Investigating the link between genetic distance and seed yield in hybrid Brassica napus L. using phenotypic and genotypic methods
Bibliographic record
Abstract
Brassica napus L. is an economically important oilseed species cultivated across Western Canada. Hybrid B. napus cultivars compose the majority of the market due to their seed yield and agronomic quality. It is important to attempt to predict high-yielding parental combinations in order to conserve resources during experimental hybrid evaluation. Genetic distance between parents has been implicated in producing high-yielding hybrids and is used as one criteria for determining parental combinations.In the current study, the genetic distance between high erucic acid rapeseed (HEAR) genotypes of B. napus was established using both phenotypic and genotypic criteria. Phenotypic criteria took the form of nine agronomic and seed quality traits gathered from 318 distinct B. napus genotypes over the 2013 and 2014 field seasons in Southern Manitoba. Genotypic criteria took the form of either 291,782 SNP markers identified in 231 distinct B. napus genotypes using genotyping-by-sequencing (GBS) or 230 polymorphic sequence-related amplified polymoprhism (SRAP) markers identified in 160 B. napus genotypes. The genetic distance between available pollinators and a single male-sterile female was established using each set of criteria in an attempt to correlate genetic distance with hybrid yield. Regression analysis was conducted with yield data from hybrid genotypes gathered from 37 field sites from 2011-2014. Using the phenotypic-derived genetic distance, a significant correlation between genetic distance and hybrid yield was uncovered explaining either 22 % or 42 % of the variation in hybrid yield depending upon whether hybrids were grown at three or more, or five or more sites in the analysis, respectively. No significant link was found between GBS or SRAP-derived genetic distance and hybrid yield. These results provide evidence that that phenotypic criteria can be used to establish genetic distance with utility in the selection of high-yielding hybrid genotypes.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".