PSIV-5 Definition of environmental variables and critical periods to evaluate heat tolerance in maternal-line pigs based on single-step genomic reaction norms
Bibliographic record
Abstract
Abstract Heat stress (HS) is a major welfare and economic issue in the swine industry. However, it is not a trivial task to appropriately quantify the environmental HS. Therefore, this study aimed to 1) define the critical periods and environmental descriptors (based on public weather station information) to evaluate heat tolerance (HT); and 2) estimate genetic parameters for HT in Large White pigs. The traits included in this study were: weaning weight (WW; kg), off-test weight (OTW; kg), total number of piglets born (TNB), number of piglets born alive (NBA), and number of piglets weaned (WN). The number of phenotypic records ranged from 6,059 (WN) to 172,984 (TNB), and genotypes were available for 8,686 animals. Seven climatic variables (maximum, minimum and average temperatures, average relative humidity, dew point, discomfort index and temperature-humidity index) based on public weather station records were compared based on three criteria [GxE estimate as measured by the slope term; theoretical accuracy of the genomic estimated breeding values (GEBV); deviation of GEBV per environmental value]. Relative humidity (for WN and WW) and maximum temperature (for OTW, TNB, and NBA) are the recommended environmental gradients for the studied traits. The acute HS (average of 30 days before measurement date) was the critical period recommended for OTW. For WN and WW, a period of 34 days prior to farrowing up to weaning is recommended. For TNB and NBA, the critical period of 20 days prior breeding to 30 days into gestation is recommended. In general, WN and WW were largely affected by the environment, while the remaining traits showed moderate correlations (OTW, TNB, and NBA). Heritabilities estimated for HT ranged from 0.08 (WW) to 0.25 (OTW). In summary, these results suggest that there is genotype-by-environment interaction for all traits analyzed, and genetic progress can be achieved through genetic selection.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".