PSI-26 Effects of particle size and enzyme supplementation on the energy value of field peas fed to growing pigs
Bibliographic record
Abstract
Abstract An experiment was conducted to determine if particle size and enzyme supplementation affects the digestible energy (DE), metabolizable energy (ME), and net energy (NE) contents in field peas fed to growing pigs. Male weaned pigs [n = 30; TN70 × TN Tempo; body weight (BW) = 16.5 ± 0.4 kg] were assigned to 1 of 5 dietary treatments: 4 consisting of 50% peas and a corn-soybean meal basal diet. The experiment was carried out as a completely randomized design with treatments arranged in a 2 × 2 factorial design, based on two particle sizes (500μm, 700μm) and two levels of carbohydrase supplementation (0 g/mt, 1,000 g/mt) to give 6 replicates per treatment. Diets were formulated to meet or exceed NRC (2012) requirements. The study was carried out in 3 consecutive periods, each consisting of 15 d; the first 10 d were for adaptation, followed by 5 d of total fecal and urine collection (marker to marker procedure) to calculate DE and ME of diets. The energy content of peas was determined using the difference method. Data were analyzed using the MIXED procedure of SAS. The model included the particle size, enzyme supplementation, and their interaction as a fixed effect. The period was included as a random effect. Least squares means for each treatment were adjusted using Tukey post-hoc test. Dry matter (DM), acid detergent fiber, neutral detergent fiber, gross energy, starch, ash, crude protein, and ether extract contents were analyzed to allow for the prediction of NE content of peas. There were no interactions between particle size and enzyme supplementation on dietary energy values. Also, no main effects of particle size and enzyme supplementation were observed. The average DE, ME, and predicted NE contents for peas were determined to be 3,848, 3,735, and 2,691 kcal/kg DM, respectively. In conclusion, enzyme supplementation and particle size did not influence the DE, ME, and NE contents of the peas.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".