58 Evaluation of heat processing on ruminal degradation and intestinal digestion of oat (Avena sativa L.) grain in dairy cattle.
Bibliographic record
Abstract
This study aimed to investigate the effect of heat processing on ruminal degradation characteristics and in vitro intestinal digestion of oat grain from the cultivars CDC Nasser and CDC Seabiscuit. Oat grain was sampled from harvested plots (n=2) grown in 2014 and 2015. Each sample (1kg) was subsampled into 4 portions and each portion was subjected to one treatment: raw, dry heating (DH; air-draft oven 60min; 120°C); moist-heating (MH; autoclave at 1.05 kg/cmin situ trial to determine ruminal degradation kinetics. Intestinal digestibility was detected using a three-step in vitro method. This study was carried out as a randomized complete block design. Dry heating had greater degradation rate (Kd) for dry matter (DM), lower soluble fraction (S) and rumen undegradable (RU) DM, but greater effectively degraded DM (EDDM; P < 0.05). The ED of organic matter (OM) was lower for MH than other treatments (P < 0.001). The S for crude protein (CP) was greater for DH than MIR (P=0.006), but both heat processing treatments were similar to the control. The RUP was greatest for MH, intermediate for the control and MIR and least for DH (70.1, 56.6, 55.82 and 45.7 g/kg DM, respectively; P < 0.001), while EDCP was greatest for DH (65.0 g/kg DM; P < 0.001). Control samples had a lower ratio of effective degradability of N to OM (ED_N/ED_OM) than heat processing (P < 0.001), where DH had the greatest ratio (22.97). Heat processing might improve the N to energy synchronization of oat grain. The higher RUP for MH resulted in greater intestinal digestible protein (P < 0.001); however, the total digestible protein did not differ between treatments (P=0.070). In conclusion, DH improved the ED_N/ED_OM, while MH decreased the effective degradability that increased increasing the intestinal digestion of RUP.
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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) | 0.000 | 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) | 0.001 | 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".