Can Parentage Analysis Facilitate Breeding Activities in Root and Tuber Crops?
Bibliographic record
Abstract
Controlled pollination in root and tuber crops is challenging. Complex ploidy, cross-incompatibility, erratic flowering patterns, outcrossing, etc., limit the efficiency of breeding progress in these crops. Half-sib breeding that involves random pollination among parents is a viable method to harness genetic gain in outcrossing crops that are problematic for performing planned and controlled pollination. The authenticity of resulting progenies from the half-sib breeding is essential to monitor the selection gain in the breeding program. Parentage analysis facilitated by molecular markers is among the available handy tools for crop breeders to maximize genetic gain in a breeding program. It can help to resolve the identity of half-sib progenies and reconstruct the pedigree in the outcrossing crops. This paper reviews the potential benefits of parentage analysis in breeding selected outcrossing root and tuber crops. It assesses how paternity analysis facilitates breeding activities and the ways it improves genetic gain in the root and tuber breeding programs. Conscious use of complementary techniques in the root and tuber breeding programs can increase the selection gain by reducing the long breeding cycle and cost, as well as reliable exploitation of the heritable variation in the desired direction.
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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 | 0.001 |
| 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) | 0.000 | 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".