Use of arbuscular mycorrhizal fungi to improve the drought tolerance of Cupressus atlantica G.
Bibliographic record
Abstract
In this study, we investigated whether indigenous arbuscular mycorrhizal (AM) fungi could improve the tolerance of Cupressus atlantica against water deficit. We tested a gradient of watering regime spanning from 90% to 25% of soil retention capacity of water on mycorhized and non-mycorhized seedlings in pot cultures with sterilized and non-sterilized soils. Our result showed a positive impact of AM fungi on shoot height, stem diameter and biomass as well as on the growth rate. We also observed that inoculation with AM fungi significantly improved uptake of minerals by C. atlantica in both sterilized and non-sterilized soils independently of water regimes. We found that mycorhized plants maintained higher relative water content (RWC) and water potential compared with non-mycorhized plants that were subjected to drought-stress regimes (50% and 25% of soil retention capacity). The contents of proline and of soluble sugars showed that their concentrations decreased in non-mycorhized plants subjected to DS. Superoxide dismutase (SOD) and catalase (CAT) activities also decreased in non-mycorhized plants submitted to DS compared to mycorhized plants. The same pattern was observed by measuring peroxidase (POD) enzyme activity. The results demonstrated that AM fungal inoculation promoted the growth and tolerance of C. atlantica against DS in pot cultures. Therefore, mycorrhizal inoculation could be a potential solution for the conservation and reestablishment of C. atlantica in its natural ecosystem.
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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) | 0.000 | 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 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".