Resistance to Gibberella ear rot in maize: Insights from near‐isogenic line populations
Bibliographic record
Abstract
Abstract Gibberella ear rot (GER) of maize, caused by Fusarium graminearum , poses a serious threat to human and animal safety as mycotoxins are deposited in the grain during fungal colonization and are hazardous to human and animal health. Currently, no completely resistant germplasm has been identified, and the underlying mechanisms of resistance remain unclear. In this study, we evaluated three near‐isogenic line (NIL) populations for resistance to GER—NC344 × H100 (DRIL), B73 × Oh43 (nNIL), and B73 × teosinte (tNIL)—across multiple environments. The recurrent parents, H100 and B73, were moderately resistant to GER. NC344 is susceptible to GER. Oh43 is moderately resistant to GER. The teosinte donor parent, PI 384071, had unknown resistance to GER. We employed two inoculation methods—kernel injection and silk channel injection—to assess their impact on genotype response to F. graminearum . The inoculation method did not significantly affect genotype response, although kernel inoculations produced more consistent disease levels. We identified lines with significantly increased susceptibility to GER compared to their recurrent parent in each population. We employed quantitative trait locus (QTL) mapping to identify markers associated with GER in the NC344 × H100 population. We identified QTL on chromosomes 4, 5, and 9. We highlight a large region on chromosome 5 that may harbor important alleles for GER resistance and for resistance to other ear rots. This study underscores the utility of NILs in dissecting the genetic basis of GER resistance and provides valuable resources for future fine mapping, gene discovery, and resistance breeding.
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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".