Effectiveness of introgression of resistance loci for Gibberella ear rot from two European flint landraces into adapted elite maize (Zea mays L.)
Bibliographic record
Abstract
European flint landraces are a major class of maize possessing favorable alleles for improving host resistance to Gibberella ear rot (GER) disease which reduces yield and contaminates the grains with mycotoxins. However, the incorporation of these landraces into breeding programs requires a clear understanding of the effectiveness of their introgression into elite materials. We evaluated 15 pre-selected doubled haploid (DH) lines from two European flint landraces, "Kemater Landmais Gelb" (KE) and "Petkuser Ferdinand Rot" (PE), together with two adapted elite flint lines and seven standard lines for GER severity as the main trait, and several adaptation traits (plant height, days to silking, seed-set, plant vigor) across four environments. From this evaluation, three KE DH lines and one PE DH line, with the lowest GER severity, were selected and used as donor parents that were crossed with the two adapted and GER susceptible flint lines (Flint1 and Flint2) to develop six bi-parental DH populations with 34-145 DH lines each. Each DH population was evaluated across two locations. Correlations between GER severity, which was the target trait, and adaptation traits were weak (-0.02 to 0.19). GER severity of lines from PE landrace was on average 2-fold higher than lines from KE landrace, indicating a clear superiority of the KE landrace lines. Mean GER severity of the DH populations was 39.4-61.0% lower than the adapted elite flint lines. All KE-derived DH populations were on average more resistant (27.0-36.7%) than the PE-derived population (51.0%). Highly resistant lines (1.3-5.2%) were found in all of the populations, suggesting that the DH populations can be successfully integrated into elite breeding programs. The findings demonstrate that selected KE landrace lines used as donors were effective in improving GER resistance of the adapted elite inbreds.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".