Genotype × environment interaction as it relates to egg production in turkeys (Meleagris gallopavo)
Bibliographic record
Abstract
Genotype x environment (GxE) interactions can reduce the accuracy of a model to predict the performance of an animal and have an undesirable influence if not accounted for when estimating breeding values. Consequently, identification of these GxE is necessary when considering a turkey breeding program. Reranking based on the genetic prediction of turkey egg production, fertility, and hatchability in different seasons was indicative of a potential GxE interaction. Quantification of the GxE interactions was based on the genetic correlation estimated when traits were expressed in different seasons. Egg production was expressed as the percentage of days with an egg produced; fertility represented the proportion of hatched eggs that contained a fertile embryo; and hatchability was defined as the percentage of fertile eggs that produced a live bird. Variance components and heritability for egg production, fertility, and hatchability were estimated using ASReml. The heritability (h(2)) of egg production was calculated to be 0.32 for both lines with the phenotypic and genetic variance, 141.3 and 45.58 (percent days with egg produced)(2) and 118.3 and 38.35 (percent days with egg produced)(2) for female and male lines, respectively. The h(2) estimates for fertility were 0.08 in both lines with and of 293.3%(2) and 24.03%(2), and 576.9%(2) and 48.43%(2) for female and male lines, respectively. The hatchability h(2), and estimates were 0.09, 267.1%(2), and 24.44%(2), respectively, for the female line and 0.15, 582.2%(2), and 90.01%(2) for the male line, respectively. Based on an animal model, the variance components were used to calculate estimated breeding values for each trait. The annual fluctuation in estimated breeding values resulted in the need to evaluate egg number, fertility, and hatchability as 2 traits, summer and winter lay. The correlation between the 2 traits was less than unity (female line: r(egg production) = 0.76, r(fertility) = -0.20, r(hatchability) = 0.75 and male line: r(egg production) = 0.86, r(fertility) = 0.19, r(hatchability) = 0.68) suggesting a GxE interaction, and animals will significantly rerank in genetic predictions for these reproductive phenotypes in different seasons of lay. Egg production, fertility, and hatchability in turkeys could be considered as 2 distinct traits in an animal model based on season of lay.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".