Comparing diploid and triploid apples from a diverse collection
Bibliographic record
Abstract
Abstract Apples ( Malus X. domestica Borkh.) are an economically important fruit species and the focus of continuing breeding efforts around the world. While most apple varieties are diploid, ploidy levels vary across the species, and triploids may be used in breeding despite poor fertility. The impact of ploidy on agricultural traits in apple is not well understood but is an important factor to consider when breeding new apple varieties. Here, we use mean heterozygosity values to categorize 970 apple accessions as diploid or triploid and then contrast apples of varying ploidy levels across 10 agriculturally important traits with sample sizes ranging from 427 to 928 accessions. After correction for multiple testing, we determine that triploids have significantly higher phenolic content. By examining historical release dates for apple varieties, our findings suggest that contemporary breeding programs are primarily releasing diploid varieties, and triploids tend to be older varieties. Ultimately, our results suggest that phenotypic differences between diploids and triploids are subtle and often insignificant indicating that triploids may not provide substantial benefit above diploids to apple breeding programs.
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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 | 0.001 |
| 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 | 0.001 |
| 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".