Foliar application of plant-derived peptides decreases the severity of leaf rust (Puccinia triticina) infection in bread wheat (Triticum aestivum L.)
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Screening and developing novel antifungal agents with minimal environmental impact are needed to maintain and increase crop production, which is constantly threatened by various pathogens. Small peptides with antimicrobial and antifungal activities have been known to play an important role in plant defense both at the pathogen level by suppressing its growth and proliferation as well as at the host level through activation or priming of the plant's immune system for a faster, more robust response against fungi. Rust fungi (Pucciniales) are plant pathogens that can infect key crops and overcome resistance genes introduced in elite wheat cultivars. RESULTS: We performed an in vitro screening of 18 peptides predominantly of plant origin with antifungal or antimicrobial activity for their ability to inhibit leaf rust (Puccinia triticina, CCDS-96-14-1 isolate) urediniospore germination. Nine peptides demonstrated significant fungicidal properties compared to the control. Foliar application of the top three candidates, β-purothionin, Purothionin-α2 and Defensin-2, decreased the severity of leaf rust infection in wheat (Triticum aestivum L.) seedlings. Additionally, increased pathogen resistance was paralleled by elevated expression of defense-related genes. CONCLUSIONS: Identified antifungal peptides could potentially be engineered in the wheat genome to provide an alternative source of genetic resistance to leaf rust.
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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 | 0.000 |
| 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) | 0.000 | 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 it