Genetic parameter estimation and selection in advanced breeding population of white Guinea yam
Bibliographic record
Abstract
White Guinea yam (Dioscorea rotundata Poir.) is an important tuber crop grown extensively in tropical regions of West African yam belt. Tuber yield, dry matter content, and tolerance to yam mosaic virus are key traits used for identification and selection of superior varieties for commercial deployment. In this study, we estimated genetic parameters for fresh tuber yield, tuber dry matter content, and quantitative field tolerance to yam mosaic virus in 49 clones grown in multi-environment trials (METs). We conducted genomic prediction involving 6337 single nucleotide polymorphisms (SNPs) and phenotypic field evaluation of data collected on the three traits from four sites. Additive genetic and non-genetic factors contributed significantly to phenotypic variation of studied yam traits in METs but to varying degrees. The non-genetic effects were relatively high for most of the measured traits. Narrow-sense heritability values were low (<0.30) for all studied traits. Further analysis of the performance of the clones at test sites with additive main effects and multiplicative interaction (AMMI) analysis exhibited significant genotype by environment interactions (GEI) for the three traits. The AMMI identified TDr10/00412, TDr11/00055, and TDr09/00135 clones with lowest mean trait stability index and outstanding performance for fresh tuber yield (t ha−1), tuber dry matter, and mosaic virus resistance across sites. The elite clones identified could serve as useful source of alleles for the genetic improvement of the crop and possibly considered for release to farmers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".