher DMD than with high diastatic power after 4 h, a trend (P = 0.07) that continued after 12 h of incubation. Seed hardness and malting characteristics may have the potential to predict DMD of barley grain in the rumen. However, observed differences in in situ DMD were relatively minor, and we did not detect a relationship between malting characteristics and in situ DMD at longer incubation times. This suggests that the identified grain physical and malt parameters may impact the rate, but not the extent of barley grain digestion in the rumen.
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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 | 0.000 | 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) | 0.004 | 0.001 |
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".