Performance and carcass characteristics of steers fed a low acid-detergent lignin hull, high-oil groat oat in growing and finishing diets
Bibliographic record
Abstract
Two trials were conducted to evaluate the performance and carcass traits of steers fed a low acid detergent lignin hull, high oil groat (LLH-HOG) oat in cattle diets. In trial 1, 400 steers (275.4 ± 20.8 kg) were fed one of two diets with barley or LLH-HOG oat at 37.8% of the diet (DM basis). Dry matter intake (DMI) was lower (P = 0.02) (7.49 vs. 7.72 kg d-1) and gain to feed improved (P < 0.01) (0.171 vs. 0.159 kg) for steers fed the oat-based diet. Calculated NEm (1.80 and 1.71 Mcal kg-1) and NEg (1.17 and 1.09 Mcal kg-1) values were greater for the oat-based diet. In trial 2, 240 steers (341.7 ± 18.1 kg) were fed one of three diets consisting of 88.2% barley, corn or oat grain, 5.1% barley silage and 6.7% supplement (DM basis). During finishing, steers on the oat diet had lower (P < 0.01) Average daily gain than barley- or corn-fed cattle (1.40, 1.69 and 1.84 kg d-1, respectively) reflecting lower (P < 0.01) DMI (9.56, 10.84 and 11.56 kg d-1, respectively). Ultrasound fat and longissimus dorsi (l. dorsi) area, carcass weight and dressing percentage were lower (P < 0.01) for steers fed the oat diet. Stearic acid content of the l. dorsi of oat-fed cattle was greater (P < 0.01) than barley- or corn-fed cattle. The ratio of polyunsaturated to saturated fatty acids in the muscle of oat- and corn-fed cattle was greater (P = 0.01) than that of barley-fed cattle. Results indicate that the energy value of the LLH-HOG oat is equivalent or superior to that of barley for growing cattle; however, research is required to identify why feed intake of finishing cattle fed this grain source is reduced. Key words: Low lignin hull, high-oil groat oat, barley, corn, cattle performance, carcass traits
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".