Exogenous Abscisic Acid and Gibberellic Acid Elicit Opposing Effects on <i>Fusarium graminearum</i> Infection in Wheat
Bibliographic record
Abstract
Although the roles of salicylate (SA) and jasmonic acid (JA) have been well-characterized in Fusarium head blight (FHB)-infected cereals, the roles of other phytohormones remain more ambiguous. Here, the association between an array of phytohormones and FHB pathogenesis in wheat is investigated. Comprehensive profiling of endogenous hormones demonstrated altered cytokinin, gibberellic acid (GA), and JA metabolism in a FHB-resistant cultivar, whereas challenge by Fusarium graminearum increased abscisic acid (ABA), JA, and SA in both FHB-susceptible and -resistant cultivars. Subsequent investigation of ABA or GA coapplication with fungal challenge increased and decreased FHB spread, respectively. These phytohormones-induced effects may be attributed to alteration of the F. graminearum transcriptome because ABA promoted expression of early-infection genes, including hydrolases and cytoskeletal reorganization genes, while GA suppressed nitrogen metabolic gene expression. Neither ABA nor GA elicited significant effects on F. graminearum fungal growth or sporulation in axenic conditions, nor do these phytohormones affect trichothecene gene expression, deoxynivalenol mycotoxin accumulation, or SA/JA biosynthesis in F. graminearum-challenged wheat spikes. Finally, the combined application of GA and paclobutrazol, a Fusarium fungicide, provided additive effects on reducing FHB severity, highlighting the potential for combining fungicidal agents with select phytohormone-related treatments for management of FHB infection in wheat.
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 | 0.000 |
| 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) | 0.001 | 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".