Effects of housing finishing pigs in two group sizes and at two floor space allocations on production, health, behavior, and physiological variables1
Bibliographic record
Abstract
With the current shift in the industry toward housing pigs in groups of 100 to 1,000 per pen have come questions as to whether pigs can perform as well in large groups as they do in small and whether large groups of pigs can use the space provided more efficiently. This study examined effects of small (18 pigs) vs. large (108 pigs) group sizes provided 0.52 m(2)/ pig (crowded) or 0.78 m(2)/pig (uncrowded) of space on production, health, behavior, and physiological variables. Eight 7-to 8-wk-long blocks, each involving 288 pigs, were completed. The average BW at the beginning of the study was 37.4 +/- 0.26 kg. Overall, ADG was 1.032 kg/d and 1.077 (+/-0.015) kg/d for crowded and uncrowded pigs, respectively (P = 0.018). Differences between the space allowance treatments were most evident during the final week of study. Overall G:F was also reduced (P = 0.002) in the crowded treatment. Pigs in the crowded groups spent less (P = 0.003) time eating over the 8-wk study than did pigs in noncrowded groups, but ADFI did not differ (P = 0.34) between treatments. Overall, ADG of large-group pigs was 1.035 kg/d, whereas small group pigs gained 1.073 kg/d (+/-0.015; P = 0.039). Average daily gain differences between the group sizes were most evident during the first 2 wk of the study. Over the entire study, G:F also differed, with large groups being less efficient (P = 0.005) than small groups. Although large-group pigs had poorer scores for lameness (P = 0.012) and leg scores (P = 0.02) throughout the 8-wk period, morbidity levels did not differ (P = 0.32) between the group sizes. Minimal changes in postural behavior and feeding patterns were noted in large groups. An interaction (P = 0.04) of group size and space allowance for lameness indicated that pigs housed in large groups at restricted space allowances were more susceptible to lameness. Although some behavioral variables, such as lying postures, suggest that pigs in large groups were able to use space more efficiently, overall productivity and health variables indicate that pigs in large and small groups were similarly affected by the crowding imposed in this study. Broken-line analysis of ADG indicated no difference in the response to crowding by pigs in large and small groups. Little support was found for reducing space allowances for pigs in large groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".