602 The impact of time on feed and partial replacement of high-moisture corn with a high-lipid high-fiber pellet on steer performance, visceral organ weight, fat deposition, and carcass composition
Bibliographic record
Abstract
The objective of this experiment was to determine the impact of time on feed and the partial replacement of starch with a high-fat, high-fiber by-product based pellet. Angus crossbred steers (n = 97; initial BW 469.3 ± 45.8 kg) were randomly assigned to one of two isocaloric dietary treatments: control (CON; n = 48) steers were fed a finishing diet consisting of 10% haylage, 77% high-moisture corn, 11% soybean meal, and 2% of a salt, vitamin, and mineral pre-mix including monensin; or high-fat, high-fiber pellet (HLHF; n = 49). The HFHF contained 29.8% wheat shorts, 26.2% corn DDGS, 18.8% soy hulls, 19.2% corn gain, and 6% tallow and replaced 30% (DM basis) of the high moisture corn in CON. Steers were randomly assigned to pens equipped with Insentec feeders to record individual feed intake. Steers were randomly split into two blocks in order to facilitate sample collection at the abattoir. On d 1 of the feeding period and every 6 wk thereafter, 10 steers from each treatment were selected at random and slaughtered. Organ and visceral fat weights were recorded, and rib sections were cut into muscle, fat, and bone in order to estimate carcass composition. Data were analyzed as a randomized complete block using PROC MIXED in SAS and included the fixed effects of diet, time on feed, and random effects of pen and block. Contrasts between diet and linear effects of time on fed were used for mean separation and significance was declared at P ≤ 0.05. Steer initial BW did not differ (P ≥ 0.43); however, final BW increased linearly (P < 0.001), but did not differ with dietary treatment (P = 0.55). Overall ADG did no differ with dietary treatment (P = 0.63), but decreased linearly with increasing time on feed (P = 0.015). Empty rumen mass was 12.4 and 11.4 ± 0.24 for CON and HLHF (P = 0.004). Abomasum weight tended to be heavier for HLHF than CON steers (P = 0.06). Carcass traits did not differ with dietary treatment (P > 0.51). Rib dissection indicated that rib section weights of lean, bone, intermuscular, body and subcutaneous fat did not differ with dietary treatment (P ≥ 0.24). Overall these data indicate that partially replacing starch with a high-lipid, high-fiber pellet had limited impacts on growth performance and carcass traits and energy partitioning in steers.
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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) | 0.001 | 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".