Herbivore‐induced plant volatiles allow detection of <i>Trichoplusia ni</i> (Lepidoptera: Noctuidae) infestation on greenhouse tomato plants
Bibliographic record
Abstract
BACKGROUND: Monitoring of insect populations is an important component of integrated pest management and typically is based on the presence and number of insects in various development stages. Yet plants respond to insect herbivory and release herbivore-induced plant volatiles (HIPVs), which could be exploited in monitoring systems. The present objective was to investigate whether the information associated with HIPVs has potential to become part of advanced technologies for monitoring pest insect populations. RESULTS: In a laboratory experiment, it was determined that tomato plants, Lycopersicon esculentum Mill cv. clarence, each infested with 20 caterpillars of the cabbage looper, Trichoplusia ni (Hübner), emit HIPVs, of which (Z)-3-hexenyl acetate, (E)-beta-ocimene and beta-caryophyllene were selected as chemicals indicative of herbivory. Using an ultrafast portable gas chromatograph (zNose()) in a research greenhouse and in a commercial greenhouse, it was possible (i) to reveal differential emissions of these three indicator chemicals from plants with or without herbivory, (ii) to detect herbivory within 6 h of its onset, (iii) to track changes in indicator chemical emissions over time and (iv) to study the effect of environmental and crop-maintenance-related factors on the emission of indicator chemicals. CONCLUSION: HIPVs appear to be promising as reliable indicators of plant health, but further studies are needed to fully understand the potential of this concept.
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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".