Effects of graded levels of potato by-products in barley- and corn-based beef feedlot diets: II. Palatability.
Bibliographic record
Abstract
The objective of this study was to evaluate the effects of barley- or corn-based diets containing 0, 10, or 20% potato by-product (DM basis) on Warner-Bratzler shear force and palatability of beef. One hundred forty-four crossbred beef steers (333+/-.44 kg) were allotted within weight block (3) to a randomized complete block design with a 2 x 3 factorial arrangement of dietary treatments. Main effects were grain (barley or corn) and level of potato by-product (0, 10, or 20% of diet DM). There were a total of 18 pens with eight steers per pen and three pens per treatment. Steers were fed diets containing 83% concentrate (grain plus potato by-product), 10% supplement, and 7% alfalfa (DM basis) for an average of 130 d. Longissimus muscle cuts were used for Warner-Bratzler shear force determination (four steers per pen) and evaluation (two steers per pen) by a 10-member trained laboratory panel, a professional flavor/texture profile panel, and by consumer panels. Diet did not affect (P > .10) Warner-Bratzler shear force or trained laboratory panel tenderness, juiciness, and flavor intensity scores. Flavor/texture profile panel scores indicated feeding a corn-based diet as opposed to barley-based diet produced a more appropriate well-balanced and well-blended beef flavor and texture. However, the magnitudes of the differences were relatively small, and flavor and texture amplitude ratings for both barley- and corn-fed beef were well above average. Beef from steers fed 10 or 20% potato by-product had lower (P < .05) incidences of inappropriate aromatics and aftertastes, which may have a slightly beneficial effect on beef flavor, but flavor amplitude was not affected (P > .05) by level of potato. Moreover, consumer panel overall acceptability scores were not affected by diet. Thus, feedlot diets containing corn or barley with or without potato by-product should result in palatable beef products.
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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) | 0.001 | 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 | 0.001 |
| 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".