Lavender sensitivity to water stress: Comparison between eleven varieties across two phenological stages
Bibliographic record
Abstract
Essential oils from Lavandula angustifolia Mill. and Lavandula x intermedia Emeric x Loisel composed of concentrated terpene mixtures, and are highly produced due to their economic value. In the Mediterranean area, the production is threatened by the increasing frequency and intensity of drought events, leading to the loss of crops. Thus, we aimed to evaluate the response to water stress and the tolerance of the main French cultivated varieties of L. angustifolia and L. x intermedia during flowering period, based on the response of their primary metabolic traits (e.g. growth, photosynthesis, stomatal conductance) and specialized metabolic traits (terpene storage and emissions related to the plant defense system). Two treatments were applied: a control where plants received 300 mL every day (≈75% of substrate field capacity) and a stress where plants received 100 mL every two days (≈25% of substrate field capacity). Our results showed that both species featured a drought-tolerant strategy to cope with water stress with a more competitive strategy in L. angustifolia. Water deficit modified the amounts of stored terpenes in both species which could be economically harmful for the sector related to essential oil production. Moreover, some compounds such as bornyl acetate were highlighted as potential defense compounds. The study also highlighted that the varieties ‘Rapido’ (L. angustifolia), arecent variety developed in France, and ‘Sumian’ (L. x intermedia), could be the best candidates to cultivate under intense drought.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".