Herbivore-induced volatiles reduce the susceptibility of neighboring tomato plants to transmission of a whitefly-borne begomovirus
Bibliographic record
Abstract
Plant viruses exist in a broader ecological community that includes non-vector herbivores that can impact vector abundance, behavior, and virus transmission within shared host plants. However, little is known about the effects of non-vector herbivore infestation on virus transmission by vector insects on neighboring plants through inter-plant airborne chemicals. In this study, we investigated how volatiles emitted from tomato plants infested with the two-spotted spider mite (Tetranychus urticae) affect the infection of neighboring plants by tomato yellow leaf curl virus (TYLCV) transmitted by whitefly (Bemisia tabaci). Exposure of neighboring tomato plants to volatiles released from T. urticae-infested tomato plants reduced subsequent herbivory as well as TYLCV transmission and infection, and the jasmonic acid signaling pathway was essential for generation of the inter-plant defense signals. We also demonstrated that (E)-β-ocimene and methyl salicylic acid were two volatiles induced by T. urticae that synergistically attenuated TYLCV transmission and infection in tomato. Thus, our findings suggest that plant-plant communication via volatiles likely represents a widespread defensive mechanism that substantially contributes to plant fitness. Understanding such phenomena may help us to predict the occurrence and epidemics of multiple herbivores and viruses in agroecosystems, and ultimately to manage pest and virus outbreaks.
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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 | 0.000 |
| 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".