Changes in anatomy and terpene chemistry in roots of Douglas-fir seedlings following treatment with methyl jasmonate
Bibliographic record
Abstract
Replicated trials were conducted on two full-sibling families of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) seedlings. In response to the application of a 0.01% solution of methyl jasmonate (MeJA) to the soil of potted seedlings, numerous anatomical and chemical changes were observed in the roots, stem and foliage. These changes were, for the most part, similar for both sib groups. Methyl jasmonate induced traumatic resin duct formation in roots and stems. Chemical differences between MeJA-treated and control seedlings were mainly limited to the roots and stem, though some changes also occurred in the foliage. A total of 35 terpenoids were observed in the P. menziesii seedlings. In response to MeJA treatment, several of the 22 detected monoterpenoids (linalool, bornyl acetate, camphene, myrcene, alpha- and beta-pinene, tricyclene and beta-phellandrene) increased significantly in roots and stems, whereas (E)-beta-ocimene decreased significantly in the foliage. Four of the five detected sesquiterpenoids (alpha-humulene, germacrene D, longifolene and (E)-caryophyllene) increased significantly following MeJA application, mainly in the root and stem. Four of the eight detected diterpenoids (abietate, levopimarate, palustrate and sandaracopimarate) increased in response to MeJA treatment, but only in root and stem tissue. This study provides the first description of the effects of MeJA applied to roots through the soil on the anatomy and terpene chemistry of a gymnosperm. This comprehensive inventory of terpenoids in P. menziesii, with and without MeJA treatment, may facilitate identification of terpenoid-related resistance traits. Potential practical applications of MeJA treatment of conifer roots as a pest management strategy are discussed.
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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 | 0.001 |
| 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".